On achieving high accuracy and reliability in the calculation of relative protein–ligand binding affinities

Abstract

We apply a free energy perturbation simulation method, free energy perturbation/replica exchange with solute tempering, to two modifications of protein-ligand complexes that lead to significant conformational changes, the first in the protein and the second in the ligand. The approach is shown to facilitate sampling in these challenging cases where high free energy barriers separate the initial and final conformations and leads to superior convergence of the free energy as demonstrated both by consistency of the results (independence from the starting conformation) and agreement with experimental binding affinity data. The second case, consisting of two neutral thrombin ligands that are taken from a recent medicinal chemistry program for this interesting pharmaceutical target, is of particular significance in that it demonstrates that good results can be obtained for large, complex ligands, as opposed to relatively simple model systems. To achieve quantitative agreement with experiment in the thrombin case, a next generation force field, Optimized Potentials for Liquid Simulations 2.0, is required, which provides superior charges and torsional parameters as compared to earlier alternatives.enhanced sampling | protein-ligand binding affinity | structural reorganization | lead optimization | drug design B iological processes often depend on protein-ligand binding so that accurate prediction of protein-ligand binding affinities is of central importance in structural based drug design (1-4). Among the existing methods used to calculate these binding affinities in explicit solvent, free energy perturbation (FEP) simulations provide one of the most rigorous simulation techniques. Usually FEP is applied in the lead optimization stage of structure based drug design and is used to rank-order a series of congeneric ligands to choose the most potent ones for further investigation (1-4).Despite the potentially large impact that FEP could have on structure based drug design projects, practical applications in an industrial context have been limited over the past decade. High accuracy and reliability in the methodology are required to make productive decisions about compound modification during late stage lead optimization, but neither has yet been demonstrated by existing implementations. Two types of challenges stand in the way of developing FEP into a true engineering platform for drug candidate optimization. Firstly, converging explicit solvent simulations to the desired precision is far from trivial, even with the immense computing power that is currently available using low cost multiprocessor clusters or cloud computing platforms of various types. Secondly, errors in the potential energy models must be reduced to the point where they lead to errors in a converged calculation that are smaller than the desired errors in relative binding affinities compared to experiment. In our estimation these errors are on the order of 0.5-1.0 kcal∕mole mean unsigned error for a typical late stage lead optimization effort in a drug dis...

Molecular dynamics and Monte Carlo simulations for protein–ligand binding and inhibitor design

“…Namely, Desmond, which is distributed as part of the Schrödinger package and is fully integrated with Maestro [18,19], which allows the efficient set-up of FEP calculations with MD sampling. Both MCPRO and Desmond optionally include replica exchange with solute tempering (REST) for enhanced sampling [7,20,21]. This allows the heating of local regions of the system, thus substantially improving traversal of the free energy surface while sampling rigorously from the Boltzmann ensemble.…”

Separated topologies—A method for relative binding free energy calculations using orientational restraints

“…In the single topology approach, there is one ligand molecule in all simulations, which morphs from being in state A (having a particular chemical structure and interaction parameters), to a different state B, where the structure and interaction parameters are different. [4][5][6][7][8][9][10][11][12][13] In some transformations, there could be atoms on A that have no direct analog on B. During the computational morphing process, these atoms will have their non-bonded interactions decoupled from the rest of the sysa) Author to whom correspondence should be addressed.…”

Towards predictive docking at aminergic G-protein coupled receptors

“…More precise estimation of binding energy than by scoring functions can be achieved by advanced MD calculations like free energy perturbations (FEP) [53] or replica exchange MD [54]. Calculation of binding energy by these methods is based on energy changes during MD simulation due to ligand dissociation.…”