The UK High-End Computing Consortium for Biomolecular Simulation
Lead Research Organisation:
University of Bristol
Department Name: Chemistry
Abstract
Simulations using powerful computers can show how biological molecules 'work' in atomic detail. For example, molecular simulations can show drugs bind to their biological targets, how enzymes catalyse reactions, and how proteins fold into their functional forms. Biomolecular simulation is a vibrant and growing area, making increasingly significant contributions to biology. It is an area of growing international importance. Simulations of biological molecules complement experiments in building a molecular-level understanding of biology: they can test hypotheses and interpret and analyse experimental data in terms of interactions at the atomic level. A wide variety of simulation techniques have been developed, applicable to a range of different problems in biomolecular science. Biomolecular simulations have already shown their worth in helping to analyse how enzymes catalyse biochemical reactions, and how proteins adopt their functional structures e.g. within cell membranes. They contribute to the design of drugs and catalysts, and in understanding the molecular basis of disease. Simulations have played a key role in developing the conceptual framework now at the heart of biomolecular science, that is, the understanding that the way that biological molecules move and flex - their dynamics - is central to their function. Developing methods from chemical physics and computational science will open exciting new opportunities in biomolecular science, including in drug development and biotechnology. Much biomolecular simulation demands high end computing (HEC) resources: e.g. large-scale simulations of biological machines such as the ribosome, proton pumps and motors, membrane receptor complexes and even whole viruses. A particular challenge is the integration of simulations across length and timescales: different types of simulation method are required for different types of problems).
Biomolecular Simulations are contributing increasingly to areas such as biotechnology, drug design, biocatalysis and biomedicine. The UK has a strong community in this field, recognized by the recent (2011) establishment by EPSRC of CCP-BioSim (ccpbiosim.ac.uk), the UK Collaborative Computational Project for Biomolecular Simulation at the Life Sciences Interface (and the subsequent award of 'widening participation' funds in 2012). We believe there is a clear, growing and demonstrable need for high-end computing in this field, and propose a new HEC Consortium in biomolecular simulation. Working with CCP-BioSim, this Consortium will help bring HEC to a wider community, including non-traditional users and experimental bioscientists, and engage physical and computer scientists in biological applications.
Biomolecular Simulations are contributing increasingly to areas such as biotechnology, drug design, biocatalysis and biomedicine. The UK has a strong community in this field, recognized by the recent (2011) establishment by EPSRC of CCP-BioSim (ccpbiosim.ac.uk), the UK Collaborative Computational Project for Biomolecular Simulation at the Life Sciences Interface (and the subsequent award of 'widening participation' funds in 2012). We believe there is a clear, growing and demonstrable need for high-end computing in this field, and propose a new HEC Consortium in biomolecular simulation. Working with CCP-BioSim, this Consortium will help bring HEC to a wider community, including non-traditional users and experimental bioscientists, and engage physical and computer scientists in biological applications.
Planned Impact
Who will benefit from this research?
As well as biosimulation specialists, a broad cross-section of bioscientists who are concerned, in some way or other, with the nature and behaviour of biomolecules at the atomic level e.g. X-ray crystallographers, NMR spectroscopists, single-molecule biophysicists, mass spectrometrists, enzymologists, medicinal chemists, chemical biologists. It will contribute to synthetic biology, biocatalysis and drug design. The UK High-End Computing Consortium for Biomolecular Simulation will help achieve maximum benefit from national HEC investment. It will assist the biological community to use high-end computing facilities and help physical scientists tackle biological problems. In the longer term, there is the potential for the project to impact on the general public through improvements in health and quality of life.
How will they benefit from this research?
The "molecule-oriented" bioscience community will benefit through access to tools, training, and trained simulation specialists that enable novel and more effective multidisciplinary projects where computational methods enhance and extend their core experimental approaches. Such integrated studies have a higher probability of producing high-impact discoveries and developments and so fostering such activities will enhance UK competitiveness in the international research arena. The Consortium will provide tools and resources to facilitate this. These tools should give rise to major benefits (e.g. high-impact papers, major international grant awards) over the term of the project, and in future. In the longer term the Consortium will be helping train a new generation of bioscientists who can work confidently and knowledgeably across the theory/experimental divide. What is 'state-of-the-art' today with regard to computational power and methodology, and so might be regarded as somewhat esoteric, will be on the desktop of bioscientists in 5-10 years time. Impacts on the health and quality of life of the general public are likely to come primarily from the application of the methodologies fostered and disseminated (e.g. by CCP-BioSim) to drug design and discovery. Computational methods are already well-established in Pharma, since they can hasten and cheapen the process of drug discovery and development. The more computationally-intensive methods of biomolecular simulation are gaining ground, as improvements in computational power make accuracy and time-to-solution competitive with 'wet' methods. The Consortium will help improve this by a) helping train new generations of researchers with the necessary HEC skills and b) providing a forum to enhance industrial-academic research links (members of the Consortium have established links with many large and smaller pharmaceutical/biotech companies (e.g. AZ, Vernalis, Phaminox, GSK, Evotec, J&J, Pfizer, Oxford Nanopore). The benefits to the public in the longer term come from new and/or cheaper medicinal products, plus the potential for simulations has in addressing the 3Rs and biosecurity.
What will be done to ensure that they benefit from this research?
Through close coordination with CCP-BioSim and other bodies:
- The programme of workshops, co-organised with leading experimentalists in key disciplines, examining and fostering links across the simulation/experimental interface
- The annual conference focused on exemplifying and encouraging the highest quality interdisciplinary research.
- Training workshops introducing non-specialist bioscientists to high quality simulation methods, and specialists to the latest technological advances.
- Associated on-line training packages, available any time, any place.
- Training workshops and tools developed to aid access to HPC resources for those with a bioscience background.
Tools, software and data from development work will be made freely available, and disseminated via the web. Involvement of a wide community will ensure broad uptake
As well as biosimulation specialists, a broad cross-section of bioscientists who are concerned, in some way or other, with the nature and behaviour of biomolecules at the atomic level e.g. X-ray crystallographers, NMR spectroscopists, single-molecule biophysicists, mass spectrometrists, enzymologists, medicinal chemists, chemical biologists. It will contribute to synthetic biology, biocatalysis and drug design. The UK High-End Computing Consortium for Biomolecular Simulation will help achieve maximum benefit from national HEC investment. It will assist the biological community to use high-end computing facilities and help physical scientists tackle biological problems. In the longer term, there is the potential for the project to impact on the general public through improvements in health and quality of life.
How will they benefit from this research?
The "molecule-oriented" bioscience community will benefit through access to tools, training, and trained simulation specialists that enable novel and more effective multidisciplinary projects where computational methods enhance and extend their core experimental approaches. Such integrated studies have a higher probability of producing high-impact discoveries and developments and so fostering such activities will enhance UK competitiveness in the international research arena. The Consortium will provide tools and resources to facilitate this. These tools should give rise to major benefits (e.g. high-impact papers, major international grant awards) over the term of the project, and in future. In the longer term the Consortium will be helping train a new generation of bioscientists who can work confidently and knowledgeably across the theory/experimental divide. What is 'state-of-the-art' today with regard to computational power and methodology, and so might be regarded as somewhat esoteric, will be on the desktop of bioscientists in 5-10 years time. Impacts on the health and quality of life of the general public are likely to come primarily from the application of the methodologies fostered and disseminated (e.g. by CCP-BioSim) to drug design and discovery. Computational methods are already well-established in Pharma, since they can hasten and cheapen the process of drug discovery and development. The more computationally-intensive methods of biomolecular simulation are gaining ground, as improvements in computational power make accuracy and time-to-solution competitive with 'wet' methods. The Consortium will help improve this by a) helping train new generations of researchers with the necessary HEC skills and b) providing a forum to enhance industrial-academic research links (members of the Consortium have established links with many large and smaller pharmaceutical/biotech companies (e.g. AZ, Vernalis, Phaminox, GSK, Evotec, J&J, Pfizer, Oxford Nanopore). The benefits to the public in the longer term come from new and/or cheaper medicinal products, plus the potential for simulations has in addressing the 3Rs and biosecurity.
What will be done to ensure that they benefit from this research?
Through close coordination with CCP-BioSim and other bodies:
- The programme of workshops, co-organised with leading experimentalists in key disciplines, examining and fostering links across the simulation/experimental interface
- The annual conference focused on exemplifying and encouraging the highest quality interdisciplinary research.
- Training workshops introducing non-specialist bioscientists to high quality simulation methods, and specialists to the latest technological advances.
- Associated on-line training packages, available any time, any place.
- Training workshops and tools developed to aid access to HPC resources for those with a bioscience background.
Tools, software and data from development work will be made freely available, and disseminated via the web. Involvement of a wide community will ensure broad uptake
Organisations
- University of Bristol (Lead Research Organisation)
- Ryerson University (Collaboration)
- Complutense University of Madrid (Collaboration)
- Vertex Pharmaceuticals (Collaboration)
- European Cooperation in Science and Technology (COST) (Collaboration)
- University of Waikato (Collaboration)
- Novartis (Collaboration)
- University College Dublin (Collaboration)
- Budapest University of Technology and Economics (Collaboration)
- UCB Pharma (Collaboration)
- UNIVERSITY OF CAMBRIDGE (Collaboration)
- EVOTEC (Collaboration)
- University of Bath (Collaboration)
- Marlow Foods (Collaboration)
- Heriot-Watt University (Collaboration)
- Immunocore Ltd (Collaboration)
- Sanofi (Collaboration)
- Johnson & Johnson (Collaboration)
- Research Complex at Harwell (Collaboration)
- Evotec (UK) Ltd (Collaboration)
- UNIVERSITY OF EDINBURGH (Collaboration)
- Autonomous University of Barcelona (UAB) (Collaboration)
- University of Bristol (Collaboration)
People |
ORCID iD |
| Adrian Mulholland (Principal Investigator) |
Publications
Mulholland A
(2020)
COVID19 - Computational Chemists Meet the Moment
in Journal of Chemical Information and Modeling
Thongdee P
(2022)
Virtual Screening Identifies Novel and Potent Inhibitors of Mycobacterium tuberculosis PknB with Antibacterial Activity.
in Journal of chemical information and modeling
Punkvang A
(2019)
Simulations of Shikimate Dehydrogenase from Mycobacterium tuberculosis in Complex with 3-Dehydroshikimate and NADPH Suggest Strategies for MtbSDH Inhibition.
in Journal of chemical information and modeling
Deeks HM
(2020)
Interactive Molecular Dynamics in Virtual Reality Is an Effective Tool for Flexible Substrate and Inhibitor Docking to the SARS-CoV-2 Main Protease.
in Journal of chemical information and modeling
Musgaard M
(2016)
Steered Molecular Dynamics Simulations Predict Conformational Stability of Glutamate Receptors.
in Journal of chemical information and modeling
Mattedi G
(2019)
Understanding Ligand Binding Selectivity in a Prototypical GPCR Family.
in Journal of chemical information and modeling
Abraham M
(2019)
Sharing Data from Molecular Simulations.
in Journal of chemical information and modeling
Corey RA
(2019)
Insights into Membrane Protein-Lipid Interactions from Free Energy Calculations.
in Journal of chemical theory and computation
Ansell TB
(2021)
Relative Affinities of Protein-Cholesterol Interactions from Equilibrium Molecular Dynamics Simulations.
in Journal of chemical theory and computation
Kaiyawet N
(2015)
High-level QM/MM calculations support the concerted mechanism for Michael addition and covalent complex formation in thymidylate synthase.
