The Maximal and Current Accuracy of Rigorous Protein-ligand Binding Free Energy Calculations

Overview

Journal Commun Chem

Publisher Springer Nature

Specialty Chemistry

Date 2023 Oct 14

PMID 37838760

Authors

Gregory A Ross

Chao Lu

Guido Scarabelli

Steven K Albanese

Evelyne Houang

Robert Abel

Edward D Harder

Lingle Wang

Affiliations

Soon will be listed here.

Abstract

Computational techniques can speed up the identification of hits and accelerate the development of candidate molecules for drug discovery. Among techniques for predicting relative binding affinities, the most consistently accurate is free energy perturbation (FEP), a class of rigorous physics-based methods. However, uncertainty remains about how accurate FEP is and can ever be. Here, we present what we believe to be the largest publicly available dataset of proteins and congeneric series of small molecules, and assess the accuracy of the leading FEP workflow. To ascertain the limit of achievable accuracy, we also survey the reproducibility of experimental relative affinity measurements. We find a wide variability in experimental accuracy and a correspondence between binding and functional assays. When careful preparation of protein and ligand structures is undertaken, FEP can achieve accuracy comparable to experimental reproducibility. Throughout, we highlight reliable protocols that can help maximize the accuracy of FEP in prospective studies.

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References

Jama M, Ahmed M, Jutla A, Wiethan C, Kumar J, Moon T . Discovery of allosteric SHP2 inhibitors through ensemble-based consensus molecular docking, endpoint and absolute binding free energy calculations. Comput Biol Med. 2022; 152:106442. DOI: 10.1016/j.compbiomed.2022.106442. View

Wang L, Friesner R, Berne B . Replica exchange with solute scaling: a more efficient version of replica exchange with solute tempering (REST2). J Phys Chem B. 2011; 115(30):9431-8. PMC: 3172817. DOI: 10.1021/jp204407d. View

Brown S, Muchmore S, Hajduk P . Healthy skepticism: assessing realistic model performance. Drug Discov Today. 2009; 14(7-8):420-7. DOI: 10.1016/j.drudis.2009.01.012. View

Abel R, Wang L, Harder E, Berne B, Friesner R . Advancing Drug Discovery through Enhanced Free Energy Calculations. Acc Chem Res. 2017; 50(7):1625-1632. DOI: 10.1021/acs.accounts.7b00083. View

Lin Z, Zou J, Liu S, Peng C, Li Z, Wan X . A Cloud Computing Platform for Scalable Relative and Absolute Binding Free Energy Predictions: New Opportunities and Challenges for Drug Discovery. J Chem Inf Model. 2021; 61(6):2720-2732. DOI: 10.1021/acs.jcim.0c01329. View

Cannon M, Papalia G, Navratilova I, Fisher R, Roberts L, Worthy K . Comparative analyses of a small molecule/enzyme interaction by multiple users of Biacore technology. Anal Biochem. 2004; 330(1):98-113. DOI: 10.1016/j.ab.2004.02.027. View

Dajnowicz S, Ghoreishi D, Modugula K, Damm W, Harder E, Abel R . Advancing Free-Energy Calculations of Metalloenzymes in Drug Discovery via Implementation of LFMM Potentials. J Chem Theory Comput. 2020; 16(11):6926-6937. DOI: 10.1021/acs.jctc.0c00615. View

Deflorian F, Perez-Benito L, Lenselink E, Congreve M, van Vlijmen H, Mason J . Accurate Prediction of GPCR Ligand Binding Affinity with Free Energy Perturbation. J Chem Inf Model. 2020; 60(11):5563-5579. DOI: 10.1021/acs.jcim.0c00449. View

Paketuryte V, Linkuviene V, Krainer G, Chen W, Matulis D . Repeatability, precision, and accuracy of the enthalpies and Gibbs energies of a protein-ligand binding reaction measured by isothermal titration calorimetry. Eur Biophys J. 2018; 48(2):139-152. DOI: 10.1007/s00249-018-1341-z. View

10.

Chen W, Cui D, Jerome S, Michino M, Lenselink E, Huggins D . Enhancing Hit Discovery in Virtual Screening through Absolute Protein-Ligand Binding Free-Energy Calculations. J Chem Inf Model. 2023; 63(10):3171-3185. DOI: 10.1021/acs.jcim.3c00013. View

11.

Ross G, Russell E, Deng Y, Lu C, Harder E, Abel R . Enhancing Water Sampling in Free Energy Calculations with Grand Canonical Monte Carlo. J Chem Theory Comput. 2020; 16(10):6061-6076. DOI: 10.1021/acs.jctc.0c00660. View

12.

Mey A, Allen B, Bruce Macdonald H, Chodera J, Hahn D, Kuhn M . Best Practices for Alchemical Free Energy Calculations [Article v1.0]. Living J Comput Mol Sci. 2021; 2(1). PMC: 8388617. DOI: 10.33011/livecoms.2.1.18378. View

13.

Wu D, Zheng X, Liu R, Li Z, Jiang Z, Zhou Q . Free energy perturbation (FEP)-guided scaffold hopping. Acta Pharm Sin B. 2022; 12(3):1351-1362. PMC: 9072250. DOI: 10.1016/j.apsb.2021.09.027. View

14.

Tonge P . Quantifying the Interactions between Biomolecules: Guidelines for Assay Design and Data Analysis. ACS Infect Dis. 2019; 5(6):796-808. PMC: 6570549. DOI: 10.1021/acsinfecdis.9b00012. View

15.

Cappel D, Jerome S, Hessler G, Matter H . Impact of Different Automated Binding Pose Generation Approaches on Relative Binding Free Energy Simulations. J Chem Inf Model. 2020; 60(3):1432-1444. DOI: 10.1021/acs.jcim.9b01118. View

16.

Koehler M, Bergeron P, Blackwood E, Bowman K, Clark K, Firestein R . Development of a Potent, Specific CDK8 Kinase Inhibitor Which Phenocopies CDK8/19 Knockout Cells. ACS Med Chem Lett. 2016; 7(3):223-8. PMC: 4789660. DOI: 10.1021/acsmedchemlett.5b00278. View

17.

Isik M, Rustenburg A, Rizzi A, Gunner M, Mobley D, Chodera J . Overview of the SAMPL6 pK challenge: evaluating small molecule microscopic and macroscopic pK predictions. J Comput Aided Mol Des. 2021; 35(2):131-166. PMC: 7904668. DOI: 10.1007/s10822-020-00362-6. View

18.

Raman E, Paul T, Hayes R, Brooks 3rd C . Automated, Accurate, and Scalable Relative Protein-Ligand Binding Free-Energy Calculations Using Lambda Dynamics. J Chem Theory Comput. 2020; 16(12):7895-7914. PMC: 7814773. DOI: 10.1021/acs.jctc.0c00830. View

19.

Lu C, Wu C, Ghoreishi D, Chen W, Wang L, Damm W . OPLS4: Improving Force Field Accuracy on Challenging Regimes of Chemical Space. J Chem Theory Comput. 2021; 17(7):4291-4300. DOI: 10.1021/acs.jctc.1c00302. View

20.

Bruce Macdonald H, Cave-Ayland C, Ross G, Essex J . Ligand Binding Free Energies with Adaptive Water Networks: Two-Dimensional Grand Canonical Alchemical Perturbations. J Chem Theory Comput. 2018; 14(12):6586-6597. PMC: 6293443. DOI: 10.1021/acs.jctc.8b00614. View