Molecular simulation methods in drug discovery: a prospective outlook

Over the last decades, molecular simulations have spread through the drug discovery arena. This trend is expected to continue in the foreseeable future thanks to increased performance and the positive impact they can exert on productivity. In this article we highlight three aspects of molecular modelling for which we expect significant improvements over the next 25 years. Increased computational resources, faster algorithms and novel methods to sample rare events will provide a better handle on target flexibility and its relation with ligand binding. More accurate target druggability predictions will improve the success, but also broaden the scope of target-based drug discovery strategies. Finally, the use of higher levels of theory will increase the accuracy of protein–ligand binding affinity predictions, resulting in better hit identification success rates as well as more efficient lead optimization processes.

[1]  B. Maryanoff,et al.  2009 Edward E Smissman Award. Pharmaceutical "gold" from neurostabilizing agents: topiramate and successor molecules. , 2009, Journal of medicinal chemistry.

[2]  Traian Sulea,et al.  Solvated Interaction Energy (SIE) for Scoring Protein-Ligand Binding Affinities. 2. Benchmark in the CSAR-2010 Scoring Exercise , 2011, J. Chem. Inf. Model..

[3]  A. Laio,et al.  Flexible docking in solution using metadynamics. , 2005, Journal of the American Chemical Society.

[4]  Xevi Biarnés,et al.  Molecular motions in drug design: the coming age of the metadynamics method , 2011, J. Comput. Aided Mol. Des..

[5]  K. Merz,et al.  Large-scale validation of a quantum mechanics based scoring function: predicting the binding affinity and the binding mode of a diverse set of protein-ligand complexes. , 2005, Journal of medicinal chemistry.

[6]  Jonathan W. Essex,et al.  A review of protein-small molecule docking methods , 2002, J. Comput. Aided Mol. Des..

[7]  Robert P. Sheridan,et al.  Drug-like Density: A Method of Quantifying the "Bindability" of a Protein Target Based on a Very Large Set of Pockets and Drug-like Ligands from the Protein Data Bank , 2010, J. Chem. Inf. Model..

[8]  Nohad Gresh,et al.  Toward a Separate Reproduction of the Contributions to the Hartree-Fock and DFT Intermolecular Interaction Energies by Polarizable Molecular Mechanics with the SIBFA Potential. , 2007, Journal of chemical theory and computation.

[9]  Christophe Chipot,et al.  Free Energy Calculations , 2008 .

[10]  Jianmin Gao,et al.  Localized Thermodynamic Coupling between Hydrogen Bonding and Microenvironment Polarity Substantially Stabilizes Proteins , 2009, Nature Structural &Molecular Biology.

[11]  J. Andrew McCammon,et al.  MM-PBSA Captures Key Role of Intercalating Water Molecules at a Protein−Protein Interface , 2009, Journal of chemical theory and computation.

[12]  John P. Overington,et al.  How many drug targets are there? , 2006, Nature Reviews Drug Discovery.

[13]  V. Hornak,et al.  Modified replica exchange simulation methods for local structure refinement. , 2005, The journal of physical chemistry. B.

[14]  Serdar Durdagi,et al.  Binding of novel fullerene inhibitors to HIV-1 protease: insight through molecular dynamics and molecular mechanics Poisson–Boltzmann surface area calculations , 2011, J. Comput. Aided Mol. Des..

[15]  Claudio N. Cavasotto,et al.  Ligand docking and structure-based virtual screening in drug discovery. , 2007, Current topics in medicinal chemistry.

[16]  G. Klebe,et al.  Approaches to the description and prediction of the binding affinity of small-molecule ligands to macromolecular receptors. , 2002, Angewandte Chemie.

[17]  W. L. Jorgensen The Many Roles of Computation in Drug Discovery , 2004, Science.

[18]  William L Jorgensen,et al.  Efficient drug lead discovery and optimization. , 2009, Accounts of chemical research.

[19]  F. Javier Luque,et al.  Polarization effects in molecular interactions , 2011 .

[20]  M. V. Subbotin,et al.  A quantum mechanical polarizable force field for biomolecular interactions , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[21]  Klaus Schulten,et al.  Accelerating Molecular Modeling Applications with GPU Computing , 2009 .

[22]  J. Mongan,et al.  Accelerated molecular dynamics: a promising and efficient simulation method for biomolecules. , 2004, The Journal of chemical physics.

