Improving Atom-Type Diversity and Sampling in Cosolvent Simulations Using λ-Dynamics.

Abstract

Cosolvent molecular dynamics (MD) simulations perform MD simulations of the protein in explicit water mixed with cosolvent molecules that represent functional groups of ligands potentially binding to the protein. The competition between different probes and water molecules allows the identification of the energetic preference of functional groups in different binding site moieties including enthalpic and entropic contributions. Cosolvent MD simulations have recently been applied to a variety of different questions in structure-based drug design but still have significant shortcomings. Among those issues is the limited chemical diversity of probe molecules ignoring the chemical context of the pharmacophoric feature represented by a probe. Here we present a novel cosolvent MD simulation method based on the λ-dynamics simulation concept that significantly increases the chemical diversity of functional groups investigated during cosolvent simulations. Application to four different test cases highlights the utility of the new approach to identify binding preferences of different functional groups and to correctly rank ligand series that differ by their substitution patterns.