in Journal of chemical theory and computation
| Description | Research data and policy |
| Geographic Reach | National |
| Policy Influence Type | Contribution to new or improved professional practice |
| URL | https://www.chemistryworld.com/news/ukri-finds-itself-in-hot-water-too-over-researchfish-cyberbullyi... |
| Description | UKRI research data capture approaches |
| Geographic Reach | National |
| Policy Influence Type | Contribution to new or improved professional practice |
| URL | https://www.researchprofessionalnews.com/rr-news-uk-research-councils-2023-1-researchfish-tweets-aga... |
| Description | An in silico structure-based approach to map the druggable allosteric space of membrane receptors |
| Amount | £310,098 (GBP) |
| Funding ID | BB/R007101/1 |
| Organisation | Biotechnology and Biological Sciences Research Council (BBSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 02/2018 |
| End | 01/2021 |
| Description | AstraZeneca CASE studentship |
| Amount | £29,500 (GBP) |
| Organisation | AstraZeneca |
| Sector | Private |
| Country | United Kingdom |
| Start | 03/2017 |
| End | 02/2021 |
| Description | BI - XChem |
| Amount | £248,000 (GBP) |
| Organisation | Boehringer Ingelheim |
| Sector | Private |
| Country | Germany |
| Start | 01/2019 |
| End | 12/2020 |
| Description | BioNet - Dynamical Redesign of Biomolecular Networks |
| Amount | £1,184,999 (GBP) |
| Funding ID | 757850 |
| Organisation | European Commission |
| Sector | Public |
| Country | European Union (EU) |
| Start | 02/2018 |
| End | 01/2023 |
| Description | Combining quantum and classical methods to study bacterial membrane enzymes |
| Amount | £126,931 (GBP) |
| Organisation | The Leverhulme Trust |
| Sector | Charity/Non Profit |
| Country | United Kingdom |
| Start | 07/2018 |
| End | 07/2021 |
| Description | Diet and Health Research Industry Club |
| Amount | £398,037 (GBP) |
| Funding ID | BB/M027449/1 and BB/M027597/1 |
| Organisation | Biotechnology and Biological Sciences Research Council (BBSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 10/2015 |
| End | 05/2018 |
| Description | EPSRC Flagship Software |
| Amount | £523,963 (GBP) |
| Funding ID | EP/P022138/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 06/2017 |
| End | 11/2019 |
| Description | EPSRC Project Grant |
| Amount | £293,994 (GBP) |
| Funding ID | EP/P011993/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 05/2017 |
| End | 04/2020 |
| Description | Industrial PhD studentship |
| Amount | £30,000 (GBP) |
| Organisation | Heptares Therapeutics Ltd |
| Sector | Private |
| Country | United Kingdom |
| Start | 03/2017 |
| End | 02/2020 |
| Description | John Fell Fund |
| Amount | £86,614 (GBP) |
| Organisation | University of Oxford |
| Sector | Academic/University |
| Country | United Kingdom |
| Start | 09/2016 |
| End | 12/2018 |
| Description | MPLS NIF FUND |
| Amount | £8,420 (GBP) |
| Organisation | University of Oxford |
| Sector | Academic/University |
| Country | United Kingdom |
| Start | 02/2017 |
| Description | Oracle for Research Cloud Fellowship |
| Amount | $100,000 (USD) |
| Organisation | Oracle Corporation |
| Sector | Private |
| Country | United States |
| Start | 02/2023 |
| End | 12/2023 |
| Description | PREDACTED Predictive computational models for Enzyme Dynamics, Antimicrobial resistance, Catalysis and Thermoadaptation for Evolution and Desig |
| Amount | € 2,482,332 (EUR) |
| Funding ID | 101021207 |
| Organisation | European Research Council (ERC) |
| Sector | Public |
| Country | Belgium |
| Start | 10/2021 |
| End | 09/2026 |
| Description | The UK High-End Computing Consortium for Biomolecular Simulation |
| Amount | £321,432 (GBP) |
| Funding ID | EP/R029407/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 11/2018 |
| End | 10/2022 |
| Description | Understanding gating kinetics in Cys-loop receptors |
| Amount | £345,655 (GBP) |
| Funding ID | BB/S001247/1 |
| Organisation | Biotechnology and Biological Sciences Research Council (BBSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 11/2018 |
| End | 10/2021 |
| Description | https://gtr.ukri.org/person/2A2990B1-E1E1-4888-8848-7C256C3A3B43 |
| Amount | £20,009,000 (GBP) |
| Funding ID | https://gtr.ukri.org/person/2A2990B1-E1E1-4888-8848-7C256C3A3B43 |
| Organisation | United Kingdom Research and Innovation |
| Sector | Public |
| Country | United Kingdom |
| Start | 01/2006 |
| End | 02/2033 |
| Title | Crystallography and QM/MM Simulations Identify Preferential Binding of Hydrolyzed Carbapenem and Penem Antibiotics to the L1 Metallo-beta-lactamase in the Imine Form |
| Description | MD trajectories, topologies, parameters and input files for the data presented in the paper Twidale et al. J Chem. Inf. Model. 2021. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2021 |
| Provided To Others? | Yes |
| Impact | Widespread bacterial resistance to carbapenem antibiotics is an increasing global health concern. Resistance has emerged due to carbapenem-hydrolyzing enzymes, including metallo-ß-lactamases (MßLs), but despite their prevalence and clinical importance, MßL mechanisms are still not fully understood. Carbapenem hydrolysis by MßLs can yield alternative product tautomers with the potential to access different binding modes. Here, we show that a combined approach employing crystallography and quantum mechanics/molecular mechanics (QM/MM) simulations allow tautomer assignment in MßL:hydrolyzed antibiotic complexes. Molecular simulations also examine (meta)stable species of alternative protonation and tautomeric states, providing mechanistic insights into ß-lactam hydrolysis. We report the crystal structure of the hydrolyzed carbapenem ertapenem bound to the L1 MßL from Stenotrophomonas maltophilia and model alternative tautomeric and protonation states of both hydrolyzed ertapenem and faropenem (a related penem antibiotic), which display different binding modes with L1. We show how the structures of both complexed ß-lactams are best described as the (2S)-imine tautomer with the carboxylate formed after ß-lactam ring cleavage deprotonated. Simulations show that enamine tautomer complexes are significantly less stable (e.g., showing partial loss of interactions with the L1 binuclear zinc center) and not consistent with experimental data. Strong interactions of Tyr32 and one zinc ion (Zn1) with ertapenem prevent a C6 group rotation, explaining the different binding modes of the two ß-lactams. Our findings establish the relative stability of different hydrolyzed (carba)penem forms in the L1 active site and identify interactions important to stable complex formation, information that should assist inhibitor design for this important antibiotic resistance determinant. |
| URL | https://data.bris.ac.uk/data/dataset/13pu85dfaobij2rumzql5buyy2/ |
| Title | Evolution of dynamical networks enhances catalysis in a designer enzyme |
| Description | Data related to: "Evolution of dynamical networks enhances catalysis in a designer enzyme". H. Adrian Bunzel, J. L. Ross Anderson, Donald Hilvert, Vickery L. Arcus, Marc W. van der Kamp, Adrian J. Mulholland. Nature Chemistry 2021. MD Trajectories of a designed and evolved Kemp eliminase (1A53-2 and 1A53-2.5) in complex with a ground state (GS) or transition state (TS, TS2) model. The ligands are called GS1, TS1, and TS3 in the raw data. Cluster analysis of each trajectory, discriminating between an open (0) or closed (1) state for each frame. Pymol Sessions to reproduce Figures 1-3 of the paper. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2021 |
| Provided To Others? | Yes |
| Impact | Activation heat capacity is emerging as a crucial factor in enzyme thermoadaptation, as shown by the non-Arrhenius behaviour of many natural enzymes. However, its physical origin and relationship to the evolution of catalytic activity remain uncertain. Here we show that directed evolution of a computationally designed Kemp eliminase reshapes protein dynamics, which gives rise to an activation heat capacity absent in the original design. These changes buttress transition-state stabilization. Extensive molecular dynamics simulations show that evolution results in the closure of solvent-exposed loops and a better packing of the active site. Remarkably, this gives rise to a correlated dynamical network that involves the transition state and large parts of the protein. This network tightens the transition-state ensemble, which induces a negative activation heat capacity and non-linearity in the activity-temperature dependence. Our results have implications for understanding enzyme evolution and suggest that selectively targeting the conformational dynamics of the transition-state ensemble by design and evolution will expedite the creation of novel enzymes. |
| URL | https://data.bris.ac.uk/data/dataset/l6hm9j11yil92bh9rvh27i7ge/ |
| Title | MemProtMD |
| Description | a datbase of all membrane protein structures and their interactions with lipids |
| Type Of Material | Database/Collection of data |
| Year Produced | 2015 |
| Provided To Others? | Yes |
| Impact | Considerable interest and uptake by membrane protein structural biologists in academia and industry (pharma). |
| URL | http://memprotmd.bioch.ox.ac.uk |
| Title | SWISH a new Hamiltonian Replica Exchange-based computational algorithm |
| Description | We developed a novel and effective computational approach to predict cryptic binding sites on targets of pharmaceutical interest. |
| Type Of Material | Computer model/algorithm |
| Year Produced | 2016 |
| Provided To Others? | Yes |
| Impact | The method has been described in an high-impact publication (JACS) and in a number of high-profile blogs in drug discovery. The PI has been invited by Pfizer and other pharmaceutical companies to give talks about the method. |
| Title | Simulation of Functional Motions in Enzymes |
| Description | Data related to: "Structure and function in homodimeric enzymes: simulations of cooperative and independent functional motions". Wells SA, Van der Kamp MW, Mulholland AJ. PLOS ONE, 2015. Results from two different simulation methods, normal-mode biased geometric simulations of flexible motion and conventional molecular dynamics, as applied to two different homodimeric enzymes, the DcpS scavanger decapping enzyme and citrate synthase. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2015 |
| Provided To Others? | Yes |
| Impact | Large-scale conformational change is a common feature in the catalytic cycles of enzymes. Many enzymes function as homodimers with active sites that contain elements from both chains. Symmetric and anti-symmetric cooperative motions in homodimers can potentially lead to correlated active site opening and/or closure, likely to be important for ligand binding and release. Here, we examine such motions in two different domain-swapped homodimeric enzymes: the DcpS scavenger decapping enzyme and citrate synthase. We use and compare two types of all-atom simulations: conventional molecular dynamics simulations to identify physically meaningful conformational ensembles, and rapid geometric simulations of flexible motion, biased along normal mode directions, to identify relevant motions encoded in the protein structure. The results indicate that the opening/closure motions are intrinsic features of both unliganded enzymes. In DcpS, conformational change is dominated by an anti-symmetric cooperative motion, causing one active site to close as the other opens; however a symmetric motion is also significant. In CS, we identify that both symmetric (suggested by crystallography) and asymmetric motions are features of the protein structure, and as a result the behaviour in solution is largely non-cooperative. The agreement between two modelling approaches using very different levels of theory indicates that the behaviours are indeed intrinsic to the protein structures. Geometric simulations correctly identify and explore large amplitudes of motion, while molecular dynamics simulations indicate the ranges of motion that are energetically feasible. Together, the simulation approaches are able to reveal unexpected functionally relevant motions, and highlight differences between enzymes. |
| URL | http://data.bris.ac.uk/data/dataset/1klro7qjw27xi19qrcs1bb2nt6/ |
| Description | Catalysis Hub |
| Organisation | Research Complex at Harwell |
| Department | UK Catalysis Hub |
| Country | United Kingdom |
| Sector | Public |
| PI Contribution | Modelling and simulation of enzyme mechanisms for applications in biocatalysts via the Catalysis Hub |
| Collaborator Contribution | Modelling and simulation of enzyme mechanisms for applications in biocatalysts via the Catalysis Hub and training of Hub PDRAs. |
| Impact | Catalysis is a core area of contemporary science posing major fundamental and conceptual challenges, while being at the heart of the chemical industry - an immensely successful and important part of the overall UK economy (generating in excess of £50 billion per annum). UK catalytic science currently has a strong presence, but there is intense competition in both academic and industrial sectors, and a need for UK industrial activity to shift towards new innovative areas posing major challenges for the future. In light of these challenges the UK Catalysis Hub endeavours to become a leading institution, both nationally and internationally, in the field and acts to coordinate, promote and advance the UK catalysis research portfolio. With a strong emphasis on effective use of the world-leading facilities on the RAL campus. Structure The project has four mature themes and a fifth theme starting in 2015 , each with a lead investigator as PI - Catalysis by Design (Catlow); Energy (Hardacre); Environment (Hutchings); Chemical Transformations (Davidson) and the new Biocatalysis and Biotransformations (Nick Turner Manchester) - with the design theme based in the Harwell hub. Each theme is supported by £3 - 3.5M EPSRC funding over 5 years and within each theme there are typically six to eight sub-projects funded initially for 2 years, involving collaborative teams working at a variety of sites throughout the UK. Professor Hutchings acts as director of the whole national programme for the first three year period and chairs the management group, which is supported by a steering group and an industrial advisory panel. We note that engagement with industry is one of the key aims of the catalysis hub project. As well as hosting the design theme, the centre within the Research Complex at Harwell (RCaH) will coordinate the programme, be a base for national and international visitors and provide both training and outreach activities. |
