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Number of items: 31.
Article
Bhati, AP;
Wan, S;
Alfè, D;
Clyde, AR;
Bode, M;
Tan, L;
Titov, M;
... Coveney, PV; + view all
(2021)
Pandemic Drugs at Pandemic Speed: Infrastructure for Accelerating COVID-19 Drug Discovery with Hybrid Machine Learning- and Physics-based Simulations on High Performance Computers.
Interface Focus
, 11
(6)
, Article 20210018. 10.1098/rsfs.2021.0018.
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Bhati, AP;
Wan, S;
Coveney, PV;
(2018)
Ensemble-based replica exchange alchemical free energy methods: the effect of protein mutations on inhibitor binding.
Journal of Chemical Theory and Computation
10.1021/acs.jctc.8b01118.
(In press).
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Bhati, AP;
Wan, S;
Hu, Y;
Sherborne, B;
Coveney, PV;
(2018)
Uncertainty Quantification in Alchemical Free Energy Methods.
Journal of Chemical Theory and Computation
, 14
(6)
pp. 2867-2880.
10.1021/acs.jctc.7b01143.
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Bhati, AP;
Wan, S;
Wright, DW;
Coveney, PV;
(2017)
Rapid, Accurate, Precise, and Reliable Relative Free Energy Prediction Using Ensemble Based Thermodynamic Integration.
Journal of Chemical Theory and Computation
, 13
(1)
pp. 210-222.
10.1021/acs.jctc.6b00979.
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Bieniek, Mateusz K;
Wade, Alexander D;
Bhati, Agastya P;
Wan, Shunzhou;
Coveney, Peter V;
(2023)
TIES 2.0: A Dual-Topology Open Source Relative Binding Free Energy Builder with Web Portal.
Journal of Chemical Information and Modeling
10.1021/acs.jcim.2c01596.
(In press).
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Bieniek, MK;
Bhati, AP;
Wan, S;
Coveney, PV;
(2021)
TIES 20: Relative Binding Free Energy with a Flexible Superimposition Algorithm and Partial Ring Morphing.
Journal of Chemical Theory and Computation
10.1021/acs.jctc.0c01179.
(In press).
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Bunney, TD;
Wan, S;
Thiyagarajan, N;
Sutto, L;
Williams, SV;
Ashford, P;
Koss, H;
... Katan, M; + view all
(2015)
The Effect of Mutations on Drug Sensitivity and Kinase Activity of Fibroblast Growth Factor Receptors: A Combined Experimental and Theoretical Study.
EBioMedicine
, 2
(3)
194 - 204.
10.1016/j.ebiom.2015.02.009.
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Coveney, PV;
Wan, S;
(2016)
On the calculation of equilibrium thermodynamic properties from molecular dynamics.
Physical Chemistry Chemical Physics
, 18
(44)
pp. 30236-30240.
10.1039/c6cp02349e.
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Dakka, J;
Turilli, M;
Wright, DW;
Zasada, SJ;
Balasubramanian, V;
Wan, S;
Coveney, PV;
(2018)
High-throughput binding affinity calculations at extreme scales.
BMC Bioinformatics
, 19
(Suppl 18)
, Article 482. 10.1186/s12859-018-2506-6.
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Eccleston, RC;
Wan, S;
Dalchau, N;
Coveney, PV;
(2017)
The Role of Multiscale Protein Dynamics in Antigen Presentation and T Lymphocyte Recognition.
Frontiers in Immunology
, 8
, Article 797. 10.3389/fimmu.2017.00797.
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Edeling, Wouter;
Vassaux, Maxime;
Yang, Yiming;
Wan, Shunzhou;
Guillas, Serge;
Coveney, Peter V;
(2024)
Global ranking of the sensitivity of interaction potential contributions within classical molecular dynamics force fields.
npj Computational Materials
, 10
, Article 87. 10.1038/s41524-024-01272-z.
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Lee, H;
Merzky, A;
Tan, L;
Titov, M;
Turilli, M;
Alfe, D;
Bhati, A;
... Jha, S; + view all
(2021)
Scalable HPC & AI infrastructure for COVID-19 therapeutics.
PASC '21: Proceedings of the Platform for Advanced Scientific Computing Conference
, Article 2. 10.1145/3468267.3470573.
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Vassaux, M;
Wan, S;
Edeling, W;
Coveney, PV;
(2021)
Ensembles Are Required to Handle Aleatoric and Parametric Uncertainty in Molecular Dynamics Simulation.
Journal of Chemical Theory and Computation
10.1021/acs.jctc.1c00526.
(In press).
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Wade, Alexander D;
Bhati, Agastya P;
Wan, Shunzhou;
Coveney, Peter V;
(2022)
Alchemical Free Energy Estimators and Molecular Dynamics Engines: Accuracy, Precision, and Reproducibility.
Journal of Chemical Theory and Computation
10.1021/acs.jctc.2c00114.
(In press).
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Wan, S;
Bhati, AP;
Wade, AD;
Alfè, D;
Coveney, PV;
(2021)
Thermodynamic and structural insights into the repurposing of drugs that bind to SARS-CoV-2 main protease.
Molecular Systems Design & Engineering
10.1039/d1me00124h.
(In press).
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Wan, S;
Coveney, PV;
(2024)
Introduction to Computational Biomedicine.
Methods in Molecular Biology
, 2716
pp. 1-13.
10.1007/978-1-0716-3449-3_1.
