Enhanced sampling algorithms have emerged as powerful methods to extend the utility of
molecular dynamics simulations and allow the sampling of larger portions of the …

Abstract Machine learning (ML) has enabled ground-breaking advances in the healthcare
and pharmaceutical sectors, from improvements in cancer diagnosis, to the identification of …

We introduce the Open Force Field (OpenFF) 2.0. 0 small molecule force field for drug-like
molecules, code-named Sage, which builds upon our previous iteration, Parsley. OpenFF …

Alchemical free energy calculations are a useful tool for predicting free energy differences
associated with the transfer of molecules from one environment to another. The hallmark of …

In the hit identification stage of drug discovery, a diverse chemical space needs to be
explored to identify initial hits. Contrary to empirical scoring functions, absolute protein …

Predicting protein–ligand binding affinities and the associated thermodynamics of
biomolecular recognition is a primary objective of structure-based drug design. Alchemical …

We present a methodology for defining and optimizing a general force field for classical
molecular simulations, and we describe its use to derive the Open Force Field 1.0. 0 small …

We assess costs and efficiency of state-of-the-art high-performance cloud computing and
compare the results to traditional on-premises compute clusters. Our use case is atomistic …

Accurate ranking of compounds with regards to their binding affinity to a protein using
computational methods is of great interest to pharmaceutical research. Physics-based free …

Free-energy calculations have seen increased usage in structure-based drug design.
Despite the rising interest, automation of the complex calculations and subsequent analysis …