| Start Year | 2015 |
| Description | Collaboration on Enzyme activation heat capacity (Chris Pudney, Vic Arcus etc.) |
| Organisation | University of Bath |
| Department | Department of Biology and Biochemistry |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Simulation studies and advice on simulation studies (conducted by research students) to 'translate' experimental data to specific structural/dynamic phenomena at the atomistic level (as uncovered through simulation). Detailed combined analysis of experimental and computational data. Co-supervision of postgraduate research students. |
| Collaborator Contribution | Performing experiments and analysis to further understand simulation data. (Co-)writing of publications. Dissemination of results. |
| Impact | Multidisciplinary - enzyme kinetics (Arcus, Pudney), spectroscopy studies of protein dynamics (Pudney); enzyme-substrate complex simulations (Van der Kamp). Multiple publications (see publications). Co-supervised PhD student thesis: https://purehost.bath.ac.uk/ws/portalfiles/portal/202462532/Rory_Crean_Thesis.pdf |
| Start Year | 2018 |
| Description | Collaboration on Enzyme activation heat capacity (Chris Pudney, Vic Arcus etc.) |
| Organisation | University of Waikato |
| Department | Faculty of Science and Engineering |
| Country | New Zealand |
| Sector | Academic/University |
| PI Contribution | Simulation studies and advice on simulation studies (conducted by research students) to 'translate' experimental data to specific structural/dynamic phenomena at the atomistic level (as uncovered through simulation). Detailed combined analysis of experimental and computational data. Co-supervision of postgraduate research students. |
| Collaborator Contribution | Performing experiments and analysis to further understand simulation data. (Co-)writing of publications. Dissemination of results. |
| Impact | Multidisciplinary - enzyme kinetics (Arcus, Pudney), spectroscopy studies of protein dynamics (Pudney); enzyme-substrate complex simulations (Van der Kamp). Multiple publications (see publications). Co-supervised PhD student thesis: https://purehost.bath.ac.uk/ws/portalfiles/portal/202462532/Rory_Crean_Thesis.pdf |
| Start Year | 2018 |
| Description | Collaboration with Beata Vertessy |
| Organisation | Budapest University of Technology and Economics |
| Department | Department of Biotechnology and Food Sciences |
| Country | Hungary |
| Sector | Academic/University |
| PI Contribution | We initiated a collaborative project to studey the role of conserved arginine residues in the dUTPase enzyme. We first performed a PDB-side structural analysis to compare arginine residues in NTP cleaving enzymes. Subsequently, we carried out QM/MM and MD calculations to establish the function of the key arginine finger residue in dUTPases. |
| Collaborator Contribution | In this collaboration the experimental group led by Beata Vertessy performed X-Ray crystallography experiments togeter with biochemical experiments to use this in our joint project. |
| Impact | Nagy et al, Journal of the American Chemical Society, 2016, DOI: 10.1021/jacs.6b09012 Multidisciplinary collaboration with experimental X-Ray crystallography and biochemistry group and our theoretical and computational biophysical chemistry group. |
| Start Year | 2014 |
| Description | Collaboration with Bristol university on predicting drug-target binding kinetics |
| Organisation | University of Bristol |
| Department | School of Chemistry |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | We contributed our enhanced sampling simulation algorithms including TS-PPTIS. Our approach will be combined with Prof. Mulholland's QM/MM algorithms to accurately predict binding kinetics. |
| Collaborator Contribution | Prof. Mulholland's contributed his QMMM algorithms as well as Waterswap to the combined computational platform. |
| Impact | A combined computational platform to predict binding kinetics and model the transition state ensemble. |
| Start Year | 2015 |
| Description | Collaboration with Derick Rousseau |
| Organisation | Ryerson University |
| Country | Canada |
| Sector | Academic/University |
| PI Contribution | Coarse-grained molecular simulation of monoglyceride self-assembly at triglyceride-water and air-water interfaces. |
| Collaborator Contribution | Experimental studies on the molecular templating effect of monoglycerides on triglyceride crystallization at oil-water interfaces |
| Impact | A poster and oral presentation was given at Food Colloids 2016 held at Wageningen university the Netherlands. A manuscript has been submitted and is under review. |
| Start Year | 2016 |
| Description | Collaboration with Johnson and Johnson |
| Organisation | Johnson & Johnson |
| Department | Janssen-Cilag |
| Country | Global |
| Sector | Private |
| PI Contribution | We helped J & J implement a computational pipeline for cryptic binding pocket discovery and collaborated on looking for druggable cryptic binding pockets on targets such the IMPase. |
| Collaborator Contribution | Provided interesting drug targets and experimental data, including NMR fragment screening. |
| Impact | Found interesting cryptic pockets in IMPase |
| Start Year | 2020 |
| Description | Collaboration with Paul Clegg |
| Organisation | University of Edinburgh |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | This project was collaborative with UoE who provided experimental expertise to complement computer modelling at HWU. |
| Collaborator Contribution | Provided expertise in soft matter physics, atomic force microscopy, spectroscopy. |
| Impact | We have authored 5 papers (6th in preparation). These are listed under this award. |
| Start Year | 2016 |
| Description | Collaboration with Prof. Jose Maria Lluch's group |
| Organisation | Autonomous University of Barcelona (UAB) |
| Country | Spain |
| Sector | Academic/University |
| PI Contribution | We helped to carry out and analyse QM/MM MD simulations using umbrella sampling bias, and calculated the kinetics as well as the free energies of the catalytic reaction to obtain the Arrhenius prefactor. |
| Collaborator Contribution | Patricia Laura, a PhD student was awarded funding to visit my group and work in my lab. |
| Impact | Joint publication by Suardiaz et al, J. Chem. Theor. Comput. 2016, DOI: 10.1021/acs.jctc.5b01236. |
| Start Year | 2015 |
| Description | Collaboration with SANOFI and Evotec on the allosteric regulation of receptor Tyrosine kinases. |
| Organisation | Evotec |
| Country | Germany |
| Sector | Private |
| PI Contribution | In this successful partnership, we helped designing a new class of allosteric anticancer drugs by using our novel computational algorithms to sample rare events and predict binding kinetics. |
| Collaborator Contribution | The partners contributed to the success of the research by performing large scale ligand screening ad providing high resolution crystallographic structures and biophysical data on the ligand-target complex. |
| Impact | A novel allosteric inhibitor is in re-clinical development for cancer. |
| Start Year | 2015 |
| Description | Collaboration with SANOFI and Evotec on the allosteric regulation of receptor Tyrosine kinases. |
| Organisation | Sanofi |
| Department | Aventis |
| Country | France |
| Sector | Private |
| PI Contribution | In this successful partnership, we helped designing a new class of allosteric anticancer drugs by using our novel computational algorithms to sample rare events and predict binding kinetics. |
| Collaborator Contribution | The partners contributed to the success of the research by performing large scale ligand screening ad providing high resolution crystallographic structures and biophysical data on the ligand-target complex. |
| Impact | A novel allosteric inhibitor is in re-clinical development for cancer. |
| Start Year | 2015 |
| Description | Collaboration with the Nano-Optics to controlled Nano-Chemistry programme |
| Organisation | University of Cambridge |
| Department | Cavendish Laboratory |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Our team performs electronic structure calculations to validate and design experiments in our collaborator groups led by Profs. Oren Scherman and Jeremy Baumberg in Cambridge. |
| Collaborator Contribution | We have several joint publications already. |
| Impact | Chikkarady et al, Nature, 2016, DOI: 10.1038/nature17974 In collaboration with the nano-optics lab - led by Prof. Jeremy Baumberg. Del Barrio et al, J. Am. Chem. Soc., 2016, DOI: 10.1021/jacs.5b11642 Ryan et al, Angewandte, 2016, DOI: 10.1002/anie.201607693 McCune et al, Org. Biomol. Chem., 2017, DOI: 10.1039/c6ob02594c Synthetic chemistry and materials reseach on host-guest supramolecular chemistry - led by Prof. Oren Scherman. |
| Start Year | 2015 |
| Description | Collaboration with the Nano-Optics to controlled Nano-Chemistry programme |
| Organisation | University of Cambridge |
| Department | Department of Chemistry |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Our team performs electronic structure calculations to validate and design experiments in our collaborator groups led by Profs. Oren Scherman and Jeremy Baumberg in Cambridge. |
| Collaborator Contribution | We have several joint publications already. |
| Impact | Chikkarady et al, Nature, 2016, DOI: 10.1038/nature17974 In collaboration with the nano-optics lab - led by Prof. Jeremy Baumberg. Del Barrio et al, J. Am. Chem. Soc., 2016, DOI: 10.1021/jacs.5b11642 Ryan et al, Angewandte, 2016, DOI: 10.1002/anie.201607693 McCune et al, Org. Biomol. Chem., 2017, DOI: 10.1039/c6ob02594c Synthetic chemistry and materials reseach on host-guest supramolecular chemistry - led by Prof. Oren Scherman. |
| Start Year | 2015 |
| Description | Developing new computational approaches to inhibit "undruggable" targets. |
| Organisation | UCB Pharma |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | We shared with UCB early versions of a computational platform we are developing to target allosteric sites on otherwise "undruggable" targets, i.e. pharmaceutical targets that are difficult to target with traditional drug design approaches based on substrate competitive ligands. |
| Collaborator Contribution | UCB contributed to the project with high quality structural and biological data and is hiring a dedicated PDRA to work on the collaboration for 3 years. |
| Impact | The new tools have been used to design novel drugs. |
| Start Year | 2016 |
| Description | ERNEST - European Research Network on Signal Transduction (CA18133) / Member of ERNEST Management Committee and the organizer of the first ERNEST Conference |
| Organisation | European Cooperation in Science and Technology (COST) |
| Department | COST Action |
| Country | Belgium |
| Sector | Public |
| PI Contribution | We were honoured to host the inaugural meeting of the European Research Network on Signal Transduction (ERNEST) funded by COST (Cooperation in Science and Technology) Action at Queen's University Belfast on October 28-30, 2019. PI was a main organizer of the GPCR meeting in Belfast. 150 delegates from 31 countries have attended the meeting, which made our conference a truly international event. This meeting was entitled "GPCR Pharmacology: Activation, Signalling and Drug Design" and focused on recent advances in knowledge and technology in the field. PI has designed the scientific program of the conference and has taken care of sponsor and venue arrangements. PDRA has gave a oral presentation on this BBSRC research project. |
| Collaborator Contribution | ERNEST COST Network has provided funding to organize the event. |
| Impact | Scientific outcomes of the meeting included recent advancements in cryo-electron microscopy, which is currently revolutionizing the field; how artificial intelligence and big data could drive pharmacology; the development of a multi-dimensional map of GPCR signal transduction and an overview of the IUPHAR / BPS Guide to PHARMACOLOGY database. The meeting had great networking opportunities and cultural experiences. On the first evening, a Welcome Reception with Deputy Lord Mayor Councillor Peter McReynolds, took place at the Belfast City Hall. The welcoming lectures were given by Michael Livingstone, a local historian, and Dr Aidan Seeley from the British Pharmacological Society. On the second evening, the Conference Dinner with traditional Irish dancing and music took place at the Great Hall. The conference has got additional sponsors: Belfast City Hall, Visit Belfast, British Pharmacological Society, ACS Pharmacology and Translational Science, Boehringer Ingelheim, Sosei Heptares, Nanotemper Technologies and Crelux, WuXi AppTec Company. As a result of this meeting, PI is a contributor to the ERNEST signalling map group. |
| Start Year | 2019 |
| Description | Evotec AI |
| Organisation | Evotec (UK) Ltd |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | Studentship aimed at researching the use of MD in Artificial Intelligence. |
| Collaborator Contribution | None yet. |
| Impact | N/A yet. |
| Start Year | 2018 |
| Description | Immunocore |
| Organisation | Immunocore Ltd |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | Simulations of various T-cell receptor peptide-HLA complexes, including analysis and prediction of binding. |
| Collaborator Contribution | Providing structural and experimental data, discussing and interpreting results from simulations. |
| Impact | Several publications are accepted (Journal of Clinical Investigation), about to be submitted, or in progress. Immunocore supported an SWBio CASE studentship (candidate not selected for interview). Discussions for further/alternative support of (co-funded) studentships or postdocs have taken place. David Cole from Immunocore has given a seminar in Bristol. |
| Start Year | 2018 |
| Description | Industrial collaboration with EVOTEC |
| Organisation | Evotec |
| Country | Germany |
| Sector | Private |