[23]  J Andrew McCammon,et al.  Optimized Radii for Poisson-Boltzmann Calculations with the AMBER Force Field. , 2005, Journal of chemical theory and computation.

[24]  C. E. Peishoff,et al.  A critical assessment of docking programs and scoring functions. , 2006, Journal of medicinal chemistry.

[25]  Claudio N. Cavasotto,et al.  Quantum mechanical binding free energy calculation for phosphopeptide inhibitors of the Lck SH2 domain , 2011, J. Comput. Chem..

[26]  Samuel Genheden,et al.  Comparison of the Efficiency of the LIE and MM/GBSA Methods to Calculate Ligand-Binding Energies. , 2011, Journal of chemical theory and computation.

[27]  Pavel Hobza,et al.  A reliable docking/scoring scheme based on the semiempirical quantum mechanical PM6-DH2 method accurately covering dispersion and H-bonding: HIV-1 protease with 22 ligands. , 2010, The journal of physical chemistry. B.

[28]  S. Lampel,et al.  The druggable genome: an update. , 2005, Drug discovery today.

[29]  V I Tarasov,et al.  Quantum mechanical polarizable force field (QMPFF3): refinement and validation of the dispersion interaction for aromatic carbon. , 2006, The Journal of chemical physics.

[30]  Michal Otyepka,et al.  Transferable scoring function based on semiempirical quantum mechanical PM6-DH2 method: CDK2 with 15 structurally diverse inhibitors , 2011, J. Comput. Aided Mol. Des..

[31]  Anthony J Stone,et al.  Accurate Induction Energies for Small Organic Molecules:  1. Theory. , 2008, Journal of chemical theory and computation.

[32]  Peter A. Kollman,et al.  FREE ENERGY CALCULATIONS : APPLICATIONS TO CHEMICAL AND BIOCHEMICAL PHENOMENA , 1993 .

[33]  Wilfred F. van Gunsteren,et al.  A GPU solvent–solvent interaction calculation accelerator for biomolecular simulations using the GROMOS software , 2010, J. Comput. Chem..

[34]  Dino Moras,et al.  Structural adaptability in the ligand-binding pocket of the ecdysone hormone receptor , 2003, Nature.

[35]  F. J. Luque,et al.  Protein flexibility and ligand recognition: challenges for molecular modeling. , 2011, Current topics in medicinal chemistry.

[36]  Ivan S Ufimtsev,et al.  Quantum Chemistry on Graphical Processing Units. 2. Direct Self-Consistent-Field Implementation. , 2009, Journal of chemical theory and computation.

[37]  X. Barril,et al.  Understanding and predicting druggability. A high-throughput method for detection of drug binding sites. , 2010, Journal of medicinal chemistry.

[38]  Paul D Lyne,et al.  Accurate prediction of the relative potencies of members of a series of kinase inhibitors using molecular docking and MM-GBSA scoring. , 2006, Journal of medicinal chemistry.

[39]  Jacob Kongsted,et al.  Ligand Affinities Estimated by Quantum Chemical Calculations. , 2010, Journal of chemical theory and computation.

[40]  Bruce E Maryanoff Inhibitors of serine proteases as potential therapeutic agents: the road from thrombin to tryptase to cathepsin G. , 2004, Journal of medicinal chemistry.

[41]  Traian Sulea,et al.  Rapid Prediction of Solvation Free Energy. 1. An Extensive Test of Linear Interaction Energy (LIE). , 2010, Journal of chemical theory and computation.

[42]  F. J. Luque,et al.  Shielded hydrogen bonds as structural determinants of binding kinetics: application in drug design. , 2011, Journal of the American Chemical Society.

[43]  Ivan S Ufimtsev,et al.  Quantum Chemistry on Graphical Processing Units. 3. Analytical Energy Gradients, Geometry Optimization, and First Principles Molecular Dynamics. , 2009, Journal of chemical theory and computation.

[44]  U. Ryde,et al.  Ligand affinities predicted with the MM/PBSA method: dependence on the simulation method and the force field. , 2006, Journal of Medicinal Chemistry.

[45]  Ivan S. Ufimtsev,et al.  Dynamic Precision for Electron Repulsion Integral Evaluation on Graphical Processing Units (GPUs). , 2011, Journal of chemical theory and computation.

[46]  Christophe Chipot,et al.  Comprar Free Energy Calculations · Theory and Applications in Chemistry and Biology | Chipot, Christophe | 9783540736172 | Springer , 2007 .

