Novel Enhanced Sampling Methods in Multiscale Modeling
Lead Research Organisation:
King's College London
Department Name: Chemistry
Abstract
Computer-based technologies are becoming one of the most promising novel approaches due to continuously accelerated growth of both hardware processing power and software algorithm efficiency. One recent example includes machine learning algorithms that revolutionised data analysis in computer science, and lead to new computer games, visual recognition, and other applications that overtake human performance in many cases.
Here, we propose to perform atomistic molecular simulations using novel enhanced sampling algorithms. Most biologically important processes take place on significantly longer timescales than those accessible to current computer simulations. Therefore, to obtain meaningful and accurate results regarding the kinetics and conformational dynamics of complex molecular systems, we use algorithms that enhance the sampling using parallel calculations with different biases. Developing more optimal biasing algorithms will allow us to model faster and more accurately the key biological processes of interest, including ligand binding, protein conformations, etc.
Here we aim to use statistical algorithms inspired by machine learning to develop novel enhanced sampling methods for molecular simulations. Novel algorithms can be applied to a wide range of molecular modeling problems. We will focus on phosphate catalytic enzymes, and study key DNA processing enzymes to reveal the catalytic mechanism in these systems.
Due to the essential nature of phosphate catalytic enzymes in most biological processes, a large number of drugs in current clinical practice also target phosphate-processing enzymes treating a wide range of diseases. Examples include reverse transcriptase and integrase inhibitors used against HIV and hepatitis B, proton pump inhibitors used in gastric diseases, kinase, PARP and topoisomerase inhibitors used against a large number of cancers. Studying phosphate catalytic systems with modern molecular modeling methods will enable fundamental advances in our current knowledge of the molecular basis of life. It will also create opportunities for rational development of better drugs to fight diseases.
Here, we propose to perform atomistic molecular simulations using novel enhanced sampling algorithms. Most biologically important processes take place on significantly longer timescales than those accessible to current computer simulations. Therefore, to obtain meaningful and accurate results regarding the kinetics and conformational dynamics of complex molecular systems, we use algorithms that enhance the sampling using parallel calculations with different biases. Developing more optimal biasing algorithms will allow us to model faster and more accurately the key biological processes of interest, including ligand binding, protein conformations, etc.
Here we aim to use statistical algorithms inspired by machine learning to develop novel enhanced sampling methods for molecular simulations. Novel algorithms can be applied to a wide range of molecular modeling problems. We will focus on phosphate catalytic enzymes, and study key DNA processing enzymes to reveal the catalytic mechanism in these systems.
Due to the essential nature of phosphate catalytic enzymes in most biological processes, a large number of drugs in current clinical practice also target phosphate-processing enzymes treating a wide range of diseases. Examples include reverse transcriptase and integrase inhibitors used against HIV and hepatitis B, proton pump inhibitors used in gastric diseases, kinase, PARP and topoisomerase inhibitors used against a large number of cancers. Studying phosphate catalytic systems with modern molecular modeling methods will enable fundamental advances in our current knowledge of the molecular basis of life. It will also create opportunities for rational development of better drugs to fight diseases.
Planned Impact
Academia
Our results are shared via workshops, tutorials, conferences and seminars. Computational groups will be able to download our newly developed programs from my research group website (www.rostaresearch.com), or from CCPBioSim workshop/tutorial webpages (http://www.ccpbiosim.ac.uk/). Our experimental collaborators will benefit from the more accurate and efficient algorithms that we can subsequently apply to design novel ligands, mutants, and test experimental hypothesis. We will work closely with experimental and theoretical collaborator groups in the UK, and overseas.
Public Sector, Business, Industry
On long term, health-related public sectors will benefit from basic research on structure and mechanism of phosphate processing enzymes. Our methods can be used and may be inspirational to a large number of projects studying ligand binding kinetics, or the dynamics of phosphate-processing enzymes that are relevant to many diseases. Phosphate processing enzymes are validated targets of a large number of drugs used in current clinical practices treating a wide range of diseases. These include reverse transcriptase and integrase inhibitors used against HIV and hepatitis B, proton pump inhibitors used in gastric diseases, kinase and topoisomerase inhibitors used in chemotherapy to treat cancers.
