Molecular simulations for the evaluation of binding free energies in lead optimization

The ability to predict, through computer simulation, the free energy of binding between drug‐like ligands and their biological target(s) is one of the most difficult yet rewarding tasks in computer‐aided drug design (CADD) efforts. Successful and consistent predictions are likely to have a profound effect on the efficiency of hit discovery and lead optimization campaigns. However, the route to achieving this goal is paved with challenges resulting from the complexity of the binding process and from the ability to simulate it, given contemporary computational tools. In this review we present the challenges faced by binding free energy simulations within the context of lead optimization, survey the main tools currently in use for performing such calculations, and discuss their applications and performance based on selected examples. Our main conclusion is that despite great progress and numerous success cases, free energy simulations have yet to mature in order to become an integral component of the arsenal of tools available to practitioners in the field of lead optimization. Drug Dev Res 72: 36–44, 2011. © 2010 Wiley‐Liss, Inc.

[1]  William L Jorgensen,et al.  Optimization of diarylamines as non-nucleoside inhibitors of HIV-1 reverse transcriptase. , 2006, Bioorganic & medicinal chemistry letters.

[2]  Jonathan W. Essex,et al.  Prediction of protein–ligand binding affinity by free energy simulations: assumptions, pitfalls and expectations , 2010, J. Comput. Aided Mol. Des..

[3]  Johan Åqvist,et al.  Ligand binding affinity prediction by linear interaction energy methods , 1998, J. Comput. Aided Mol. Des..

[4]  William L. Jorgensen,et al.  Optimization of azoles as anti-human immunodeficiency virus agents guided by free-energy calculations. , 2008, Journal of the American Chemical Society.

[5]  P. Kollman,et al.  Continuum Solvent Studies of the Stability of DNA, RNA, and Phosphoramidate−DNA Helices , 1998 .

[6]  Chris Oostenbrink,et al.  Improved ligand-protein binding affinity predictions using multiple binding modes. , 2010, Biophysical journal.

[7]  B. Honig,et al.  A rapid finite difference algorithm, utilizing successive over‐relaxation to solve the Poisson–Boltzmann equation , 1991 .

[8]  K. Dill,et al.  Binding of small-molecule ligands to proteins: "what you see" is not always "what you get". , 2009, Structure.

[9]  William L Jorgensen,et al.  Optimization of pyrimidinyl- and triazinyl-amines as non-nucleoside inhibitors of HIV-1 reverse transcriptase. , 2006, Bioorganic & medicinal chemistry letters.

[10]  David A. Pearlman,et al.  Free energy derivatives: A new method for probing the convergence problem in free energy calculations , 1994, J. Comput. Chem..

[11]  W L Jorgensen,et al.  Rationale for the observed COX-2/COX-1 selectivity of celecoxib from Monte Carlo simulations. , 2001, Bioorganic & medicinal chemistry letters.

[12]  M. Jacobson,et al.  Molecular mechanics methods for predicting protein-ligand binding. , 2006, Physical chemistry chemical physics : PCCP.

[13]  Michael R Shirts,et al.  Parallelized-over-parts computation of absolute binding free energy with docking and molecular dynamics. , 2006, The Journal of chemical physics.

[14]  Jens Carlsson,et al.  Continuum solvation models in the linear interaction energy method. , 2006, The journal of physical chemistry. B.

[15]  J. Aqvist,et al.  A new method for predicting binding affinity in computer-aided drug design. , 1994, Protein engineering.

[16]  Wang,et al.  Replica Monte Carlo simulation of spin glasses. , 1986, Physical review letters.

[17]  B. Berne,et al.  Multiple "time step" Monte Carlo , 2002 .

[18]  Caterina Barillari,et al.  Classification of water molecules in protein binding sites. , 2007, Journal of the American Chemical Society.

[19]  P A Kollman,et al.  Molecular dynamics and continuum solvent studies of the stability of polyG-polyC and polyA-polyT DNA duplexes in solution. , 1998, Journal of biomolecular structure & dynamics.

[20]  Julian Tirado-Rives,et al.  Computer-aided design of non-nucleoside inhibitors of HIV-1 reverse transcriptase. , 2006, Bioorganic & medicinal chemistry letters.

[21]  Ruhong Zhou,et al.  New Linear Interaction Method for Binding Affinity Calculations Using a Continuum Solvent Model , 2001 .