[47]  Kenneth M Merz,et al.  A Mixed QM/MM Scoring Function to Predict Protein-Ligand Binding Affinity. , 2010, Journal of chemical theory and computation.

[48]  Valentina Tozzini,et al.  Coarse-grained models for proteins. , 2005, Current opinion in structural biology.

[49]  Ivan S Ufimtsev,et al.  Quantum Chemistry on Graphical Processing Units. 1. Strategies for Two-Electron Integral Evaluation. , 2008, Journal of chemical theory and computation.

[50]  Michal Otyepka,et al.  Semiempirical quantum mechanical method PM6-DH2X describes the geometry and energetics of CK2-inhibitor complexes involving halogen bonds well, while the empirical potential fails. , 2011, The journal of physical chemistry. B.

[51]  R. Nussinov,et al.  Induced Fit, Conformational Selection and Independent Dynamic Segments: an Extended View of Binding Events Opinion , 2022 .

[52]  P. Hajduk,et al.  Druggability indices for protein targets derived from NMR-based screening data. , 2005, Journal of medicinal chemistry.

[53]  Hongxing Lei,et al.  Improved sampling methods for molecular simulation. , 2007, Current opinion in structural biology.

[54]  F. J. Luque,et al.  Pyrano[3,2-c]quinoline-6-chlorotacrine hybrids as a novel family of acetylcholinesterase- and beta-amyloid-directed anti-Alzheimer compounds. , 2009, Journal of medicinal chemistry.

[55]  Peter V Coveney,et al.  Rapid and accurate prediction of binding free energies for saquinavir-bound HIV-1 proteases. , 2008, Journal of the American Chemical Society.

[56]  Dariusz Plewczynski,et al.  Can we trust docking results? Evaluation of seven commonly used programs on PDBbind database , 2011, J. Comput. Chem..

[57]  Margaret E. Johnson,et al.  Current status of the AMOEBA polarizable force field. , 2010, The journal of physical chemistry. B.

[58]  Ricardo Macarron,et al.  Critical review of the role of HTS in drug discovery. , 2006, Drug discovery today.

[59]  B. Berne,et al.  Replica exchange with solute tempering: a method for sampling biological systems in explicit water. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[60]  Daniel R. Caffrey,et al.  Structure-based maximal affinity model predicts small-molecule druggability , 2007, Nature Biotechnology.

[61]  Steven W. Muchmore,et al.  Rapid Estimation of Relative Protein-Ligand Binding Affinities Using a High-Throughput Version of MM-PBSA , 2007, J. Chem. Inf. Model..

[62]  J. Gready,et al.  Combining docking and molecular dynamic simulations in drug design , 2006, Medicinal research reviews.

[63]  R. Cramer,et al.  Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins. , 1988, Journal of the American Chemical Society.

[64]  J Andrew McCammon,et al.  Studying enzyme binding specificity in acetylcholinesterase using a combined molecular dynamics and multiple docking approach. , 2002, Journal of the American Chemical Society.

[65]  A. Cavalli,et al.  Single-molecule pulling simulations can discern active from inactive enzyme inhibitors. , 2010, Journal of the American Chemical Society.

[66]  Johannes C. Hermann,et al.  A combined QM/MM approach to protein--ligand interactions: polarization effects of the HIV-1 protease on selected high affinity inhibitors. , 2004, Journal of medicinal chemistry.

[67]  Jacob Kongsted,et al.  An improved method to predict the entropy term with the MM/PBSA approach , 2009, J. Comput. Aided Mol. Des..

[68]  Ryo Maezono,et al.  Acceleration of a QM/MM‐QMC simulation using GPU , 2010, J. Comput. Chem..

[69]  C. Hunter,et al.  Quantifying intermolecular interactions: guidelines for the molecular recognition toolbox. , 2004, Angewandte Chemie.

[70]  A. Caflisch,et al.  Is quantum mechanics necessary for predicting binding free energy? , 2008, Journal of medicinal chemistry.

[71]  Christine Humblet,et al.  Investigation of MM-PBSA Rescoring of Docking Poses , 2008, J. Chem. Inf. Model..

[72]  Robert Kiss,et al.  Virtual Fragment Docking by Glide: a Validation Study on 190 Protein-Fragment Complexes , 2010, J. Chem. Inf. Model..

[73]  Akash Khandelwal,et al.  A combination of docking, QM/MM methods, and MD simulation for binding affinity estimation of metalloprotein ligands. , 2005, Journal of medicinal chemistry.