Computational tools for enzyme engineering: bridging the gap between enzymologists and expert simulation
Lead Research Organisation:
University of Bristol
Department Name: Chemistry
Abstract
It is becoming increasingly popular to use the powerful principles present in nature to our advantage. A key example is the extraordinary ability of organisms to make molecules with high specificity (pure, potentially complex molecules are obtained) and efficiency (little energy is used). Nature uses enzymes, proteins that act as catalysts, to achieve this. These enzymes typically work under mild conditions. Enzymes are already used in industry to make molecules that we require in cost-efficient, comparatively green and sustainable processes. However, nature has not provided us with an enzyme to suit the production of every desired molecule; typically enzymes only catalyze specific chemical reactions with specific starting materials. But the process of evolution teaches us that enzymes may be malleable for engineering different properties. For example, making small changes (mutations) in specific amino acids (the building blocks of proteins) of enzymes can allow these enzymes to accept different substrates and thereby catalyze the formation of new, desired molecules. Even though it is possible to determine the positions of atoms in an enzyme with great detail (e.g. using X-ray crystallography), the full effects of making changes to amino acids are not evident. This limits researchers in assessing what the (beneficial or non-beneficial) effects of such mutations are. It is possible to predict these effects with sophisticated computer simulation methods, but performing the necessary simulations requires expert knowledge. The researchers that are involved in optimizing enzymes to obtain new catalysts for making desired molecules are therefore usually limited to guessing what the effect of mutations is based on static structures alone. To bridge the gap between such experimental researchers and those that are experts in computer simulation, we aim to make expert simulation methods available through an interface that is familiar to the experimental researchers. Our project will involve the development of simulation protocols that assess the effects of mutations, using state-of-the-art methods that include molecular dynamics simulations and quantum chemistry calculations. The protocols will be designed such that they can be run on standard computers and they will be made accessible through an easy and familiar interface for experimental researchers (without the need for in-depth training in computer simulation). In addition, the protocols will allow high-throughput screening of 100s of mutations on high-performance computer clusters. The end result will be that researchers not skilled in computer simulation can easily assess the potential influence of mutations using their own computers, and that high-throughput screening of enzyme variants can be performed computationally. This can potentially save a lot of time and resources in the process of adapting an enzyme for a desired reaction. In addition, collaboration between researchers with complementary skills will be encouraged. The tools developed will also be beneficial in related fields, for example in designing effective drugs and understanding inheritable diseases.
Technical Summary
To obtain efficient biocatalysts, re-design or 'de novo' design of enzymes is often needed. Computational methods are increasingly employed for this purpose, but general and efficient workflows to assess how mutations affect enzymes are not yet available and accessible to experimentalists. The aim of this project is therefore to provide computational tools to a) run state-of-the-art simulation to assess the influence of mutations by non-experts on standard computers and b) perform computational high-throughput screening of enzyme variants on HPC facilities. The tools will be geared towards enzyme (re)design, but will also be useful more generally for structural and synthetic biology, drug design and health research. The protocols will go significantly beyond what is currently accessible to experimentalists, by assessing effects on the structure, dynamics, electronic properties and catalytic efficiency of enzymes. To ensure a broad uptake of the tools, we will actively develop and engage with the user community.
The project will deliver three main outputs:
1) Computationally inexpensive protocols for use on standard computers and HPC facilities. The protocols will use state-of-the-art simulation techniques, in particular molecular dynamics simulation and quantum mechanical / molecular mechanical (QM/MM) calculations, and provide relevant analysis of the simulation data.
2) A core software program that links together simulation setup and driving of software for MM and QM calculations, to seamlessly run the protocols mentioned above. The program will be set up such that interfaces to different external software packages can be written easily. The software will be released under an open-source (GPL) licence.
3) User-friendly plugins to molecular visualization software popular with structural biologists. With the plugins, released as open-source (GPL licence), users can run the core software program and then display the results in the molecular viewer.
The project will deliver three main outputs:
1) Computationally inexpensive protocols for use on standard computers and HPC facilities. The protocols will use state-of-the-art simulation techniques, in particular molecular dynamics simulation and quantum mechanical / molecular mechanical (QM/MM) calculations, and provide relevant analysis of the simulation data.
2) A core software program that links together simulation setup and driving of software for MM and QM calculations, to seamlessly run the protocols mentioned above. The program will be set up such that interfaces to different external software packages can be written easily. The software will be released under an open-source (GPL) licence.
3) User-friendly plugins to molecular visualization software popular with structural biologists. With the plugins, released as open-source (GPL licence), users can run the core software program and then display the results in the molecular viewer.