[22]  J. Essex,et al.  Hit identification and binding mode predictions by rigorous free energy simulations. , 2008, Journal of medicinal chemistry.

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

[24]  James Andrew McCammon,et al.  Ligand-receptor interactions , 1984, Comput. Chem..

[25]  H. Berendsen,et al.  COMPUTER-SIMULATION OF MOLECULAR-DYNAMICS - METHODOLOGY, APPLICATIONS, AND PERSPECTIVES IN CHEMISTRY , 1990 .

[26]  Paulo Augusto Netz,et al.  Linear interaction energy (LIE) method in lead discovery and optimization. , 2008, Current drug targets.

[27]  B. Berne,et al.  A Multiple-Time-Step Molecular Dynamics Algorithm for Macromolecules , 1994 .

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

[29]  F. Österberg,et al.  Exploring blocker binding to a homology model of the open hERG K+ channel using docking and molecular dynamics methods , 2005, FEBS letters.

[30]  Julien Michel,et al.  Protein-ligand binding affinity predictions by implicit solvent simulations: a tool for lead optimization? , 2006, Journal of medicinal chemistry.

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

[32]  J. Åqvist,et al.  Ligand binding affinities from MD simulations. , 2002, Accounts of chemical research.

[33]  P A Kollman,et al.  What determines the van der Waals coefficient β in the LIE (linear interaction energy) method to estimate binding free energies using molecular dynamics simulations? , 1999, Proteins.

[34]  Julien Michel,et al.  The parameterization and validation of generalized born models using the pairwise descreening approximation , 2004, J. Comput. Chem..

[35]  Jens Carlsson,et al.  Predicting binding modes from free energy calculations. , 2008, Journal of medicinal chemistry.

[36]  Ulrich Rester,et al.  From virtuality to reality - Virtual screening in lead discovery and lead optimization: a medicinal chemistry perspective. , 2008, Current opinion in drug discovery & development.

[37]  P. Kollman,et al.  Calculating structures and free energies of complex molecules: combining molecular mechanics and continuum models. , 2000, Accounts of chemical research.

[38]  R. Elber,et al.  Modeling side chains in peptides and proteins: Application of the locally enhanced sampling and the simulated annealing methods to find minimum energy conformations , 1991 .

[39]  Amedeo Caflisch,et al.  Efficient evaluation of binding free energy using continuum electrostatics solvation. , 2004, Journal of medicinal chemistry.

[40]  Mark A Olson,et al.  An efficient hybrid explicit/implicit solvent method for biomolecular simulations , 2004, J. Comput. Chem..

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

[42]  J. Andrew McCammon,et al.  Free energy difference calculations by thermodynamic integration: Difficulties in obtaining a precise value , 1991 .

[43]  Lev D. Gelb,et al.  Monte Carlo simulations using sampling from an approximate potential , 2003 .

[44]  J. Andrew McCammon,et al.  Dynamics and design of enzymes and inhibitors , 1986 .

[45]  H. Senderowitz,et al.  G Protein-Coupled Receptors: target-based in silico screening. , 2009, Current pharmaceutical design.

[46]  Jens Carlsson,et al.  Combining docking, molecular dynamics and the linear interaction energy method to predict binding modes and affinities for non-nucleoside inhibitors to HIV-1 reverse transcriptase. , 2008, Journal of medicinal chemistry.

[47]  William L. Jorgensen,et al.  Analysis of Binding Affinities for Celecoxib Analogues with COX-1 and COX-2 from Combined Docking and Monte Carlo Simulations and Insight into the COX-2/COX-1 Selectivity , 2000 .

[48]  Michael W Deem,et al.  Parallel tempering: theory, applications, and new perspectives. , 2005, Physical chemistry chemical physics : PCCP.

[49]  M. Karplus,et al.  Enhanced sampling in molecular dynamics: use of the time-dependent Hartree approximation for a simulation of carbon monoxide diffusion through myoglobin , 1990 .

[50]  W. C. Still,et al.  Semianalytical treatment of solvation for molecular mechanics and dynamics , 1990 .

[51]  Chris Oostenbrink,et al.  Are Automated Molecular Dynamics Simulations and Binding Free Energy Calculations Realistic Tools in Lead Optimization? An Evaluation of the Linear Interaction Energy (LIE) Method , 2006, J. Chem. Inf. Model..