Our basic research results are therefore also relevant to UK charities such as Cancer Research UK. In addition to drug design, insights related to controlling enzyme activity is also relevant for biotechnology industries, e.g., businesses developing industrial enzymes such as Novozymes.
General Public, Education
The general public, high school and university students will benefit from new basic research developments in general, by public lectures in the UK and world-wide (e.g., via STEM seminars, such as the one I presented in a London-area Girls' School), or by the Open Days at King's. My lab also hosted 10 high school students to date since 2013, who were introduced to on-going research in my lab via the In2Science and Nuffield Research Placement programs.
Our results are shared via workshops, tutorials, conferences and seminars. Computational groups will be able to download our newly developed programs from my research group website (www.rostaresearch.com), or from CCPBioSim workshop/tutorial webpages (http://www.ccpbiosim.ac.uk/). Our experimental collaborators will benefit from the more accurate and efficient algorithms that we can subsequently apply to design novel ligands, mutants, and test experimental hypothesis. We will work closely with experimental and theoretical collaborator groups in the UK, and overseas.
Public Sector, Business, Industry
On long term, health-related public sectors will benefit from basic research on structure and mechanism of phosphate processing enzymes. Our methods can be used and may be inspirational to a large number of projects studying ligand binding kinetics, or the dynamics of phosphate-processing enzymes that are relevant to many diseases. Phosphate processing enzymes are validated targets of a large number of drugs used in current clinical practices treating a wide range of diseases. These include reverse transcriptase and integrase inhibitors used against HIV and hepatitis B, proton pump inhibitors used in gastric diseases, kinase and topoisomerase inhibitors used in chemotherapy to treat cancers.
Our basic research results are therefore also relevant to UK charities such as Cancer Research UK. In addition to drug design, insights related to controlling enzyme activity is also relevant for biotechnology industries, e.g., businesses developing industrial enzymes such as Novozymes.
General Public, Education
The general public, high school and university students will benefit from new basic research developments in general, by public lectures in the UK and world-wide (e.g., via STEM seminars, such as the one I presented in a London-area Girls' School), or by the Open Days at King's. My lab also hosted 10 high school students to date since 2013, who were introduced to on-going research in my lab via the In2Science and Nuffield Research Placement programs.
Publications
Huggins D
(2018)
Biomolecular simulations: From dynamics and mechanisms to computational assays of biological activity
in WIREs Computational Molecular Science
Readman C
(2019)
Anomalously Large Spectral Shifts near the Quantum Tunnelling Limit in Plasmonic Rulers with Subatomic Resolution.
in Nano letters
Noé F
(2019)
Special Topic: Markov Models of Molecular Kinetics
Kells A
(2019)
Mean first passage times in variational coarse graining using Markov state models.
in The Journal of chemical physics
Faizi F
(2019)
Efficient Irreversible Monte Carlo samplers
Pereverzev A
(2019)
Gas-phase structures reflect the pain-relief potency of enkephalin peptides
in Physical Chemistry Chemical Physics
Olesinska M
(2019)
Modular supramolecular dimerization of optically tunable extended aryl viologens.
in Chemical science
Noé F
(2019)
Markov Models of Molecular Kinetics.
in The Journal of chemical physics
Wu G
(2019)
Cucurbit[8]uril-mediated pseudo[2,3]rotaxanes.
in Chemical communications (Cambridge, England)
Wu G
(2019)
Controlling the structure and photophysics of fluorophore dimers using multiple cucurbit[8]uril clampings.
in Chemical science
Cook NJ
(2020)
Structural basis of second-generation HIV integrase inhibitor action and viral resistance.
in Science (New York, N.Y.)