Planned Impact
This project will lead to new, easy-to-use and intuitive software designed to suit experimental researchers with no or little expertise in computational modelling and simulation. The software will thus facilitate basic and applied biochemical research by helping experimental scientists better understand and predict the effect of mutations. The software, related protocols and demonstration cases are primarily aimed at those interested in (re)designing enzymes for use as biocatalysts; this is an area of research that is also actively being pursued in industry, due to its ability to enhance the cost-effectiveness and sustainability of synthesis of chemical compounds and production of biofuels, for example. The tools produced are therefore expected to be taken up in industry as well as academia.
In the short term, the proposed project will deliver tools to help increase understanding and successful engineering of enzymes. The same tools will similarly help related biochemical research, such as protein and drug design. Significant efforts will be made to introduce interested experimental researchers to the tools developed, and train them in their use. By giving researchers with primarily experimental expertise access to and explanation of expert simulation methods, the skill-sets of these researchers will be increased. Outreach to experimental researchers will also encourage further cross-disciplinary research and related transfer of knowledge and skills. In addition, the researcher responsible for software development will obtain valuable programming experience that will be useful in his future academic or non-academic career.
In the medium term, the protocols and software that will be developed as part of the project (especially those for computational high-throughput screening of enzyme variants) should significantly reduce the time and resources spent to optimize biocatalysts for particular reactions. This has direct economic and environmental benefits (biocatalysts can be brought to market sooner, with reduced use of chemicals and energy in the development process). Similarly, computational assessment of the effect of mutations may avoid spending on producing and testing protein variants or drug lead compounds that subsequently prove ineffective.
In the long term, the commercial availability of biocatalysts optimized with help of the developed tools can potentially have enormous economic and environmental benefits by allowing the sustainable production of desired molecules, including fine-chemicals, drugs and biofuels. Biocatalysts are already starting to transform our current chemical industry by improvements in the methods, cost-effectiveness, safety, health, and environmental impact of the processes involved, and these impacts will be extended by the availability of additional biocatalysts. In addition, the application of the tools to help with and speed up drug design, for example to develop anti-viral and antibiotic compounds active against species that are currently drug-resistant, has obvious significant benefits for health in addition to the economic benefits. Similarly, the tools should contribute in helping to fulfil the enormous potential of synthetic biology to deliver societal and economic benefits.
In the short term, the proposed project will deliver tools to help increase understanding and successful engineering of enzymes. The same tools will similarly help related biochemical research, such as protein and drug design. Significant efforts will be made to introduce interested experimental researchers to the tools developed, and train them in their use. By giving researchers with primarily experimental expertise access to and explanation of expert simulation methods, the skill-sets of these researchers will be increased. Outreach to experimental researchers will also encourage further cross-disciplinary research and related transfer of knowledge and skills. In addition, the researcher responsible for software development will obtain valuable programming experience that will be useful in his future academic or non-academic career.
In the medium term, the protocols and software that will be developed as part of the project (especially those for computational high-throughput screening of enzyme variants) should significantly reduce the time and resources spent to optimize biocatalysts for particular reactions. This has direct economic and environmental benefits (biocatalysts can be brought to market sooner, with reduced use of chemicals and energy in the development process). Similarly, computational assessment of the effect of mutations may avoid spending on producing and testing protein variants or drug lead compounds that subsequently prove ineffective.
In the long term, the commercial availability of biocatalysts optimized with help of the developed tools can potentially have enormous economic and environmental benefits by allowing the sustainable production of desired molecules, including fine-chemicals, drugs and biofuels. Biocatalysts are already starting to transform our current chemical industry by improvements in the methods, cost-effectiveness, safety, health, and environmental impact of the processes involved, and these impacts will be extended by the availability of additional biocatalysts. In addition, the application of the tools to help with and speed up drug design, for example to develop anti-viral and antibiotic compounds active against species that are currently drug-resistant, has obvious significant benefits for health in addition to the economic benefits. Similarly, the tools should contribute in helping to fulfil the enormous potential of synthetic biology to deliver societal and economic benefits.