| PI Contribution | We helped EVOTEC to rationalize the binding mode of a novel allosteric modulator of FGFR. By using our novel "SWISH" Hamiltonian Replica exchange algorithm, we predicted a previously unknown binding cavity in the D3 domain of FGFR3c, which was then validated by NMR spectroscopy. |
| Collaborator Contribution | Evotec provided a plethora of unpublished experimental data on the binding mode and on the biological effect of the new tool compound in cells. |
| Impact | The collaboration is multi-disciplinary involving Computational Chemistry, Chemical Biology, Structural Biology, Cellular Biology and Drug Discovery. A new manuscript is in preparation and will soon be submitted to a very prominent and high-impact journal. The PI (FLG) has been invited to a number of high-profile national international (ACS-meeting) conferences to discuss the results. |
| Start Year | 2016 |
| Description | MARISURF |
| Organisation | Marlow Foods |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | MARISURF is a 4.8Meuro H2020 project coordinated by HWU to identify, isolate and purify biosurfactants from marine bacteria. The production will then be scaled up to pilot scale and the surfactants tested by industrial end-users from various industry sectors including food, cosmetic and biomedical sectors. My research group is responsible for overall coordination of the project, and specifically for the screening of functional properties of the surfactants to ensure suitability in industrial applications. |
| Collaborator Contribution | Marlow Foods are a partner in MARISURF an EUH2020 project coordinated by HWU. They will test marine bacteria-derived surfactants in their Quorn food applications. |
| Impact | The collaboration is multi-disciplinary and involves the following scientific disciplines, Microbiology Chemistry Biochemistry Molecular Biology Process Engineering |
| Start Year | 2015 |
| Description | Organic synthesis of alternative gelator molecules |
| Organisation | Heriot-Watt University |
| Department | Department of Mathematics |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Shared information on olegelation. Invited collaborator to project meetings. Eventual joint publications. |
| Collaborator Contribution | The partner will synthesize a range of alternative olegelator molecules that are derivatives of gamma oryzanol that either have the ferullic acid side chain substituted for another group, or have a hydroxyl group substituted. The hydroxyl group is believed to be important in dimerization of the sterols prior to their subsequent self-association into tubules, and also stabilizes the tubules through cooperative H-bonding. The ferrulic acid group is believed to allow inter-tubule interaction (it sticks out from the surface of the tubule) via pi-pi stacking interactions, thus leading to gel formation. By creating and testing oleogelators where one or both of these groups has been substituted will allow us to understand the role they play in the self-association and gelation process. |
| Impact | Too early in project/collaboration. |
| Start Year | 2017 |
| Description | Participation of European Topology interdisciplinary Initiative (Eutopia) network |
| Organisation | European Cooperation in Science and Technology (COST) |
| Country | Belgium |
| Sector | Public |
| PI Contribution | Participation on the 2nd annual meeting |
| Collaborator Contribution | The network invited me to give a talk |
| Impact | I gave a talk to the 2nd annual meeting of the network It is a multidisciplinary network from mathematics to biology, physics and chemistry. |
| Start Year | 2019 |
| Description | Vertex - CFTR |
| Organisation | Vertex Pharmaceuticals |
| Country | United States |
| Sector | Private |
| PI Contribution | This is a studentship that will commence in 2019. |
| Collaborator Contribution | None yet., |
| Impact | N/A. |
| Start Year | 2019 |
| Description | collaboration with Dr.Chantal Valeriani |
| Organisation | Complutense University of Madrid |
| Country | Spain |
| Sector | Academic/University |
| PI Contribution | We have collaborated with Dr Valeriani and her team on the behaviour of different water models in simulations of aquaporins. We contributed expertise in water models and simulations of nanopores. This has resulted in a joint publication in J Chem Phys. |
| Collaborator Contribution | Dr. Valeriani's post doc Dr Miguel Angel Gonzalez visited Oxford for a few weeks and worked alongside Dr Lynch (the EPSRC postdoc on this project). We have continued the collaboration online and a paper has been published in J Chem Phys. |
| Impact | This has resulted in a joint publication in J Chem Phys. |
| Start Year | 2018 |
| Description | collaboration with Novartis |
| Organisation | Novartis |
| Department | Drug Discovery & Development |
| Country | United States |
| Sector | Private |
| PI Contribution | We have shared data and software/home-made code to derive kinetic rates from umbrella sampling simulations. We also developed methods to be used for calculating residence times frlom atomistic simulations. |
| Collaborator Contribution | Shared data with us of atomistic simulations for drug molecules crossing the membrane. |
| Impact | We have joint publications. |
| Start Year | 2018 |
| Description | collaboration with Walter Kolch |
| Organisation | University College Dublin |
| Country | Ireland |
| Sector | Academic/University |
| PI Contribution | Computational MD simulations to reveal structure and dynamics of RAF kinases. |
| Collaborator Contribution | Prof. Kolch's group carried out in vitro and in cell biochemical experiments to reveal RAF kinase activity and validate key mutations suggested by computational results. |
| Impact | Jambrina et al, Angewandte Chemie, 2016, DOI: 10.1002/anie.201509272 Sanchez-Sanz et al, PLOS Computational Biology, 2016, DOI: 10.1371/journal.pcbi.1005051 Interdisciplinary research with essential biochemical and biological experiments from the Kolch group (Systems Biology Ireland) and computational work from our group. |
| Start Year | 2012 |
| Title | Computational tool to predict allosteric sites in membrane proteins |
| Description | The jupyter notebook scripts to set up the mapping of allosteric sites in GPCRs used in the paper: Probe Confined Dynamic Mapping for GPCR Allosteric Site Prediction Ciancetta A., Gill A.K., Ding T., Karlov D.S., Chalhoub G., McCormick P.J. and Tikhonova I.G. ACS Central Science, 2021 in press https://doi.org/10.1021/acscentsci.1c00802 The automatic procedure of probe confined dynamic mapping is provided as jupyter notebooks (MIDAS_EC.ipynb, MIDAS_IC.ipynb, and MIDAS_LI.ipynb) available. The required input files are (i) pdb of a receptor (preoriented with OPM), membrane, and one copy of cosolvent/fragment structures and (ii) an input file containing the following information: a receptor, an orthosteric ligand (if applicable), cosolvent and membrane file names (1); an orthosteric ligand (if applicable), cosolvent, and lipid residue names (2); cosolvent/fragment molecular weight and desired water/probe m/m % (in the closed box) (3); and height of the water buffer region between the protein and the water/probe mixture box (4). |
| Type Of Technology | New/Improved Technique/Technology |
| Year Produced | 2021 |
| Open Source License? | Yes |
| Impact | The product has received press coverage and new research collaborations. https://www.qub.ac.uk/News/Allnews/Newcomputermodellingcouldboostdrugdiscovery.html |
| URL | https://github.com/irinat12/Probe-Confined-Dynamic-Mapping-Protocols-GPCRs_membrane_proteins |
| Title | FESetup |
| Description | FESetup FESetup is a tool to automate the setup of (relative) alchemical free energy simulations like thermodynamic integration (TI) and free energy perturbation (FEP) as well as post-processing methods like MM-PBSA and LIE. FESetup can also be used for general simulation setup ("equilibration") through an abstract MD engine. The latest releases are available from the project web page. |
| Type Of Technology | Software |
| Year Produced | 2017 |
| Impact | FESetup FESetup is a tool to automate the setup of (relative) alchemical free energy simulations like thermodynamic integration (TI) and free energy perturbation (FEP) as well as post-processing methods like MM-PBSA and LIE. FESetup can also be used for general simulation setup ("equilibration") through an abstract MD engine. The latest releases are available from the project web page. |
| Title | Grand - an OpenMM module for grand canonical Monte Carlo |
| Description | This software allows grand canonical Monte Carlo calculations to be performed in the OpenMM simulation environment |
| Type Of Technology | Software |
| Year Produced | 2020 |
| Open Source License? | Yes |
| Impact | None yet |
| Title | HECBioSim Web Portal |
| Description | The HECBioSim web portal provides a clean and simple way for us to interact with our community. It serves as a single place in which members of the bio-simulation community can get access to all of the things we offer; whether this be finding out about/applying for time on ARCHER, downloading our software tools, getting support with using HPC or our software, this web portal provides users with a single and consistent point of entry to what we have to offer. |
| Type Of Technology | Webtool/Application |
| Year Produced | 2016 |
| Impact | Based on usage patterns and user feedback, the HECBioSim pages were refreshed. More information was added to the ARCHER application guide and FAQs to assist new and non-traditional users of HPC traverse the jargon laden application process. The pages were simplified and redesigned to remain compatible with current technologies and trends in user expectations. Feedback provided by STFC impact managers was used to make the HECBioSim web portal more accessible to a wider audience. The biggest updates to this were related to cyber security, maintaining a feature rich website comes with its own set of risks. A security audit is performed regularly and this feeds directly into the code maintenance tasks to keep the portal secure. |
| URL | http://www.hecbiosim.ac.uk |
| Title | HECBioSim Web Portal |
| Description | The new web portal provides a clean and simple way for us to interact with our community. It serves as a single place in which members of the bio-simulation community can get access to all of the things we offer; whether this be finding out about/applying for time on ARCHER, downloading our software tools, getting support with using HPC or our software, this web portal provides users with a single and consistent point of entry to what we have to offer. Built into this portal are facilities fo |
| Type Of Technology | Webtool/Application |
| Year Produced | 2014 |
| Impact | The HECBioSim portal has been heavily utilised by a very broad spectrum of users. Since the website was installed in 2014 we have had just over 213,000 hits by 67,869 unique IP addresses. Users are making heavy use of the ARCHER application form, guidance material and the kAU calculator tool, suggesting that users are finding these tools helpful over the old word document by email application process. Other sections of the website seeing heavy use are the software download and the documentation |
| URL | http://www.hecbiosim.ac.uk |
| Title | HECBioSim kAU Calculator v1.0 |
| Description | The HECBioSim kAU calculator is a user friendly web application that provides a simple interface to the complex predictive scaling model derived from our benchmark studies of commonly used molecular dynamics codes on ARCHER. The basic premises of this tool are; To provide users of all abilities with real numbers of the notional costs of running molecular dynamics simulations on ARCHER with respect to information that is more familiar to the user such as number of atoms and simulation time etc. To provide a tool that the consortium can use to screen applications based on information given during the application process to assess the feasibility of a project achieving stated goals given the size of the resource request. This version of the software was the first public production release of the tool, it released with a smaller subset of the benchmarking data to start with (GROMACS and AMBER) so that the community could evaluate the accuracy of our model against their data. |
| Type Of Technology | Webtool/Application |
| Year Produced | 2015 |
| Impact | This tool has proved to be quite popular amongst the academic community, feedback from members of the community has been very positive for this tool with requests to expand to more codes being quite common. The tool has helped groups that do not have a traditional background in HPC to make sense of the often quite daunting application process for super computing time. Usage statistics from this tool suggest it has been utilised by 1,343 unique IP addresses globally and that users are likely to be making use of this tool for systems that are very similar to ARCHER. |
| URL | http://www.hecbiosim.ac.uk/applications/hectime-aucalculator |
| Title | HECBioSim kAU Calculator v1.1 |
| Description | The HECBioSim kAU calculator is a user friendly web application that provides a simple interface to the complex predictive scaling model derived from our benchmark studies of commonly used molecular dynamics codes on ARCHER. The basic premises of this tool are; To provide users of all abilities with real numbers of the notional costs of running molecular dynamics simulations on ARCHER with respect to information that is more familiar to the user such as number of atoms and simulation time etc. To provide a tool that the consortium can use to screen applications based on information given during the application process to assess the feasibility of a project achieving stated goals given the size of the resource request. Changes: This release focused on releasing the full data set (LAMMPS, NAMD and CHARMM). Cosmetic update to deal with browser changes (new edge browser). Security fixes. Small bug fixes. |
| Type Of Technology | Webtool/Application |
| Year Produced | 2015 |