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Wan, Shunzhou;
Bhati, Agastya P;
Coveney, Peter V;
(2023)
Comparison of Equilibrium and Nonequilibrium Approaches for Relative Binding Free Energy Predictions.
Journal of Chemical Theory and Computation
10.1021/acs.jctc.3c00842.
(In press).
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Wan, Shunzhou;
Bhati, Agastya P;
Wade, Alexander D;
Coveney, Peter V;
(2023)
Ensemble-Based Approaches Ensure Reliability and Reproducibility.
Journal of Chemical Information and Modeling
10.1021/acs.jcim.3c01654.
(In press).
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Wan, Shunzhou;
Bhati, Agastya P;
Wright, David W;
Wall, Ian D;
Graves, Alan P;
Green, Darren;
Coveney, Peter V;
(2022)
Ensemble Simulations and Experimental Free Energy Distributions: Evaluation and Characterization of Isoxazole Amides as SMYD3 Inhibitors.
Journal of Chemical Information and Modeling
10.1021/acs.jcim.2c00255.
(In press).
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Wan, S;
Bhati, AP;
Skerratt, S;
Omoto, K;
Shanmugasundaram, V;
Bagal, SK;
Coveney, PV;
(2017)
Evaluation and Characterization of Trk Kinase Inhibitors for the Treatment of Pain: Reliable Binding Affinity Predictions from Theory and Computation.
J. Chem. Inf. Model
, 57
(4)
pp. 897-909.
10.1021/acs.jcim.6b00780.
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Wan, S;
Bhati, AP;
Zasada, SJ;
Coveney, PV;
(2020)
Rapid, accurate, precise and reproducible ligand–protein binding free energy prediction.
Interface Focus
, 10
(6)
, Article 20200007. 10.1098/rsfs.2020.0007.
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Wan, S;
Bhati, AP;
Zasada, SJ;
Wall, I;
Green, D;
Bamborough, P;
Coveney, PV;
(2017)
Rapid and Reliable Binding Affinity Prediction of Bromodomain Inhibitors: A Computational Study.
Journal of Chemical Theory and Computation
, 13
(2)
pp. 784-795.
10.1021/acs.jctc.6b00794.
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Wan, S;
Knapp, B;
Wright, DW;
Deane, CM;
Coveney, PV;
(2015)
Rapid, Precise, and Reproducible Prediction of Peptide-MHC Binding Affinities from Molecular Dynamics That Correlate Well with Experiment.
Journal of Chemical Theory and Computation
, 11
(7)
pp. 3346-3356.
10.1021/acs.jctc.5b00179.
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Wan, S;
Kumar, D;
Ilyin, V;
Al Homsi, U;
Sher, G;
Knuth, A;
Coveney, PV;
(2021)
The effect of protein mutations on drug binding suggests ensuing personalised drug selection.
Scientific Reports
, 11
(1)
, Article 13452. 10.1038/s41598-021-92785-w.
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Wan, S;
Potterton, A;
Husseini, FS;
Wright, DW;
Heifetz, A;
Malawski, M;
Townsend-Nicholson, A;
(2020)
Hit-to-lead and lead optimization binding free energy calculations for G protein-coupled receptors.
Interface Focus
, 10
(6)
, Article 20190128. 10.1098/rsfs.2019.0128.
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Wan, S;
Sinclair, RC;
Coveney, PV;
(2021)
Uncertainty quantification in classical molecular dynamics.
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
, 379
(2197)
, Article 20200082. 10.1098/rsta.2020.0082.
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Wan, S;
Tresadern, G;
Pérez‐Benito, L;
Vlijmen, H;
Coveney, PV;
(2020)
Accuracy and Precision of Alchemical Relative Free Energy Predictions with and without Replica‐Exchange.
Advanced Theory and Simulations
, 3
(1)
, Article 1900195. 10.1002/adts.201900195.
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Wright, DW;
Husseini, F;
Wan, S;
Meyer, C;
van Vlijmen, H;
Tresadern, G;
Coveney, PV;
(2020)
Application of the ESMACS Binding Free Energy Protocol to a Multi‐Binding Site Lactate Dehydogenase A Ligand Dataset.
Advanced Theory and Simulations
, 3
(1)
, Article 1900194. 10.1002/adts.201900194.
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Wright, DW;
Wan, S;
Meyer, C;
van Vlijmen, H;
Tresadern, G;
Coveney, PV;
(2019)
Application of ESMACS binding free energy protocols to diverse datasets: Bromodomain-containing protein 4.
Scientific Reports
, 9
(1)
, Article 6017. 10.1038/s41598-019-41758-1.
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Proceedings paper
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Dakka, J;
Farkas-Pall, K;
Balasubramanian, V;
Turilli, M;
Wan, S;
Wright, DW;
Zasada, S;
... Jha, S; + view all
(2018)
Enabling trade-offs between accuracy and computational cost: Adaptive algorithms to reduce time to clinical insight.
In:
(Proceedings) 2018 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID).
(pp. pp. 572-577).
IEEE: Washington DC, USA.
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Saadi, AA;
Alfe, D;
Babuji, Y;
Bhati, A;
Blaiszik, B;
Brace, A;
Brettin, T;
... Yin, J; + view all
(2021)
IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads.
In:
Proceedings of ICPP 2021: 50th International Conference on Parallel Processing.
Association for Computing Machinery (ACM): New York, NY, USA.
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