Publications
Acevedo-Rocha C
(2018)
P450-Catalyzed Regio- and Diastereoselective Steroid Hydroxylation: Efficient Directed Evolution Enabled by Mutability Landscaping
in ACS Catalysis
Ainsley J
(2018)
Structural Insights from Molecular Dynamics Simulations of Tryptophan 7-Halogenase and Tryptophan 5-Halogenase.
in ACS omega
Ainsley J
(2018)
Combined Quantum Mechanics and Molecular Mechanics Studies of Enzymatic Reaction Mechanisms.
in Advances in protein chemistry and structural biology
Ali HS
(2019)
Entropy of Simulated Liquids Using Multiscale Cell Correlation.
in Entropy (Basel, Switzerland)
Althorpe SC
(2016)
Non-adiabatic reactions: general discussion.
in Faraday discussions
Amaro RE
(2020)
A Community Letter Regarding Sharing Biomolecular Simulation Data for COVID-19.
in Journal of chemical information and modeling
Amaro RE
(2020)
Biomolecular Simulations in the Time of COVID19, and After.
in Computing in science & engineering
Amaro RE
(2018)
Multiscale Methods in Drug Design Bridge Chemical and Biological Complexity in the Search for Cures.
in Nature reviews. Chemistry
Amos STA
(2021)
Membrane Interactions of a-Synuclein Revealed by Multiscale Molecular Dynamics Simulations, Markov State Models, and NMR.
in The journal of physical chemistry. B
Angulo G
(2016)
New methods: general discussion.
in Faraday discussions
| Description | We have developed computational tools to model enzymes (biological catalysts) and the reactions they catalyse. Enzymes make possible all chemical reactions required for the survival and reproduction of living systems. The remarkable power of enzymes to catalyse reactions rapidly, selectively and efficiently under mild conditions is exploited in biotechnology. We are, however, not yet taking full advantage of enzymes as biocatalysts, whereas more widespread application of biocatalysts in industry is desired. To enable the use of enzymes as biocatalysts for reactions of interest, modifications are often necessary; for example to improve efficiency or alter and broaden substrate specificity. Recent state-of-the-art examples of such modifications, or re-design, often employ a combination of knowledge-based site-specific engineering and directed evolution. De novo enzyme design, which can be used to obtain biocatalysts for non-natural chemical reactions, has emerged as a promising field in the past decade and typically uses a similar combined strategy. For both re-design and de novo design, computational methods are now increasingly playing a key role in the design strategies employed. Specifically, computational simulation methods can help to predict the influence of amino-acid mutations far beyond the static view of modelling a new side-chain into a crystal structure. Changes in the structure, electrostatics and dynamics of an enzyme that affect substrate binding and catalysis can be simulated. It is increasingly recognized that all these effects, including protein dynamics, must be considered to allow successful enzyme (re)design. Beyond the need for (computationally) assessing the effect of mutations in enzyme (re)design, the wider fields of protein and drug design also benefit from such assessment. In synthetic biology, mutations are routinely made with the aim to improve designed functions of proteins other than biocatalysis, such as protein-protein or protein-ligand complex formation. Mutations that occur in rapidly evolving systems such as viruses or bacteria are often a challenge for drug design. Computational simulation can be used to understand why certain mutations or enzyme variants cause antibiotic resistance. For the design of drugs that target such rapidly evolving systems, efficient computational prediction of the influence of mutations on drug interaction will be beneficial. Although computer simulations can, in principle, efficiently assess different effects of mutations on enzymes and other proteins (structural, dynamical and catalytic), setting up and performing such simulations currently requires significant knowledge of and experience with biomolecular simulation methods and a range of different programs. Each of these programs comes with its own requirements for installation, input preparation, usage and analysis of results. The application of combined quantum mechanics/molecular mechanics (QM/MM) methods to the study of biological systems is a thriving and growing area, with advances in computer hardware and software opening up exciting new avenues of research. The award of the 2013 Nobel Prize for Chemistry to Martin Karplus, Michael Levitt and Arieh Warshel, recognises the development of combined quantum mechanical / molecular mechanical (QM/MM) methods and the important role these methods can play in our understanding of enzyme-catalysed reactions. The Diels-Alder reaction, a [4 + 2] cycloaddition of a conjugated diene to a dienophile, is one of the most powerful reactions in synthetic chemistry. Biocatalysts capable of unlocking new and efficient Diels-Alder reactions would have major impact. Here we present a molecular-level description of the reaction mechanism of the spirotetronate cyclase AbyU, an enzyme shown here to be a bona fide natural Diels-Alderase. Using enzyme assays, X-ray crystal structures, and simulations of the reaction in the enzyme, we reveal how linear substrate chains are contorted within the AbyU active site to facilitate a transannular pericyclic reaction. This study provides compelling evidence for the existence of a natural enzyme evolved to catalyze a Diels-Alder reaction