| Impact | This tool has proved to be quite popular amongst the academic community, feedback from members of the community has been very positive for this tool with requests to expand to more codes being quite common. The tool has helped groups that do not have a traditional background in HPC to make sense of the often quite daunting application process for super computing time. Usage statistics from this tool suggest it has been utilised by 1,343 unique IP addresses globally and that users are likely to be making use of this tool for systems that are very similar to ARCHER. |
| URL | http://www.hecbiosim.ac.uk/applications/hectime-aucalculator |
| Title | HECBioSim kAU Calculator v1.2 |
| Description | The HECBioSim kAU calculator is a user friendly web application that provides a simple interface to the complex predictive scaling model derived from our benchmark studies of commonly used molecular dynamics codes on ARCHER. The basic premises of this tool are; To provide users of all abilities with real numbers of the notional costs of running molecular dynamics simulations on ARCHER with respect to information that is more familiar to the user such as number of atoms and simulation time etc. To provide a tool that the consortium can use to screen applications based on information given during the application process to assess the feasibility of a project achieving stated goals given the size of the resource request. |
| Type Of Technology | Webtool/Application |
| Year Produced | 2016 |
| Impact | This version release addressed problems that users of chrome and firefox browsers were having when trying to use the calculator. This version also patched a serious security vulnerability that would have allowed a malicious user to compromise the underlying server on which the HECBioSim portal is located. This tool has been heavily used by both users applying for time on ARCHER since its release, but also by the panel making the decisions on allocations. This tools has proved invaluable in getting better value out of the ARCHER time budget for the whole community. |
| URL | http://www.hecbiosim.ac.uk/applications/hectime-aucalculator |
| Title | Longbow 1.2.0 |
| Description | Longbow is a piece of software that acts as a job proxying tool for biomolecular simulations, Longbow reproduces the native look and feel of using popular molecular dynamics packages (AMBER, CHARMM, GROMACS, LAMMPS and NAMD), with the difference that when those packages are used through Longbow simulations can be run on High Performance Computing (HPC) resources such as ARCHER. Longbow handles jobs setup in terms of creating job submission scripts, automatically stages input files, launches and monitors jobs and stages back simulation results. The option is also there to persistently monitor and stage (realtime local syncing with remote simulation files) simulation files at a specified time interval. This is designed to have the jobs running on the HPC remote resource appear to the user as if the simulation has run on their local computer/cluster. Users do not have to concern themselves with writing submission files, nor do they have to worry about staging. Longbow provides a convenient interface for generating large ensembles of simulation jobs which in effect extends the packages it supports. |
| Type Of Technology | Software |
| Year Produced | 2016 |
| Open Source License? | Yes |
| Impact | Longbow has now been downloaded 1,266 times from the HECBioSim website and tens of thousands of times from the pypi directory (March 2017). It has a wide reaching user-base across the world, some of those users being at 24 UK institutions actively downloading new versions as they are released. This version was released to introduce new functionality in the form of restarts, this enabled users to be able to disconnect and reconnect thus eliminating the need to be always connected. Queue limits are now also automatically detected and Longbow can maintain its own local queues for jobs, allowing a much more powerful way to submit jobs to machines with extreme limitations. This release was really aimed at boosting the productivity gains realised by utilising Longbow. |
| URL | http://www.hecbiosim.ac.uk/longbow |
| Title | Longbow v1.0.0 |
| Description | Longbow is a piece of software that acts as a job proxying tool for biomolecular simulations, Longbow reproduces the native look and feel of using popular molecular dynamics packages (AMBER, CHARMM, GROMACS, LAMMPS and NAMD), with the difference that when those packages are used through Longbow simulations can be run on High Performance Computing (HPC) resources such as ARCHER. Longbow handles jobs setup in terms of creating job submission scripts, automatically stages input files, launches and monitors jobs and stages back simulation results. The option is also there to persistently monitor and stage (realtime local syncing with remote simulation files) simulation files at a specified time interval. This is designed to have the jobs running on the HPC remote resource appear to the user as if the simulation has run on their local computer/cluster. Users do not have to concern themselves with writing submission files, nor do they have to worry about staging. Longbow provides a convenient interface for generating large ensembles of simulation jobs which in effect extends the packages it supports. This version was the first public release of Longbow after an extended period of closed alpha and beta testing. |
| Type Of Technology | Software |
| Year Produced | 2015 |
| Open Source License? | Yes |
| Impact | Since the release of the first version of Longbow, there have been just over 400 verified unique downloads between the HECBioSim download repository and the Python PyPi index. The active user-base includes users from both academic (21 different institutions in the UK) and the industrial sector globally. Longbow has also been or is currently being incorporated into software pipelines of other groups/consortia, projects of notable progress include integrating with FLEX-EM a powerful tool developed by CCP-EM and FESetup developed by CCPBioSim. The Longbow project led to a collaboration with pharmaceutical company UCB into integration of Longbow into their workflow, this also led to a feasibility study into the construction of a similar tool for commercial cloud services such as Amazon EC2 or Microsoft Azure. |
| URL | http://www.hecbiosim.ac.uk/longbow |
| Title | Longbow v1.0.1 |
| Description | Longbow is a piece of software that acts as a job proxying tool for biomolecular simulations, Longbow reproduces the native look and feel of using popular molecular dynamics packages (AMBER, CHARMM, GROMACS, LAMMPS and NAMD), with the difference that when those packages are used through Longbow simulations can be run on High Performance Computing (HPC) resources such as ARCHER. Longbow handles jobs setup in terms of creating job submission scripts, automatically stages input files, launches and monitors jobs and stages back simulation results. The option is also there to persistently monitor and stage (realtime local syncing with remote simulation files) simulation files at a specified time interval. This is designed to have the jobs running on the HPC remote resource appear to the user as if the simulation has run on their local computer/cluster. Users do not have to concern themselves with writing submission files, nor do they have to worry about staging. Longbow provides a convenient interface for generating large ensembles of simulation jobs which in effect extends the packages it supports. Changes: 1. longbow commands now have a well defined format of: longbow [longbow arguments] executable [executableargs]. 2. The parameter hierarchy has changed such that now parameters provided on the Longbow command line will overrule the same parameters in configuration files. 3. The -stage longbow argument is no longer supported as Longbow will automatically detect additional input files. 4. The rsync --include and --exclude have been exposed so that users can mask out files they do not need. These are separated into upload and downloads by using the following parameters; upload-include, upload-exclude, download-include and download-exclude. Only the download variants are available to the user (upload variants are used internally within Longbow but developers can make use of them in the API). 5. For replicate jobs, the order in which Longbow will search for input files has changed such that it looks in the repX subdirectories before the current working directory. 6. The batch parameter has been renamed replicates. 7. The commandline parameter has been renamed executableargs. 8. The parameters replicates (formerly batch) and jobname can now be provided on the Longbow command line as longbow arguments. 9. jobname is an exception as it is the only parameter that cannot overrule the jobname provided in the job configuration file. 10. LongbowExamples is now downloaded to the current working directory rather than the home directory when downloaded using longbow -examples. Jobs now run on the remote resource in /remoteworkdir/jobnameXXXXX where XXXXX represents a random 5-digit number. This is to prevent jobs with the same jobname clashing on the remote resource. Bugs have been fixed such that jobs will run on remote resources that use the SGE_ARC2 scheduler. Four Gromacs executables are now supported: mdrun, mdrun_d, mdrun_mpi, mdrun_mpi_d The hosts configuration file and LongbowExamples will now be downloaded using curl for those who do not have wget. |
| Type Of Technology | Software |
| Year Produced | 2015 |
| Open Source License? | Yes |
| Impact | Since the release of the first version of Longbow, there have been just over 400 verified unique downloads between the HECBioSim download repository and the Python PyPi index. The active user-base includes users from both academic (21 different institutions in the UK) and the industrial sector globally. Longbow has also been or is currently being incorporated into software pipelines of other groups/consortia, projects of notable progress include integrating with FLEX-EM a powerful tool developed by CCP-EM and FESetup developed by CCPBioSim. The Longbow project led to a collaboration with pharmaceutical company UCB into integration of Longbow into their workflow, this also led to a feasibility study into the construction of a similar tool for commercial cloud services such as Amazon EC2 or Microsoft Azure. |
| URL | http://www.hecbiosim.ac.uk/longbow |
| Title | Longbow v1.1.0 |
| Description | Longbow is a piece of software that acts as a job proxying tool for biomolecular simulations, Longbow reproduces the native look and feel of using popular molecular dynamics packages (AMBER, CHARMM, GROMACS, LAMMPS and NAMD), with the difference that when those packages are used through Longbow simulations can be run on High Performance Computing (HPC) resources such as ARCHER. Longbow handles jobs setup in terms of creating job submission scripts, automatically stages input files, launches and monitors jobs and stages back simulation results. The option is also there to persistently monitor and stage (realtime local syncing with remote simulation files) simulation files at a specified time interval. This is designed to have the jobs running on the HPC remote resource appear to the user as if the simulation has run on their local computer/cluster. Users do not have to concern themselves with writing submission files, nor do they have to worry about staging. Longbow provides a convenient interface for generating large ensembles of simulation jobs which in effect extends the packages it supports. Changes: 1. Fix for overwritten rsync-includes (developers only). 2. Bad character length on PBS now has an error message to inform the user what went wrong. Job names longer than 15 chars would be rejected. 3. Jobs that failed in a multi job would bring down the whole lot due to a bad initialisation now fixed. 4. Command line Longbow is submitted with is now logged to the log file for debugging purposes. 5. Bug fix with a bad initialisation in job processing code. 6. New ini parsers that don't rely on python std lib parser, this means comments are no longer deleted. 7. The following methods; loadhosts(), loadjobs(), sortjobsconfigs(), sorthostsconfigs(), amendjobsconfigs() have been replaced with single method processconfigs() 8. Fix for critical failure when the remoteworkdir did not exist |
| Type Of Technology | Software |
| Year Produced | 2015 |
| Open Source License? | Yes |
| Impact | Since the release of the first version of Longbow, there have been just over 400 verified unique downloads between the HECBioSim download repository and the Python PyPi index. The active user-base includes users from both academic (21 different institutions in the UK) and the industrial sector globally. Longbow has also been or is currently being incorporated into software pipelines of other groups/consortia, projects of notable progress include integrating with FLEX-EM a powerful tool developed by CCP-EM and FESetup developed by CCPBioSim. The Longbow project led to a collaboration with pharmaceutical company UCB into integration of Longbow into their workflow, this also led to a feasibility study into the construction of a similar tool for commercial cloud services such as Amazon EC2 or Microsoft Azure. |
| URL | http://www.hecbiosim.ac.uk/longbow |
| Title | Longbow v1.1.1 |
| Description | Longbow is a piece of software that acts as a job proxying tool for biomolecular simulations, Longbow reproduces the native look and feel of using popular molecular dynamics packages (AMBER, CHARMM, GROMACS, LAMMPS and NAMD), with the difference that when those packages are used through Longbow simulations can be run on High Performance Computing (HPC) resources such as ARCHER. Longbow handles jobs setup in terms of creating job submission scripts, automatically stages input files, launches and monitors jobs and stages back simulation results. The option is also there to persistently monitor and stage (realtime local syncing with remote simulation files) simulation files at a specified time interval. This is designed to have the jobs running on the HPC remote resource appear to the user as if the simulation has run on their local computer/cluster. Users do not have to concern themselves with writing submission files, nor do they have to worry about staging. Longbow provides a convenient interface for generating large ensembles of simulation jobs which in effect extends the packages it supports. Changes: 1. Modifications to how Longbow accepts the help and version command line parameters, some people don't follow GNU standards and thus so that we can show them the help message/version we have allowed -v, -version, --version, -h, -help and --help 2. Longbow now creates missing repX directories if they are missing in cases where all input files are global. This would allow jobs that might use different random seeds on the same input files to be efficient on transfers. |