Faizi F
(2020)
Simulated tempering with irreversible Gibbs sampling techniques.
in The Journal of chemical physics
Fanelli R
(2020)
Organocatalytic Access to a cis-Cyclopentyl-?-amino Acid: An Intriguing Model of Selectivity and Formation of a Stable 10/12-Helix from the Corresponding ?/a-Peptide.
in Journal of the American Chemical Society
Berta D
(2020)
Cations in motion: QM/MM studies of the dynamic and electrostatic roles of H+ and Mg2+ ions in enzyme reactions.
in Current opinion in structural biology
Jenkins K
(2020)
Combining data integration and molecular dynamics for target identification in a-Synuclein-aggregating neurodegenerative diseases: Structural insights on Synaptojanin-1 (Synj1).
in Computational and structural biotechnology journal
Ojambati O
(2020)
Breaking the Selection Rules of Spin-Forbidden Molecular Absorption in Plasmonic Nanocavities
in ACS Photonics
Faizi F
(2020)
Efficient Irreversible Monte Carlo Samplers.
in Journal of chemical theory and computation
Wagner A
(2020)
Host-Guest Chemistry Meets Electrocatalysis: Cucurbit[6]uril on a Au Surface as a Hybrid System in CO2 Reduction.
in ACS catalysis
Faulkner M
(2020)
Molecular simulations unravel the molecular principles that mediate selective permeability of carboxysome shell protein.
in Scientific reports
Berta D
(2020)
Toward Understanding CB[7]-Based Supramolecular Diels-Alder Catalysis.
in Frontiers in chemistry
Kells A
(2020)
Correlation functions, mean first passage times, and the Kemeny constant.
in The Journal of chemical physics
Pereverzev AY
(2020)
Spectroscopic Evidence for Peptide-Bond-Selective Ultraviolet Photodissociation.
in The journal of physical chemistry letters
Sicard F
(2021)
Position-Dependent Diffusion from Biased Simulations and Markov State Model Analysis.
in Journal of chemical theory and computation
Dürr S
(2021)
The Role of Conserved Residues in the DEDDh Motif: the Proton-Transfer Mechanism of HIV-1 RNase H
in ACS Catalysis
Xomalis A
(2021)
Detecting mid-infrared light by molecular frequency upconversion in dual-wavelength nanoantennas.
in Science (New York, N.Y.)
Pan X
(2021)
A simplified charge projection scheme for long-range electrostatics in ab initio QM/MM calculations.
in The Journal of chemical physics
Berta D
(2021)
Modelling the active SARS-CoV-2 helicase complex as a basis for structure-based inhibitor design.
in Chemical science
Wright D
(2021)
Mechanistic study of an immobilized molecular electrocatalyst by in situ gap-plasmon-assisted spectro-electrochemistry
in Nature Catalysis
Griffiths J
(2021)
Resolving sub-angstrom ambient motion through reconstruction from vibrational spectra.
in Nature communications
Koczor-Benda Z
(2021)
Molecular Screening for Terahertz Detection with Machine-Learning-Based Methods
in Physical Review X
Badaoui M
(2022)
Combined Free-Energy Calculation and Machine Learning Methods for Understanding Ligand Unbinding Kinetics.
in Journal of chemical theory and computation
Lin Q
(2022)
Optical suppression of energy barriers in single molecule-metal binding.
in Science advances
Peng J
(2022)
In-Situ Spectro-Electrochemistry of Conductive Polymers Using Plasmonics to Reveal Doping Mechanisms.
in ACS nano
Koczor-Benda Z
(2022)
Molecular Vibration Explorer: an Online Database and Toolbox for Surface-Enhanced Frequency Conversion and Infrared and Raman Spectroscopy
in The Journal of Physical Chemistry A
Berta D
(2023)
Mechanism-Based Redesign of GAP to Activate Oncogenic Ras.
in Journal of the American Chemical Society
Koczor-Benda Z
(2023)
Direct Calculation of Electron Transfer Rates with the Binless Dynamic Histogram Analysis Method.
in The journal of physical chemistry letters
Buigues PJ
(2023)
Investigating the Unbinding of Muscarinic Antagonists from the Muscarinic 3 Receptor.
in Journal of chemical theory and computation
Koskin V
(2023)
Variational kinetic clustering of complex networks.