and shows how catalysis is achieved. Researchers from the School of Chemistry, and the University of Parma, Italy, have used molecular simulations to understand resistance to osimertinib - an anticancer drug used to treat types of lung cancer. Osimertinib binds tightly to a protein, epidermal growth factor receptor (EGFR), which is overexpressed in many tumours. EGFR is involved in a pathway that signals for cell proliferation, and so is a target for drugs. Blocking the action of EGFR (inhibiting it) can switch it off, and so is a good way to treat the disease. Osimertinib is an effective anticancer drug that works in this way. It is used to treat non-small-cell lung cancer (NSCLC), in cases where the cancer cells have a particular (T790M) mutant form of EGFR. It is a so-called 'third-generation' EGFR inhibitor, which was approved as a cancer treatment in 2017. Osimertinib is a covalent inhibitor: as such, it binds irreversibly to EGFR by forming a chemical bond with it. Although patients generally respond well to osimertinib, most acquire drug resistance within one year of treatment, so the drug stops working. Drug resistance arises because the EGFR protein mutates, so that the drug binds less tightly. One such mutation, called L718Q, was recently discovered in patients in the clinic by the Medical Oncology Unit of the University Hospital of Parma. In this drug resistant mutant, a single amino acid is changed. Unlike other drug resistant mutants, it was not at all clear how this change stops the drug from binding effectively, information potentially crucial in developing new drugs to overcome resistance. Now, a collaboration between medicinal and computational chemists and clinical oncologists has revealed exactly how subtle changes in the protein target cause drug resistance. Using a range of advanced molecular simulation techniques, scientists from the Universities of Bristol and Parma, Italy, showed that the structure of the mutant protein changes in a way that stops the drug reacting and binding to it. Professor Adrian Mulholland, said: "This work shows how molecular simulations can reveal mechanisms of drug resistance, which can be subtle and non-obvious. "In particular, here we've used combined quantum mechanics/molecular mechanics (QM/MM) methods, which allow us to study chemical reactions in proteins. "This is crucial in investigating covalent inhibitors, which react with their biological targets, and are the focus of growing interest in the pharmaceutical industry." His collaborators, Professor Alessio Lodola and Professor Marco Mor of the Drug Design and Discovery group at the University of Parma, added: "It was an exciting experience to work closely with clinical colleagues who identified the mutant, and to help analyse its effects. "Now the challenge is to exploit this discovery in the development of novel drugs targeting EGFR mutants for cancer treatment in future." This research is a collaboration between The Drug Design and Discovery group of the Department of Food and Drug at the University of Parma; the Medical Oncology Unit, University Hospital of Parma and the Centre for Computational Chemistry, in the School of Chemistry of the University of Bristol. Researchers at the University of Bristol are pioneering the use of virtual reality (VR) as a tool to design the next generation of drug treatments. The findings, published in the journal PLOS One describe how researchers used VR to understand how common medications work on a molecular level. Many drugs are small molecules, and discovering new drugs involves finding molecules that bind to biological targets like proteins. In the study, users were able to use VR to 'step inside' proteins and manipulate them, and the drugs binding to them, in atomic detail, using interactive molecular dynamics simulations in VR (iMD-VR). Using this iMD-VR approach, researchers 'docked' drug molecules into proteins and were able to predict accurately how the drugs bind. Among the systems studied were drugs for flu and HIV. Professor Adrian Mulholland, from the University of Bristol's Centre for Computational Chemistry, and co-lead of the work, said: "Many drugs work by binding to proteins and stopping them working. For example, by binding to a particular virus protein, a drug can stop the virus from reproducing. "To bind well, a small molecule drug needs to fit snugly in the protein. An important part of drug discovery is finding small molecules that bind tightly to specific proteins, and understanding what makes them bind tightly, which helps to design better drugs. "To design new therapies, researchers need to understand how drug molecules fit into their biological targets. To do this, we use VR to represent them as fully three-dimensional objects. Users can then fit a drug within the 'keyhole' of a protein binding site to discover how they fit together." In the study, users were set the task of binding drugs to protein targets such as influenza neuraminidase and HIV protease. Tests showed that users were able to predict correctly how the drugs bind to their protein targets. By pulling the drug into the protein, they could build structures that are very similar to the structures of the drug complexes found from experiments. Even non-experts were able to dock drugs into the proteins effectively. This shows that interactive VR can be used to predict accurately how new potential drugs bind to their targets. The study shows how VR can be used effectively in structure-based drug design, even by non-experts. It