Ensemble-Based Steered Molecular Dynamics Predicts Relative Residence Time of A_2A Receptor Binders

Abstract

Drug-target residence time, the length of time for which a small molecule stays bound to its receptor target, has increasingly become a key property for optimization in drug discovery programs. However, its in silico prediction has proven difficult. Here we describe a method, using atomistic ensemble-based steered molecular dynamics (SMD), to observe the dissociation of ligands from their target G protein-coupled receptor in a time scale suitable for drug discovery. These dissociation simulations accurately, precisely, and reproducibly identify ligand-residue interactions and quantify the change in ligand energy values for both protein and water. The method has been applied to 17 ligands of the A 2A adenosine receptor, all with published experimental kinetic binding data. The residues that interact with the ligand as it dissociates are known experimentally to have an effect on binding affinities and residence times. There is a good correlation (R 2 = 0.79) between the computationally calculated change in waterligand interaction energy and experimentally determined residence time. Our results indicate that ensemble-based SMD is a rapid, novel, and accurate semi-empirical method for the determination of drug-target relative residence time.

Uncertainty quantification in classical molecular dynamics

“…Extensive studies we and others have performed in recent years [8,44,[46][47][48][49][64][65][66][67][68][69][70][71][72][73][74] confirm that the most effective and reliable computational route to reproducible binding free energies of ligands to proteins using MD simulation can be achieved using ensemble methods. The same conclusion has been drawn from MD simulations in other areas, including studies on materials applications such as graphene-based systems [75], on DNA nanopores using coarse-grained MD [76] and so on [77,78].…”

Rapid, accurate, precise and reproducible ligand–protein binding free energy prediction

“…The former normally trap a system for very long times, while the latter can only be accessed rarely and transitorily [ 9 ]. Transition path sampling [ 55 ] is one common approach to investigate the transition paths connecting different minima, in which accelerated MD approaches such as metadynamics [ 67 ], steered MD [ 117 ] and high-temperature simulations are first used to construct an overall free energy landscape, followed by ensemble simulations from putative transition states to generate a transition path containing information on the mechanism and kinetics of the process [ 121 ]. The ensemble simulations consist of many relatively short runs sampling regions between different minima but do not need to spend a long time in any specific minimum.…”

Hit-to-lead and lead optimization binding free energy calculations for G protein-coupled receptors

“…There is an urgent need for approaches and tools that permit the prediction of rapid, accurate and reliable properties of systems across science as a whole. We have a longstanding interest in the development of in silico methodologies able to predict values computationally that agree with and therefore may replace experimental measurements [ 1 – 4 ]. Here, we focus our efforts on a subject of global importance in computational biomedicine: the accurate prediction of protein–small molecule binding affinities.…”