in The Journal of chemical physics
Related Projects
| Project Reference | Relationship | Related To | Start | End | Award Value |
|---|---|---|---|---|---|
| EP/R013012/1 | 30/09/2018 | 30/08/2020 | £819,960 | ||
| EP/R013012/2 | Transfer | EP/R013012/1 | 31/08/2020 | 31/12/2024 | £541,660 |
| Description | We advanced the field of enhanced sampling methods, focusing on improving the accuracy and efficiency of molecular dynamics simulations for complex biological systems. A key achievement is the development of novel algorithms that optimize bias based on system kinetics, particularly minimizing the mean first passage time (MFPT), a critical advancement over traditional methods that often neglect kinetic considerations. Furthermore, we developed and applied novel methodologies that incorporate machine learning in identifying key dynamical events and corresponding structural insights for biomedically relevant systems, such as the Ras GTPase, GPCR igand unbinding kinetics, etc. We demonstrated the practical impact by applications where extracting kinetic information from biased simulations is very important, enabling a deeper understanding of molecular dynamics and facilitating advancements in various scientific disciplines. |
| Exploitation Route | We developed tutorials and shared code that enables others to use the developed methodology. |
| Sectors | Pharmaceuticals and Medical Biotechnology |
| Title | Data Supporting "Resolving Sub-Angstrom Ambient Motion through Reconstructions from Vibrational Spectra" |
| Description | Experimental and computational data to support the associated manuscript. This includes Raman scattering spectra taken using a 633nm laser and described in detail in the manuscript. Also includes the results of Density Functional Theory Calculations as described in detail in the manuscript. All data provided as .txt and .csv with README.txt files to explain each file. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2022 |
| Provided To Others? | Yes |
| URL | https://www.repository.cam.ac.uk/handle/1810/336608 |
| Title | Mechanism-Based Redesign of GAP to Activate Oncogenic Ras |
| Description | Additional material for Berta et al. J. Am. Chem. Soc. 2023, 145, 37, 20302-20310 Paths: minimised structures corresponding to the the GTP hydrolysis mechanism. MD setup: equilibriated inputs for classical MD simulations for WT and mutant systems in CHARMM/NAMD format, set up for the charmm36m FF. NBO: outputs for Natrual Bonding Orbitals analysis carried out for TS and RS structures. GAP mutants: optimised TS and RS structures of the most promising designed GAP mutants. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2023 |
| Provided To Others? | Yes |
| URL | https://zenodo.org/record/8375282 |
| Title | Mechanism-Based Redesign of GAP to Activate Oncogenic Ras |
| Description | Additional material for Berta et al. J. Am. Chem. Soc. 2023, 145, 37, 20302-20310 Paths: minimised structures corresponding to the the GTP hydrolysis mechanism. MD setup: equilibriated inputs for classical MD simulations for WT and mutant systems in CHARMM/NAMD format, set up for the charmm36m FF. NBO: outputs for Natrual Bonding Orbitals analysis carried out for TS and RS structures. GAP mutants: optimised TS and RS structures of the most promising designed GAP mutants. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2023 |
| Provided To Others? | Yes |
| URL | https://zenodo.org/record/8375281 |
| Title | Raw Data supporting article: Host-guest Chemistry Meets Electrocatalysis: Cucurbit[6]uril on a Au Surface as Hybrid System in CO2 Reduction |
| Description | This is raw data for the publication "Host-guest Chemistry Meets Electrocatalysis: Cucurbit[6]uril on a Au Surface as Hybrid System in CO2 Reduction". It includes All raw data for figures contained in the manuscript under the following DOI: 10.1021/acscatal.9b04221 Types of data/experiments: Animations/Schematics, Infrared Transmission spectroscopy, Fluorescence spectroscopy, Density Functional Theory computations, Molecular Dynamics computations, Surface-enhanced infrared spectroscopy, electrocatalysis with in-line gas chromatography, nuclear magnetic resonance spectroscopy, Quartz-crystal microbalance with dissipation measurements, X-Ray Photoelectron Spectroscopy |
| Type Of Material | Database/Collection of data |
| Year Produced | 2019 |
| Provided To Others? | Yes |
| URL | https://www.repository.cam.ac.uk/handle/1810/299409 |