uses readily available VR equipment and an open source software framework, so can be applied by anyone. Professor Mulholland added: "An important aspect of the work is that the drugs, and their protein targets, are fully flexible: we model their structural changes and dynamics, and users can manipulate them interactively to find how drugs interact with their biological targets. This is a really exciting and powerful way to model drug binding. We have shown in this work that it gives accurate results. These tools will be useful in the design and development of new drugs." Dr David Glowacki, Royal Society Senior Research Fellow in Bristol's School of Chemistry and Department of Computer Science, said: "Our results show that it is possible to unbind and rebind drugs from protein targets on a simulation timescale significantly shorter than the timescale of similar events observed using non-interactive molecular dynamics engines. "It is also important to note that the full unbinding and rebinding events generated using iMD-VR were achieved by the users in less than five minutes of real time. "Where non-expert users had trace atoms showing them the correct pose, all participants were able to establish a docking pose which was close enough to the starting structure to be scientifically considered redocked. "Where no trace atoms were present, binding poses understandably had more variation, but users were still able to get within the same range of the accepted bound position for all three systems. These results were achieved within a single hour-long training session with each participant, demonstrating the usability of this VR framework." This research was supported by funding from EPSRC and the Royal Society. Further information Paper: 'Interactive molecular dynamics in virtual reality for accurate flexible protein-ligand docking' by H. Deeds, R. Walters, S. Hare, M. O'Connor, A. Mulholland and D. Glowacki in PLOS One Designing better enzymes: Insights from directed evolution Authors H Adrian Bunzel, JL Ross Anderson, Adrian J Mulholland Publication date 2021/4/1 Source Current Opinion in Structural Biology Volume 67 Pages 212-218 Publisher Elsevier Current Trends Description De novo enzymes can be created by computational design and directed evolution. Here, we review recent insights into the origins of catalytic power in evolved designer enzymes to pinpoint opportunities for next-generation designs: Evolution precisely organizes active sites, introduces catalytic H-bonding networks, invokes electrostatic catalysis, and creates dynamical networks embedding the active site in a reactive protein scaffold. Such insights foster our fundamental knowledge of enzyme catalysis and fuel the future design of tailor-made enzymes. |
| Exploitation Route | The computational tools developed will be useful for researchers in academia and industry working on enzymes, e.g. for biocatalysis. All software will be released using an open source, GPL license, and will be hosted on the github site. Final code will also be accessible via a Google Code repository, and made available through CCPForge (ccpforge.cse.rl.ac.uk). Google code and github are publicly accessible repositories, which can provide immediate, free access to the software while it is in the process of development. In addition, packaged releases of the software will be produced and hosted through CCPForge as well as data.bris (see above) to ensure its integrity, availability and longevity. Github and google code provide indefinite hosting and archiving of the data, together with versioning and automatic metadata generation. This will enable the software to be advertised to automatic software discovery services, linked to from third party sites and the code to be re-used by interested parties. To ensure further visibility to the user community, links to the core program and its plugins to visualization programs will be provided on the CCP-BioSim website (ccpbiosim.ac.uk) and further download links for the plugins will be placed on their respective websites. In addition, documentation and installation instructions for the PyMOL plugin will also be placed on its designated wiki site (http://pymolwiki.org/index.php/Category:Plugins). Detailed descriptions and the required input files for the developed simulation protocols (for all supported simulation software packages) will be made publicly available via a dedicated github site (https://github.com/marcvanderkamp/enzlig_tools) and (when finalised) through data.bris (Bristol's Research Data Repository). The latter allows free, secure and accessible storage (including unique Digital Object Identifiers (DOIs)) for reasonable size data sets; simulation protocols and input will require minimal storage ~1 GB. To make the protocols easily accessible, DOIs will be generated and links placed on the CCP-BioSim website (http://www.ccpbiosim.ac.uk). Designing better enzymes: Insights from directed evolution Authors H Adrian Bunzel, JL Ross Anderson, Adrian J Mulholland Publication date 2021/4/1 Source Current Opinion in Structural Biology Volume 67 Pages 212-218 Publisher Elsevier Current Trends Description De novo enzymes can be created by computational design and directed evolution. Here, we review recent insights into the origins of catalytic power in evolved designer enzymes to pinpoint opportunities for next-generation designs: Evolution precisely organizes active sites, introduces catalytic H-bonding networks, invokes electrostatic catalysis, and creates dynamical networks