| Type Of Technology | Software |
| Year Produced | 2015 |
| Open Source License? | Yes |
| Impact | Since the release of the first version of Longbow, there have been just over 400 verified unique downloads between the HECBioSim download repository and the Python PyPi index. The active user-base includes users from both academic (21 different institutions in the UK) and the industrial sector globally. Longbow has also been or is currently being incorporated into software pipelines of other groups/consortia, projects of notable progress include integrating with FLEX-EM a powerful tool developed by CCP-EM and FESetup developed by CCPBioSim. The Longbow project led to a collaboration with pharmaceutical company UCB into integration of Longbow into their workflow, this also led to a feasibility study into the construction of a similar tool for commercial cloud services such as Amazon EC2 or Microsoft Azure. |
| URL | http://www.hecbiosim.ac.uk/longbow |
| Title | Longbow v1.1.3 |
| Description | Longbow is a piece of software that acts as a job proxying tool for biomolecular simulations, Longbow reproduces the native look and feel of using popular molecular dynamics packages (AMBER, CHARMM, GROMACS, LAMMPS and NAMD), with the difference that when those packages are used through Longbow simulations can be run on High Performance Computing (HPC) resources such as ARCHER. Longbow handles jobs setup in terms of creating job submission scripts, automatically stages input files, launches and monitors jobs and stages back simulation results. The option is also there to persistently monitor and stage (realtime local syncing with remote simulation files) simulation files at a specified time interval. This is designed to have the jobs running on the HPC remote resource appear to the user as if the simulation has run on their local computer/cluster. Users do not have to concern themselves with writing submission files, nor do they have to worry about staging. Longbow provides a convenient interface for generating large ensembles of simulation jobs which in effect extends the packages it supports. Changes: 1. Update to the supported command line arguments to support non and GNU standard options for help and version number. 2. Update to allow the creation of repX directories when they are missing (Stops gromacs etc from exiting with path not found error) 3. Fix for bugs in python 3, there were two issues, one a python name change and the second was due to garbled output coming from the linux shell environment. |
| Type Of Technology | Software |
| Year Produced | 2015 |
| Open Source License? | Yes |
| Impact | Since the release of the first version of Longbow, there have been just over 400 verified unique downloads between the HECBioSim download repository and the Python PyPi index. The active user-base includes users from both academic (21 different institutions in the UK) and the industrial sector globally. Longbow has also been or is currently being incorporated into software pipelines of other groups/consortia, projects of notable progress include integrating with FLEX-EM a powerful tool developed by CCP-EM and FESetup developed by CCPBioSim. The Longbow project led to a collaboration with pharmaceutical company UCB into integration of Longbow into their workflow, this also led to a feasibility study into the construction of a similar tool for commercial cloud services such as Amazon EC2 or Microsoft Azure. |
| URL | http://www.hecbiosim.ac.uk/longbow |
| Title | Longbow v1.1.4 |
| Description | Longbow is a piece of software that acts as a job proxying tool for biomolecular simulations, Longbow reproduces the native look and feel of using popular molecular dynamics packages (AMBER, CHARMM, GROMACS, LAMMPS and NAMD), with the difference that when those packages are used through Longbow simulations can be run on High Performance Computing (HPC) resources such as ARCHER. Longbow handles jobs setup in terms of creating job submission scripts, automatically stages input files, launches and monitors jobs and stages back simulation results. The option is also there to persistently monitor and stage (realtime local syncing with remote simulation files) simulation files at a specified time interval. This is designed to have the jobs running on the HPC remote resource appear to the user as if the simulation has run on their local computer/cluster. Users do not have to concern themselves with writing submission files, nor do they have to worry about staging. Longbow provides a convenient interface for generating large ensembles of simulation jobs which in effect extends the packages it supports. Changes: 1. Fix for issue #114 - The saveconfigs method would overwrite entries within the hosts config with potentially blank entries if it was triggered and parameters existed in such a state (perhaps via overrides). 2. Fix for issue #113 - There was a missing clause on one of the if statements that prevented parameters at the hosts level from overriding internal defaults. This has now been added in. |
| Type Of Technology | Software |
| Year Produced | 2015 |
| Open Source License? | Yes |
| Impact | Since the release of the first version of Longbow, there have been just over 400 verified unique downloads between the HECBioSim download repository and the Python PyPi index. The active user-base includes users from both academic (21 different institutions in the UK) and the industrial sector globally. Longbow has also been or is currently being incorporated into software pipelines of other groups/consortia, projects of notable progress include integrating with FLEX-EM a powerful tool developed by CCP-EM and FESetup developed by CCPBioSim. The Longbow project led to a collaboration with pharmaceutical company UCB into integration of Longbow into their workflow, this also led to a feasibility study into the construction of a similar tool for commercial cloud services such as Amazon EC2 or Microsoft Azure. |
| URL | http://www.hecbiosim.ac.uk/longbow |
| Title | Longbow v1.1.5 |
| Description | Longbow is a piece of software that acts as a job proxying tool for biomolecular simulations, Longbow reproduces the native look and feel of using popular molecular dynamics packages (AMBER, CHARMM, GROMACS, LAMMPS and NAMD), with the difference that when those packages are used through Longbow simulations can be run on High Performance Computing (HPC) resources such as ARCHER. Longbow handles jobs setup in terms of creating job submission scripts, automatically stages input files, launches and monitors jobs and stages back simulation results. The option is also there to persistently monitor and stage (realtime local syncing with remote simulation files) simulation files at a specified time interval. This is designed to have the jobs running on the HPC remote resource appear to the user as if the simulation has run on their local computer/cluster. Users do not have to concern themselves with writing submission files, nor do they have to worry about staging. Longbow provides a convenient interface for generating large ensembles of simulation jobs which in effect extends the packages it supports. Changes: Fix for issue #117 - Python 3 and pip bug: 1. Longbow would not install under python 3 using either pip or by running the setup script manually. This has now been fixed by using print statements of the format print("text"), this form will work in all versions of python. Fix for issue #116 - User reported annoyances: 1. Fix for user reported annoyance of installing the hosts.conf in secret, and also leaving the archive that is downloaded in $home. This has now been replaced with a warning during install, and also the file is created locally and not downloaded. 2. Removed padding from version numbers so v1.01.005 > v1.1.5 3. Changed the README.md from markdown format to reStructured text, so now the README is README.rst, this is to make Longbow more pip friendly whilst still being bitbucket and possibly github (in case in future we move). 4. setup.py modified to eliminate the python 3 issues, and also the long description is now the README.rst, this means that users will see something standard between the pip page and the bitbucket page, this will also tie in with new pages on the HECBioSim website which will push pip as the preferred way to install more prominently. 5. hosts.conf file has been removed from the development version since this is now created on install for new users using pip, this will be marked as deprecated on the website for a while so users on old versions can still get it. Documentation will need to be updated to reflect this change and provide the quickstart example that users can grab a copy of if they are doing a more manual install. However pip will be the encouraged way to install. Issue #115 - Parameters in input files: Parameters specified within the configuration files had to be specified in a very strict format (param = value), users that omitted the spaces would find that Longbow would crash. The code has now been fixed to use regular expression to read in and parse for the equals sign, this can now handle cases where users specify cases such as: param1 = value1 param2 =value2 param3= value3 param4=value4 Minor edits: Added python version to logging added longbow version to logging moved version to the top of the longbow file added the paper citation to the logging and readme |
| Type Of Technology | Software |
| Year Produced | 2016 |
| Open Source License? | Yes |
| Impact | Since the release of the first version of Longbow, there have been just over 400 verified unique downloads between the HECBioSim download repository and the Python PyPi index. The active user-base includes users from both academic (21 different institutions in the UK) and the industrial sector globally. Longbow has also been or is currently being incorporated into software pipelines of other groups/consortia, projects of notable progress include integrating with FLEX-EM a powerful tool developed by CCP-EM and FESetup developed by CCPBioSim. The Longbow project led to a collaboration with pharmaceutical company UCB into integration of Longbow into their workflow, this also led to a feasibility study into the construction of a similar tool for commercial cloud services such as Amazon EC2 or Microsoft Azure. |
| URL | http://www.hecbiosim.ac.uk/longbow |
| Title | Longbow v1.2.1 |
| Description | Longbow is a piece of software that acts as a job proxying tool for biomolecular simulations, Longbow reproduces the native look and feel of using popular molecular dynamics packages (AMBER, CHARMM, GROMACS, LAMMPS and NAMD), with the difference that when those packages are used through Longbow simulations can be run on High Performance Computing (HPC) resources such as ARCHER. Longbow handles jobs setup in terms of creating job submission scripts, automatically stages input files, launches and monitors jobs and stages back simulation results. The option is also there to persistently monitor and stage (realtime local syncing with remote simulation files) simulation files at a specified time interval. This is designed to have the jobs running on the HPC remote resource appear to the user as if the simulation has run on their local computer/cluster. Users do not have to concern themselves with writing submission files, nor do they have to worry about staging. Longbow provides a convenient interface for generating large ensembles of simulation jobs which in effect extends the packages it supports. |
| Type Of Technology | Software |
| Year Produced | 2016 |
| Open Source License? | Yes |
| Impact | Longbow has now been downloaded 1,266 times from the HECBioSim website and tens of thousands of times from the pypi directory (March 2017). It has a wide reaching user-base across the world, some of those users being at 24 UK institutions actively downloading new versions as they are released. This version was released to address complexities that were introduced in the previous release surrounding the creation of restart files. A new intuitive naming regimen was implemented based on user feedback. |
| URL | http://www.hecbiosim.ac.uk/longbow |
| Title | Longbow v1.3.0 |
| Description | Longbow is a piece of software that acts as a job proxying tool for biomolecular simulations, Longbow reproduces the native look and feel of using popular molecular dynamics packages (AMBER, CHARMM, GROMACS, LAMMPS and NAMD), with the difference that when those packages are used through Longbow simulations can be run on High Performance Computing (HPC) resources such as ARCHER. Longbow handles jobs setup in terms of creating job submission scripts, automatically stages input files, launches and monitors jobs and stages back simulation results. The option is also there to persistently monitor and stage (realtime local syncing with remote simulation files) simulation files at a specified time interval. This is designed to have the jobs running on the HPC remote resource appear to the user as if the simulation has run on their local computer/cluster. Users do not have to concern themselves with writing submission files, nor do they have to worry about staging. Longbow provides a convenient interface for generating large ensembles of simulation jobs which in effect extends the packages it supports. |
| Type Of Technology | Software |
| Year Produced | 2016 |
| Open Source License? | Yes |
