(1) A. Bhati, S. Wan, D. Wright, P. V. Coveney, “Rapid, accurate, precise and reliable relative free energy prediction using ensemble based thermodynamic integration”, Journal of Chemical Theory and Computation, 13 (1), 210–222 (2017), DOI: 10.1021/acs.jctc.6b00979

This is the seminal paper describing the TIES method and applying it to a set of 55 ligand transformations bound to 5 different protein targets. The results obtained are in very good agreement with experimental data (90% of calculations agree to within 1 kcal/mol), while the method is reproducible by construction. Statistical uncertainties of the order of 0.5 kcal/mol or less are achieved. A systematic account of how the uncertainty in the predictions may be estimated is presented.

(2) M. Bieniek, A. Bhati, S. Wan and P. V. Coveney, “TIES 20: Relative Binding Free Energy with a Flexible Superimposition Algorithm and Partial Ring Morphing”, J. Chem. Theory Comput., 17, 2, 1250–1265 (2021), DOI:10.1021/acs.jctc.0c01179

TIES20, an updated ligand matching protocol with flexible topology superimposition algorithm employed using an exhaustive joint-traversal for identifying the maximum common sub-structure between ligand pairs, has been described and validated using the same dataset as the original TIES study. The major advancement here is the allowance of partial ring matching that reduces the size of the alchemical region on average resulting in significant improvement in the precision of results. TIES 20 with the RESP charge system, using the new superimposition algorithm, reproduces the previous results with mean unsigned error of 0.75 kcal/mol. Further, using the AM1-BCC charge system improves agreement with the experimental data by slightly over 10% due to smaller mutation in this case.

(3) S. Wan, A. P. Bhati, S. J. Zasada, I. Wall, D. Green, P. Bamborough, and P. V. Coveney, “Rapid and Reliable Binding Affinity Prediction of Bromodomain Inhibitors: a Computational Study”, J. Chem. Theory Comput., 13 (2), 784–795 (2017), DOI: 10.1021/acs.jctc.6b00794

(4) S. Wan, A. Bhati, S. Skerratt, K. Omoto, V. Shanmugasundaram, S. Bagal, P. V. Coveney, “Evaluation and Characterization of Trk Kinase Inhibitors for the Treatment of Pain: Reliable Binding Affinity Predictions from Theory and Computation”, Journal of Chemical Information and Modelling, 57 (4), 897–909 (2017), DOI: 10.1021/acs.jcim.6b00780

(5) A. Bhati, S. Wan, Y. Hu, B. Sherborne, P. V. Coveney, “Uncertainty Quantification in Alchemical Free Energy Methods”, Journal of Chemical Theory and Computation, 14 (6), 2867–2880 (2018), DOI: 10.1021/acs.jctc.7b01143

(6) A. P. Bhati, S. Wan, and P. V. Coveney, “Ensemble-based replica exchange alchemical free energy methods: the effect of protein mutations on inhibitor binding”, J. Chem. Theory Comput., Available Online (2018), DOI: 10.1021/acs.jctc.8b01118

(7) S. Wan, G. Tresadern, L. Perez-Benito, H. van Vlijmen, P. V. Coveney, “Accuracy and Precision of Alchemical Relative Free Energy Predictions With and Without Replica-Exchange”, Advanced Theory and Simulations, 3, 1900195 (2020), DOI:10.1002/adts.201900195

(8) S. Wan, A. P. Bhati, S. J. Zasada and P. V. Coveney, “Rapid, accurate, precise and reproducible ligand–protein binding free energy prediction”, J R Soc Interface Focus 10, 2020007 (2020), DOI:10.1098/rsfs.2020.0007

(9) S. Wan, A. Potterton, F. S. Husseini, D. W. Wright, A. Heifetz, M. Malawski, A. Townsend-Nicholson and P. V. Coveney, “Hit-to-lead and lead optimization binding free energy calculations for G protein-coupled receptors”, J R Soc Interface Focus 10, 20190128 (2020), DOI:10.1098/rsfs.2019.0128

(10) S. Wan, D. Kumar, V. Ilyin, U. Al Homsi, G. Sher, A. Knuth, P. V. Coveney, “The effect of protein mutations on drug binding suggests ensuing personalised drug selection”, Sci. Rep., 11, 13452 (2021), DOI: 10.1038/s41598-021-92785-w