embedding the active site in a reactive protein scaffold. Such insights foster our fundamental knowledge of enzyme catalysis and fuel the future design of tailor-made enzymes. How enzymes - the biological proteins that act as catalysts and help complex reactions occur - are 'tuned' to work at a particular temperature is described in new research from groups in New Zealand and the UK, including the University of Bristol. Professor Vic Arcus (University of Waikato) and colleagues, including Bristol's Professor Adrian Mulholland and Dr Marc van der Kamp, showed that the heat capacity of enzymes changes during a reaction as the enzymes tighten up. Exactly how much the enzymes tighten up is the critical factor in determining the temperature at which they work best. These findings could provide a route to designing better biocatalysts for use in chemical reactions in industrial processes, such as the production of drugs. Enzymes have an optimum temperature at which they are most catalytically active. Above that temperature, they become less active. Previously, it was thought that this was because enzymes unfolded (lost their functional shape) at higher temperatures, but actually they typically become less active at higher temperatures even though they maintain their functional shape. So what makes them less active? And what is it that causes enzymes from different organisms to have different catalytic activities at the same temperature? Enzymes from organisms that live at normal temperatures are not very active at low temperatures, while cold-adapted enzymes are active in the cold - why, when they have very similar structures? The new research, published as a 'New Concept' in Biochemistry (and selected for the American Chemical Society (ACS) Editors' Choice), shows that a basic physical property - the heat capacity - explains and predicts the temperature dependence of enzymes. The heat capacity of a substance is the amount of heat required to raise its temperature by one degree. For enzymes, the heat capacity changes during the reaction and this change is 'tuned' to give the optimal temperature. Professor Mulholland said: "Our theory - macromolecular rate theory, (MMRT) - applies to all enzymes, and so will have a critical role in predicting metabolic activity as a function of temperature. "We also expect to see characteristics of MMRT at the level of cells, whole organisms and even ecosystems. This means that it is important in understanding and predicting the response of biological systems to temperature changes, for example, how ecosystems will respond to temperature changes associated with climate change." The theory also explains why enzymes are so big (the more 'difficult' the chemistry to catalyse, the bigger the enzyme). It also hints at why proteins were eventually preferred by evolution over nucleic acids as catalysts in biology: proteins offer much more ability to 'tune' dynamics and their response to chemical reactions. Paper 'On the Temperature Dependence of Enzyme-catalyzed Rates' by Vickery L. Arcus, Erica J. Prentice, Joanne K. Hobbs, Adrian J. Mulholland, Marc W. Van der Kamp, Christopher R. Pudney, Emily J. Parker and Louis A. Schipper in Biochemistry https://pubs.acs.org/doi/abs/10.1021/acs.biochem.5b01094 Researchers at the University of Bristol are pioneering the use of virtual reality (VR) as a tool to design the next generation of drug treatments. The findings, published in the journal PLOS One describe how researchers used VR to understand how common medications work on a molecular level. Many drugs are small molecules, and discovering new drugs involves finding molecules that bind to biological targets like proteins. In the study, users were able to use VR to 'step inside' proteins and manipulate them, and the drugs binding to them, in atomic detail, using interactive molecular dynamics simulations in VR (iMD-VR). Using this iMD-VR approach, researchers 'docked' drug molecules into proteins and were able to predict accurately how the drugs bind. Among the systems studied were drugs for flu and HIV. Professor Adrian Mulholland, from the University of Bristol's Centre for Computational Chemistry, and co-lead of the work, said: "Many drugs work by binding to proteins and stopping them working. For example, by binding to a particular virus protein, a drug can stop the virus from reproducing. "To bind well, a small molecule drug needs to fit snugly in the protein. An important part of drug discovery is finding small molecules that bind tightly to specific proteins, and understanding what makes them bind tightly, which helps to design better drugs. "To design new therapies, researchers need to understand how drug molecules fit into their biological targets. To do this, we use VR to represent them as fully three-dimensional objects. Users can then fit a drug within the 'keyhole' of a protein binding site to discover how they fit together." In the study, users were set the task of binding drugs to protein targets such as influenza neuraminidase and HIV protease. Tests showed that users were able to predict correctly how the drugs bind to their protein targets. By pulling the drug into the protein, they could build structures that are very similar to the structures of the drug complexes found from experiments. Even non-experts were able to dock drugs into the proteins effectively. This shows that interactive VR can be used to predict accurately how new potential drugs bind to their targets. The study shows how VR can be used effectively in