In this study, we subject a series of five protein-ligand systems which contain important SARS-CoV-2 targets - 3CLpro, PLpro and ADRP - to long-timescale and adaptive sampling molecular dynamics simulations. By performing ensembles of ten or twelve 10-microsecond simulations for each system, we accurately and reproducibly determine ligand binding sites including the crystallographically resolved ones, thereby discovering binding sites that can be exploited for drug discovery. We also investigate the reliability and accuracy of long-timescale trajectories. Due to the chaotic nature of molecular dynamics trajectories, individual long-timescale trajectories do not allow for accurate or reproducible elucidation of macroscopic expectation values. Upon comparing the statistical distribution of protein-ligand contact frequencies for these ten/twelve 10-microsecond trajectories, we find that over 90% of trajectories have significantly different contact frequency distributions where the associated Kolmogorov-Smirnov statistics have p values of &lt; 0.05. Furthermore, using a direct binding free energy calculation protocol, we determine the ligand binding free energies for each of the identified sites. We find that all long-timescale simulations lead to the computation of widely different values of binding free energy, regardless of their length. These differences range between 0.77 and 7.26 kcal/mol depending on the binding site and the system. Hence it is clear that although that is the standard way such quantities are reported, such a method cannot reliably determine the ligand binding free energy from an individual simulation to chemical accuracy (± 1 kcal/mol). The inherent non-reproducibility of properties calculated from these individual simulations demonstrates that it is only by running ensembles of many independent trajectories that we are able to overcome the aleatoric uncertainty intrinsic to these systems in order to obtain statistically robust, reproducible and precise results. We also show how the binding of one ligand at an experimentally determined allosteric binding site affects the binding of another ligand at the active site of 3CLPro target by performing long simulations with both ligands present simultaneously. By performing an ensemble of such simulations, we show how opposite conclusions could be obtained using individual replicas highlighting the necessity of ensembles to obtain reliable outcomes.

Long timescale ensemble simulation in molecular dynamics: Application to ligand-protein interactions in three SARS-CoV-2 targets

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