| Impact | Longbow has now been downloaded 1,266 times from the HECBioSim website and tens of thousands of times from the pypi directory (March 2017). It has a wide reaching user-base across the world, some of those users being at 24 UK institutions actively downloading new versions as they are released. This release focused on bug fixes but there was also a new feature. User feedback showed that naming conventions for commonly used molecular dynamics packages were changing, this was added to Longbow for out of the box support. Bugs in the recovery feature were fixed and some bugs with automatic file staging were fixed. A new fire and forget mode was introduced, so users could use Longbow in launcher mode and not have to use the monitoring features, they can then use the recovery feature to get access to their files in an automated way. |
| URL | http://www.hecbiosim.ac.uk/longbow |
| Title | Longbow v1.3.1 |
| Description | Longbow is a piece of software that acts as a job proxying tool for biomolecular simulations, Longbow reproduces the native look and feel of using popular molecular dynamics packages (AMBER, CHARMM, GROMACS, LAMMPS and NAMD), with the difference that when those packages are used through Longbow simulations can be run on High Performance Computing (HPC) resources such as ARCHER. Longbow handles jobs setup in terms of creating job submission scripts, automatically stages input files, launches and monitors jobs and stages back simulation results. The option is also there to persistently monitor and stage (realtime local syncing with remote simulation files) simulation files at a specified time interval. This is designed to have the jobs running on the HPC remote resource appear to the user as if the simulation has run on their local computer/cluster. Users do not have to concern themselves with writing submission files, nor do they have to worry about staging. Longbow provides a convenient interface for generating large ensembles of simulation jobs which in effect extends the packages it supports. |
| Type Of Technology | Software |
| Year Produced | 2016 |
| Open Source License? | Yes |
| Impact | Longbow has now been downloaded 1,266 times from the HECBioSim website and tens of thousands of times from the pypi directory (March 2017). It has a wide reaching user-base across the world, some of those users being at 24 UK institutions actively downloading new versions as they are released. This was another dual release fixing bugs and introducing new features. User reported bugs on machines running SGE with GPUs have been fixed. A problem with premature exiting and an error with some configuration files were fixed. A new feature was implemented allowing pre-launch scripts to be called server-side enabling quite powerful workflows or analysis tools to be used. |
| URL | http://www.hecbiosim.ac.uk/longbow |
| Title | Longbow v1.3.2 |
| Description | Longbow is a piece of software that acts as a job proxying tool for biomolecular simulations, Longbow reproduces the native look and feel of using popular molecular dynamics packages (AMBER, CHARMM, GROMACS, LAMMPS and NAMD), with the difference that when those packages are used through Longbow simulations can be run on High Performance Computing (HPC) resources such as ARCHER. Longbow handles jobs setup in terms of creating job submission scripts, automatically stages input files, launches and monitors jobs and stages back simulation results. The option is also there to persistently monitor and stage (realtime local syncing with remote simulation files) simulation files at a specified time interval. This is designed to have the jobs running on the HPC remote resource appear to the user as if the simulation has run on their local computer/cluster. Users do not have to concern themselves with writing submission files, nor do they have to worry about staging. Longbow provides a convenient interface for generating large ensembles of simulation jobs which in effect extends the packages it supports. |
| Type Of Technology | Software |
| Year Produced | 2016 |
| Open Source License? | Yes |
| Impact | Longbow has now been downloaded 1,266 times from the HECBioSim website and tens of thousands of times from the pypi directory (March 2017). It has a wide reaching user-base across the world, some of those users being at 24 UK institutions actively downloading new versions as they are released. This was mainly a bug fix release to address a number of user reported problems. |
| URL | http://www.hecbiosim.ac.uk/longbow |
| Title | Longbow v1.4 |
| Description | Longbow is a piece of software that acts as a job proxying tool for biomolecular simulations, Longbow reproduces the native look and feel of using popular molecular dynamics packages (AMBER, CHARMM, GROMACS, LAMMPS and NAMD), with the difference that when those packages are used through Longbow simulations can be run on High Performance Computing (HPC) resources such as ARCHER. Longbow handles jobs setup in terms of creating job submission scripts, automatically stages input files, launches and monitors jobs and stages back simulation results. The option is also there to persistently monitor and stage (realtime local syncing with remote simulation files) simulation files at a specified time interval. This is designed to have the jobs running on the HPC remote resource appear to the user as if the simulation has run on their local computer/cluster. Users do not have to concern themselves with writing submission files, nor do they have to worry about staging. Longbow provides a convenient interface for generating large ensembles of simulation jobs which in effect extends the packages it supports. |
| Type Of Technology | Software |
| Year Produced | 2017 |
| Open Source License? | Yes |
| Impact | Longbow has now been downloaded 1,266 times from the HECBioSim website and tens of thousands of times from the pypi directory (March 2017). It has a wide reaching user-base across the world, some of those users being at 24 UK institutions actively downloading new versions as they are released. This version was a major new release which focused on addressing a number of architectural problems, this required major refactoring of the code base. In this release a move to continuous integration by making use of cloud services such as Travis (Testing), Landscape (Quality) and Coveralls (Coverage) was performed, this required writing of more than 600 unit tests based on the code refactors done on this version. The shift towards continuous integration should help to improve the quality of the software, help make development more collaborative, and also increase sustainability. Several new features were introduced and numerous bugs found during automated testing were fixed. |
| URL | http://www.hecbiosim.ac.uk/longbow |
| Title | Longbow v1.5 |
| Description | Longbow is a piece of software that acts as a job proxying tool for biomolecular simulations, Longbow reproduces the native look and feel of using popular molecular dynamics packages (AMBER, CHARMM, GROMACS, LAMMPS and NAMD), with the difference that when those packages are used through Longbow simulations can be run on High Performance Computing (HPC) resources such as ARCHER. Longbow handles jobs setup in terms of creating job submission scripts, automatically stages input files, launches and monitors jobs and stages back simulation results. The option is also there to persistently monitor and stage (realtime local syncing with remote simulation files) simulation files at a specified time interval. This is designed to have the jobs running on the HPC remote resource appear to the user as if the simulation has run on their local computer/cluster. Users do not have to concern themselves with writing submission files, nor do they have to worry about staging. Longbow provides a convenient interface for generating large ensembles of simulation jobs which in effect extends the packages it supports. |
| Type Of Technology | Software |
| Year Produced | 2017 |
| Open Source License? | Yes |
| Impact | Longbow has now been downloaded 1,523 times from the HECBioSim website and tens of thousands of times from the pypi directory (July 2017). It has a wide reaching user-base across the world, some of those users being at 26 UK institutions actively downloading new versions as they are released. This version was a major new release which focused on addressing a number of architectural problems, this required major refactoring of the code base. This version fixed a number of community reported bugs and added user requested new functionality. Support for the latest python 3 version was added and the API restructured to simplify uptake in other projects. |
| URL | https://github.com/HECBioSim/Longbow/releases/tag/v1.5.0 |
| Title | Longbow v1.5.0 |
| Description | Longbow is an automated simulation submission and monitoring tool. Longbow is designed to reproduce the look and feel of using software on the users local computer with the difference that the heavy lifting is done by a supercomputer. Longbow will automatically generate the necessary submit files and handle all initial file transfer, monitor jobs, transfer files at configurable intervals and perform final file transfer and cleanup. Longbow can be used to launch one-off jobs, generate ensembles of similar jobs or even run many different jobs over many different supercomputers. Out of the box, Longbow is currently supporting the PBS/Torque, LSF, SGE, Slurm, SoGE schedulers and ships with application plugins for commonly used bio-molecular simulation softwares AMBER, CHARMM, GROMACS, LAMMPS, NAMD. Longbow is however highly configurable and will function normally with generic software without plugins, however plugins can easily be made to extend Longbow to fully support applications and schedulers that do not ship out of the box. Longbow is also available to developers of applications which require support for automating job submission. Longbow is available as a convenient and light-weight python API that can be integrated in a number of different way. |
| Type Of Technology | Software |
| Year Produced | 2018 |
| Open Source License? | Yes |
| Impact | Longbow has been downloaded by 6,211 times world wide by researchers doing biomolecular simulation. Longbow simplifies the transfer, preparation and submission of simulations across a wide range of HPC architectures. Users at the beginner end of the spectrum can quickly be up and running on any HPC resource within minutes without having to learn much about the process of doing it. Power users can leverage the power of Longbow in generating huge arrays of simulations and have it fire and bring back results across multiple machines that they have access to. It is a tool mainly aimed at taking the pain out of HPC by automating the time consuming tedious tasks associated with doing it at scale. |
| URL | http://www.hecbiosim.ac.uk/longbow |
| Title | Longbow v1.5.1 |
| Description | Longbow is an automated simulation submission and monitoring tool. Longbow is designed to reproduce the look and feel of using software on the users local computer with the difference that the heavy lifting is done by a supercomputer. Longbow will automatically generate the necessary submit files and handle all initial file transfer, monitor jobs, transfer files at configurable intervals and perform final file transfer and cleanup. Longbow can be used to launch one-off jobs, generate ensembles of similar jobs or even run many different jobs over many different supercomputers. Out of the box, Longbow is currently supporting the PBS/Torque, LSF, SGE, Slurm, SoGE schedulers and ships with application plugins for commonly used bio-molecular simulation softwares AMBER, CHARMM, GROMACS, LAMMPS, NAMD. Longbow is however highly configurable and will function normally with generic software without plugins, however plugins can easily be made to extend Longbow to fully support applications and schedulers that do not ship out of the box. Longbow is also available to developers of applications which require support for automating job submission. Longbow is available as a convenient and light-weight python API that can be integrated in a number of different way. |
| Type Of Technology | Software |
| Year Produced | 2019 |
| Open Source License? | Yes |
| Impact | Longbow has been downloaded by 7,542 times world wide by researchers doing biomolecular simulation. Longbow simplifies the transfer, preparation and submission of simulations across a wide range of HPC architectures. Users at the beginner end of the spectrum can quickly be up and running on any HPC resource within minutes without having to learn much about the process of doing it. Power users can leverage the power of Longbow in generating huge arrays of simulations and have it fire and bring back results across multiple machines that they have access to. It is a tool mainly aimed at taking the pain out of HPC by automating the time consuming tedious tasks associated with doing it at scale. |
| URL | http://www.hecbiosim.ac.uk/longbow |
| Title | Longbow v1.5.2 |
| Description | Longbow is an automated simulation submission and monitoring tool. Longbow is designed to reproduce the look and feel of using software on the users local computer with the difference that the heavy lifting is done by a supercomputer. Longbow will automatically generate the necessary submit files and handle all initial file transfer, monitor jobs, transfer files at configurable intervals and perform final file transfer and cleanup. Longbow can be used to launch one-off jobs, generate ensembles of similar jobs or even run many different jobs over many different supercomputers. Out of the box, Longbow is currently supporting the PBS/Torque, LSF, SGE, Slurm, SoGE schedulers and ships with application plugins for commonly used bio-molecular simulation softwares AMBER, CHARMM, GROMACS, LAMMPS, NAMD. Longbow is however highly configurable and will function normally with generic software without plugins, however plugins can easily be made to extend Longbow to fully support applications and schedulers that do not ship out of the box. Longbow is also available to developers of applications which require support for automating job submission. Longbow is available as a convenient and light-weight python API that can be integrated in a number of different way. |
| Type Of Technology | Software |
| Year Produced | 2019 |
| Open Source License? | Yes |