structure-based drug design, even by non-experts. It uses readily available VR equipment and an open source software framework, so can be applied by anyone. Professor Mulholland added: "An important aspect of the work is that the drugs, and their protein targets, are fully flexible: we model their structural changes and dynamics, and users can manipulate them interactively to find how drugs interact with their biological targets. This is a really exciting and powerful way to model drug binding. We have shown in this work that it gives accurate results. These tools will be useful in the design and development of new drugs." Dr David Glowacki, Royal Society Senior Research Fellow in Bristol's School of Chemistry and Department of Computer Science, said: "Our results show that it is possible to unbind and rebind drugs from protein targets on a simulation timescale significantly shorter than the timescale of similar events observed using non-interactive molecular dynamics engines. "It is also important to note that the full unbinding and rebinding events generated using iMD-VR were achieved by the users in less than five minutes of real time. "Where non-expert users had trace atoms showing them the correct pose, all participants were able to establish a docking pose which was close enough to the starting structure to be scientifically considered redocked. "Where no trace atoms were present, binding poses understandably had more variation, but users were still able to get within the same range of the accepted bound position for all three systems. These results were achieved within a single hour-long training session with each participant, demonstrating the usability of this VR framework." This research was supported by funding from EPSRC and the Royal Society. Further information Paper: 'Interactive molecular dynamics in virtual reality for accurate flexible protein-ligand docking' by H. Deeds, R. Walters, S. Hare, M. O'Connor, A. Mulholland and D. Glowacki in PLOS One |
| Sectors | Chemicals,Digital/Communication/Information Technologies (including Software),Education,Healthcare,Manufacturing, including Industrial Biotechology,Pharmaceuticals and Medical Biotechnology |
| URL | https://sites.google.com/site/mulhollandresearchgroup/ |
| Description | The computational tools developed for enzyme simulations have been demonstrated to industrial researchers working in biocatalysis and pharmaceuticals, and via the Catalysis Hub. Carbapenems, 'last resort' antibiotics for many bacterial infections, can now be broken down by several class A ß-lactamases (i.e. carbapenemases). Here, carbapenemase activity is predicted through QM/MM dynamics simulations of acyl-enzyme deacylation, requiring only the 3D structure of the apo-enzyme. This may |
| First Year Of Impact | 2014 |
| Sector | Agriculture, Food and Drink,Chemicals,Digital/Communication/Information Technologies (including Software),Healthcare,Pharmaceuticals and Medical Biotechnology |
| Impact Types | Economic |
| 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 | Biocatalysis and Biotransformation: A 5th Theme for the National Catalysis Hub |
| Amount | £3,053,639 (GBP) |
| Funding ID | EP/M013219/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 01/2015 |
| End | 12/2019 |
| Description | Carbapenem Antibiotic Resistance in Enterobacteriaceae: Understanding Interactions of KPC Carbapenemases with Substrates and Inhibitors |
| Amount | £668,396 (GBP) |
| Funding ID | MR/T016035/1 |
| Organisation | Medical Research Council (MRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 01/2020 |
| End | 01/2023 |
| 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 | 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 | A Multiscale Workflow for Modelling Ligand Complexes of Zinc Metalloproteins |
| Description | Representative MD trajectories, topologies and input files for the protein:ligand complexes presented in the paper Yang et al. J Chem. Inf. Model. 2021. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2021 |
| Provided To Others? | Yes |
| Impact | Zinc metalloproteins are ubiquitous, with protein zinc centers of structural and functional importance, involved in interactions with ligands and substrates and often of pharmacological interest. Biomolecular simulations are increasingly prominent in investigations of protein structure, dynamics, ligand interactions, and catalysis, but zinc poses a particular challenge, in part because of its versatile, flexible coordination. A computational workflow generating reliable models of ligand complexes of biological zinc centers would find broad application. Here, we evaluate the ability of alternative treatments, using (nonbonded) molecular mechanics (MM) and quantum mechanics/molecular mechanics (QM/MM) at semiempirical (DFTB3) and density functional theory (DFT) levels of theory, to describe the zinc centers of ligand complexes of six metalloenzyme systems differing in coordination geometries, zinc stoichiometries (mono- and dinuclear), and the nature of interacting groups (specifically the presence of zinc-sulfur interactions). MM molecular dynamics (MD) simulations can overfavor octahedral geometries, introducing additional water molecules to the zinc coordination shell, but this can be rectified by subsequent semiempirical (DFTB3) QM/MM MD simulations. B3LYP/MM geometry optimization further improved the accuracy of the description of coordination distances, with the overall effectiveness of the approach depending upon factors, including the presence of zinc-sulfur interactions that are less well described by semiempirical methods. We describe a workflow comprising QM/MM MD using DFTB3 followed by QM/MM geometry optimization using DFT (e.g., B3LYP) that well describes our set of zinc metalloenzyme complexes and is likely to be suitable for creating accurate models of zinc protein complexes when structural information is more limited. |