| Title | Research data supporting "Breaking the Selection Rules of Spin-Forbidden Molecular Absorption in Plasmonic Nanocavities" |
| Description | The experimental data were taken in the NanoPhotonics Group at the Cavendish Laboratory (University of Cambridge). The dataset is for the journal article," Breaking the Selection Rules of Spin-Forbidden Molecular Absorption in Plasmonic Nanocavities". The photoluminescent spectra were taken with an electron multiplying charge-coupled detected (EMCCD)(Andor iXon) and darkfield scattering spectra by OceanOptics spectrometer. For further description see the Supplementary description of the manuscript. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2020 |
| Provided To Others? | Yes |
| URL | https://www.repository.cam.ac.uk/handle/1810/309153 |
| Title | Research data supporting "Optical suppression of energy barriers in single molecule-metal binding" |
| Description | Figure 1B: SERS spectra from BPT NPoM every 100ms at 20µW, showing no picocavities at low power. Figure 2: (A) Time-series SERS spectra of BPT for 50 µW 633 nm laser irradiation, showing examples of the nanocavity, a picocavity, and a flare in time-series. (B) Time-series SERS spectra of MBN for 50 µW irradiation. (C) Time-series SERS spectra of MPy for 10 µW irradiation. (D-F) Example SERS spectra from the nanocavity, a picocavity, and a flare. (G-I) DFT-calculated Raman spectra before the scaling by a factor of 0.97 (.csv and .out), with the corresponding molecular structures (.out). Figure 3: (A) Raw formation times and (B) lifetimes of picocavities, for the example histograms (with bin size of 20 and 30 respectively) in log scale. (C) Formation rate of picocavities at room and cryogenic temperatures, with critical intensities. (D) Formation rate of flares, with critical intensities. (E) Critical laser intensity required for picocavity and flare formation (from C,D), and saturation decay rate of slow picocavities (from F), vs molecule-metal binding energy. (F) Decay rate of picocavities in log scale, split into two classes (observed as in B): fast (<10 s for BPT, <25 s for MBN, MPy) and slow lifetimes. (G) Decay rate of flares, with fast (<2 s) and slow lifetimes. Figure 4E: Simulated energy for picocavities when molecule tip-adatom separation decreases by light vs without molecule, showing reduced barrier height. Note y values start from Row 87. Figure 5: (A) Simulated dependence of energy barrier and picocavity formation rate vs laser power in Model 2 for BPT. (B,E) DFT calculated charge induced on the tip atom (here N for MPy) when the gold adatom field is treated as an optical dipole of strength p at distance z away. (C,F,I) Induced charge q mapped vs adatom position, with z and angle ? on planes perpendicular to the aromatic ring. (D) Extracted energy barriers for different molecules from data. (G) Induced charge q from DFT tracks tip atom polarizability. (H) Molecule-metal binding energy well depth, and critical laser intensity, required for picocavity and flare formation, vs induced charge q at the molecule tip atom. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2022 |
| Provided To Others? | Yes |
| URL | https://www.repository.cam.ac.uk/handle/1810/337544 |
| Title | Research data supporting ''Mechanistic study of an immobilised molecular electrocatalyst by in-situ gap plasmon assisted spectro-electrochemistry'' |
| Description | Data supporting the publication findings (data.zip) that can reproduce figures from the main text. In text file format: Dark field scattering spectra for phenyl diisocyanide (PDI) and Ni(tpyS)2 NPoMs. Potential-dependent SERS spectra of PDI molecule displaying isocyanide group shifts, and extracted peak positions from NPoM and roughened Au. Cyclic voltammetry for Ni(tpyS)2 in N2 and CO2 purged conditions and the corresponding SERS spectra and DFT calculated spectra. In (code.zip) we include: Python 3 files (.py) for earth mover's algorithm spectral matching and DFT calculated structures for Ni(tpyS)2 throughout the CO2 reduction cycle (.out and .log). HOMO and LUMO calculations for two structures are included as .cub files. Experimental spectra used for matching are included as .npy and .dat files. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2021 |
| Provided To Others? | Yes |
| URL | https://www.repository.cam.ac.uk/handle/1810/317122 |
| 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 |