| Impact | Longbow has been downloaded by 8,695 times world wide by researchers doing biomolecular simulation. Longbow simplifies the transfer, preparation and submission of simulations across a wide range of HPC architectures. Users at the beginner end of the spectrum can quickly be up and running on any HPC resource within minutes without having to learn much about the process of doing it. Power users can leverage the power of Longbow in generating huge arrays of simulations and have it fire and bring back results across multiple machines that they have access to. It is a tool mainly aimed at taking the pain out of HPC by automating the time consuming tedious tasks associated with doing it at scale. |
| URL | https://www.hecbiosim.ac.uk/downloads |
| Title | OpenMMSLICER |
| Description | scientific software for sequential monte carlo simulations in openmm |
| Type Of Technology | Software |
| Year Produced | 2022 |
| Impact | This software has been further developed for simulated tempering and is being used for new research projects |
| URL | https://github.com/openmmslicer/openmmslicer |
| Title | ProtoCaller |
| Description | Software to automate the setup of free energy calculations |
| Type Of Technology | Software |
| Year Produced | 2020 |
| Open Source License? | Yes |
| Impact | non yet |
| URL | https://protocaller.readthedocs.io/en/latest/index.html |
| Title | Software - Crossflow |
| Description | Crossflow is a Python framework for writing computational workflows for execution on distributed computing facilities. |
| Type Of Technology | Software |
| Year Produced | 2020 |
| Open Source License? | Yes |
| Impact | The software is currently being evaluated by UCB for use in their drug discovery activities |
| URL | http://bitbucket.org/claughton/crossflow.git |
| Title | WaterDock |
| Description | A software to predict the location of water molecules in proteins. |
| Type Of Technology | Software |
| Year Produced | 2016 |
| Open Source License? | Yes |
| Impact | N/A |
| URL | https://github.com/bigginlab/WaterDock-2.0 |
| Description | 6th Molecular Microbiology Meeting |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Other audiences |
| Results and Impact | I attended this conference and I gave a talk with the purpose of engaging with microbiologists on multidisciplinary exchange of knowledge |
| Year(s) Of Engagement Activity | 2019 |
| URL | https://conferences.ncl.ac.uk/molmicro2019/ |
| Description | Advanced technology to support research, innovation and economic growth in the UK |
| Form Of Engagement Activity | A formal working group, expert panel or dialogue |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Policymakers/politicians |
| Results and Impact | Reform hosted a policy roundtable on the opportunities for advanced technology in the UK in May 2019, with the kind support of Hewlett Packard Enterprise. The session was introduced by Chris Skidmore MP, then Minister of State for Universities, Science, Research and Innovation, and Professor Mark Parsons, Director at the Edinburgh Parallel Computing Centre. The Minister stressed the importance of international collaboration in R&D, reaffirming the UK's ambition to strengthen and enrich existing partnerships, as well as to develop new global partnerships - as outlined in the then recently announced International Research & Innovation Strategy. The discussion also focused on the opportunities the upcoming Comprehensive Spending Review would offer to the science, research and innovation sectors, and on the need to build a strong case for. investment in emerging technologies - including quantum technology, performance computing (HPC) and robotics. During this meeting it was highlighted that High-performance computing is considered a game-changing technology, which will be fundamental to the UK's ability to maintain its global competitiveness in the science, research and innovation sectors. |
| Year(s) Of Engagement Activity | 2019 |
| URL | https://reform.uk/research/advanced-technology-support-research-innovation-and-economic-growth-uk |
| Description | Alchemistry in Boston 2018 - Bluck and Biggin |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | A poster was presented on free energy calculations and received useful feedback. |
| Year(s) Of Engagement Activity | 2018 |
| Description | Astbury Conversation - Introduction to HECBioSim and Longbow vendor stall |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | HECBioSim had an exhibitor stand with access to information leaflets, a laptop with demonstration software and one of our software engineering and performance experts manning the stand. The audience was generally experimental and practical life sciences with an interest in simulation. We focused on what HECBioSim did and what resources they could apply for through us, what advice was available and how to access it. Longbow demonstrations were quite popular as this enabled non-experts in computation to run powerful simulations without them having to master another discipline. We had a large number of follow-up queries for information, and some of the individuals later attended our other training events. |
| Year(s) Of Engagement Activity | 2018 |
| URL | https://eps.leeds.ac.uk/chemistry/news/article/147/the-astbury-conversation-16-17-april-2018 |
| Description | Banff International Research Station for Mathematical Innovation and Discovery: "The Topology of Nucleic Acids" |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Other audiences |
| Results and Impact | Invited talk that has been made accessible online |
| Year(s) Of Engagement Activity | 2019 |
| URL | https://www.birs.ca/events/2019/5-day-workshops/19w5226 |
| Description | CCPBioSim Training Week - Day 2: Running and analysing MD simulations |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Postgraduate students |
| Results and Impact | As part of the second day of the CCPBioSim training week workshop, users new to molecular dynamics were given a hands on introduction to how to setup up basic simulations through to how to analyse the results. In the second session of this day, Longbow was introduced with the aim of demonstrating how to move from running a small number of simulations to farming out hundreds if not thousands of simulations in one go. Users were introduced to the concepts surrounding simulation automation before moving onto hands on demonstration of the technology. Afterwards discussions with a number of the delegates revealed that they found the tool very useful and were planning on utilising it within their research to increase productivity. When asked if they would spread the word to their colleagues, all said they intended to. |
| Year(s) Of Engagement Activity | 2016 |
| URL | http://www.ccpbiosim.ac.uk/training-week-day2 |
| Description | Conference paper at Physics in Food manufacturing event, Chipping Campden, January 2019. |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | Workshop organised by the Institute of Physics food group. Allowed networking with physicists/physical chemists with similar intersts in food science. |
| Year(s) Of Engagement Activity | 2019 |
| Description | Conference paper on Food Oleogels at EFFost conference November 2018 in Nantes France |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Discussion were held with industrial (and academic) scientists who were interested in the finding of the work.The computational approaches used were of particular interests to academics and this has fostered new interactions with potential academic collaborators. |
| Year(s) Of Engagement Activity | 2018 |
| Description | EUTOPIA-2: 2 nd meeting of the European Topology interdisciplinary Initiative |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Other audiences |
| Results and Impact | Invited talk and enroll at this EU-funded COST network |
| Year(s) Of Engagement Activity | 2019 |
| URL | https://eutopiaam2019.wordpress.com |
| Description | Exhibitor Stand at CCP5 & CCPBioSim multiscale meeting |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Postgraduate students |
| Results and Impact | HECBioSim had an exhibitor stand at the conference where we ran had information leaflets available about what HECBioSim is and does. We ran software demonstrations, in particular Longbow and Xbow. We also engaged with students on HPC and gave advice about performance and HPC. |
| Year(s) Of Engagement Activity | 2018 |
| URL | https://www.ccpbiosim.ac.uk/events/past-conferences/eventdetail/106/-/3rd-conference-on-multiscale-m... |
| Description | HECBioSim: tools to simplify running and analysing large-scale MD simulations on HPC resources |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Postgraduate students |
| Results and Impact | This workshop was to introduce members of the bio-simulation community to tools that simplify the process of running and analysing MD simulations on a large scale. Users were introduced to consortia developed tools (Longbow pyPcazip and pyPcazipgui), users attempted hands on demonstrations of how to use such software and how to introduce them into their own workflows. Users had access to the national super computing service ARCHER for the duration of this workshop, so they had hands on experience with such resources for the first time in some cases. This workshop provided users direct exposure to the developers of the tools, which helped to open dialogue between users and developers and bring more ideas for new features. |
| Year(s) Of Engagement Activity | 2015 |
| URL | http://www.ccpbiosim.ac.uk/hecbio-goinglarge |
| Description | Headstart program at the University of York |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Undergraduate students |
| Results and Impact | Lecture "Introduction to Biophysics" to A-level physics students within the Work Experience Week and Headstart programs |
| Year(s) Of Engagement Activity | 2019 |
| URL | https://www.york.ac.uk/physics/public-and-schools/events/headstart-2019/ |
| Description | Istanbul December 2018 |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | A talk on free energy. |
| Year(s) Of Engagement Activity | 2018 |
| Description | London Free Energy Meeting |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | I presented a talk on free energy calculations to specialised audience of practitioners including industry attendees. |
| Year(s) Of Engagement Activity | 2017 |
| Description | Markov modelling and free energy calculation workshop 2016 |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Postgraduate students |
| Results and Impact | About 50 participants attended the Markov modelling workshop we organised at King's College London, some of which were international scientists from India, Europe or the US. Several participants were from pharmaceutical companies, such as Novartis, GSK, and UCB Pharma. The workshop initiated further collaborations and research visits with both academic groups and pharma companies. |
| Year(s) Of Engagement Activity | 2016 |
| Description | Pint of Science |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Public/other audiences |
| Results and Impact | Outreach talk for general public about current research in genomes and how affects our lives. |
| Year(s) Of Engagement Activity | 2019 |
| URL | https://pintofscience.co.uk/ |
| Description | Pint of Science talk: Making movies of Bacterial membranes |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Public/other audiences |
| Results and Impact | I gave a talk in a pub to an audience consisting of members of the general public who had bought tickets to the event. The talk explained some of the science behind antimicrobial resistance followed by some details of my own work in terms of 'making movies' of the bacterial membranes so we can understand how they protect bacteria. I talked about how we have to understand the membranes in molecular detail if we are to design new drugs with the ability to permeate across these membranes. Audience members said they had a much better understanding of how they must not abuse antibiotics, after the talk. |
| Year(s) Of Engagement Activity | 2017 |
| URL | https://pintofscience.co.uk/event/architecture-with-atoms |
| Description | Queen's Computational Biology Club Symposium. Almudena Pino-Angeles |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Postgraduate students |
| Results and Impact | Poster: Tracing the allosteric binding pathways to the cell membrane-GPCR interface. Discussions with bioinformaticians and appreciation of the application of AI in GPCR research. |
| Year(s) Of Engagement Activity | 2019 |
| Description | Seminar at University of Leeds |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Other audiences |
| Results and Impact | Seminar on edible oleogels at the University of Leeds to academic staff and students |
| Year(s) Of Engagement Activity | 2017 |
| Description | Sweden Keynote Presentation |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | I gave a keynote presentation on drug design to a specialist audience. |
| Year(s) Of Engagement Activity | 2018 |
| Description | Talk give in Oxford to Shanghai Tech |
| Form Of Engagement Activity | Participation in an open day or visit at my research institution |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Policymakers/politicians |
| Results and Impact | A talk was given on free energy calculations as part of a discussion to investigate joint operations between the university and Shanghai Tech. |
| Year(s) Of Engagement Activity | 2018 |
| Description | Talk in Dundee |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Postgraduate students |
| Results and Impact | A talk to 50-60 scientists from the Dundee area that provoked some interesting ideas and discussion. |
| Year(s) Of Engagement Activity | 2017 |
| Description | UKQSAR Sept 2018 Meeting - Bromodomains and Drug design |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | A talk on drug design given. |
| Year(s) Of Engagement Activity | 2018 |
| Description | Vertex 2018 Talk |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Industry/Business |
| Results and Impact | An invited talk given to Vertex Pharmaceuticals. |
| Year(s) Of Engagement Activity | 2018 |
| Description | Yale iGluR Poster Presentation |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Postgraduate students |
| Results and Impact | Poster presentation to about 130 scientists in the field of glutamate research |
| Year(s) Of Engagement Activity | 2017 |