| URL | https://data.bris.ac.uk/data/dataset/10p78zgsappbz226bzrdagabq9/ |
| 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/ |
| 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 |
| Title | CCP-BioSim software for biomolecular simulation |
| Description | BioSimSpace A new software framework to create an interoperability layer around the many software packages that are already embedded within the biosimulation community. BioSimSpace will enable rapid development of workflows between these software packages that can then be used in conjunction with existing workflow software such as Knime, Pipeline Pilot, ExTASY etc. This project is currently in an early phase of development, more information can be found here. 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. Other Software: ProtoMS - a complete protein Monte Carlo free energy simulation package. Sire - a complete python/C++ molecular simulation framework, particularly focussed around Monte Carlo, QM/MM and free energy methods. PCAZIP - a toolkit for compression and analysis of molecular dynamics trajectories. COCO - a tool to enrich an ensemble of structures, obtained e.g. from NMR. Handy Routines for Ptraj/Cpptraj - additional analysis methods for ptraj and cpptraj. |
| Type Of Technology | Software |
| Year Produced | 2016 |
| Open Source License? | Yes |
| Impact | BioSimSpace A new software framework to create an interoperability layer around the many software packages that are already embedded within the biosimulation community. BioSimSpace will enable rapid development of workflows between these software packages that can then be used in conjunction with existing workflow software such as Knime, Pipeline Pilot, ExTASY etc. This project is currently in an early phase of development, more information can be found here. 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. Other Software: ProtoMS - a complete protein Monte Carlo free energy simulation package. Sire - a complete python/C++ molecular simulation framework, particularly focussed around Monte Carlo, QM/MM and free energy methods. PCAZIP - a toolkit for compression and analysis of molecular dynamics trajectories. COCO - a tool to enrich an ensemble of structures, obtained e.g. from NMR. Handy Routines for Ptraj/Cpptraj - additional analysis methods for ptraj and cpptraj. |
| URL | http://www.ccpbiosim.ac.uk |
| Title | Enlighten |
| Description | Protocols and tools to run (automated) atomistic simulations of protein-ligand (e.g. enzyme-substrate) systems. There is further a plugin to the popular (open source) visualisation program PyMOL that can be used to access and run these protocols. Aimed at: - Experimental biochemists/enzymologists interested in gaining detailed insight into protein-ligand / enzyme-substrate complexes. - Biomolecular researchers that would like to perform simulations in a high(er)-throughput fashion, e.g. for testing and hypothesis generation |
| Type Of Technology | Software |
| Year Produced | 2016 |
| Open Source License? | Yes |
| Impact | Development of the software has allowed engaging with (experimental) enzymologists, e.g. through tutorial workshops on simulation of protein-ligand system for non-experts. Free tutorial workshops were held as follows: 6-6-2016 University of Bristol, Bristol, 40 participants (see also: www.ccpbiosim.ac.uk/training-week-day1 ) 23-2-2017 University of Manchester, Manchester, 25 participants (see also: http://www.ukcatalysishub.co.uk/catalysis-events-publication/atomistic_simulation_workshop) Feedback from the workshops was very positive. |
| URL | http://www.github.com/marcvanderkamp/enlighten |
| 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. |
| Description | Atomistic Simulation of Biocatalysts for Non-Experts |
| 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 | On February 23rd, a tutorial workshop was held in Manchester, sponsored by the UK catalysis Hub and CCPBiosim and aimed at non-experts to learn about atomistic simulation of biocatalysts. The day included general introduction, the Enlighten simulation protocols & tools, and a "simulation clinic". 25 participants from around the UK (including from industry), with very positive feedback - all having a better idea about atomistic simulation and how to apply it in their research. |
| Year(s) Of Engagement Activity | 2017 |
| URL | https://www.eventbrite.com/e/atomistic-simulation-of-biocatalysts-for-non-experts-tickets-3150736136... |
| Description | Enlighten: Tools for enzyme-ligand modelling |
| 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 | A tutorial and feedback session was held on June 6th covering Enlighten, protocols and tools for atomistic simulation of protein-ligand systems that I have developed (www.github.com/marcvanderkamp/enlighten), aimed at non-experts (experimentalists/protein crystallographers). 40 participants from around the UK attended (including from industry), with very positive feedback: all reporting increased understanding of simulation, many likely to use the tools etc. |
| Year(s) Of Engagement Activity | 2016 |
| URL | http://www.ccpbiosim.ac.uk/training-week-day1 |