Relative binding free energy between chemically distant compounds using a bidirectional nonequilibrium approach

22 February 2022, Version 1
This content is a preprint and has not undergone peer review at the time of posting.


In the context of advanced hit-to-lead drug design based on atomistic Molecular Dynamics simulations, we propose a dual topology alchemical approach for calculating the relative binding free energy (RBFE) between two chemically distant compounds. The method (termed NE-RBFE) relies on the enhanced sampling of the end-states in bulk and in the bound state via Hamiltonian Replica Exchange, alchemically connected by a series of independent and fast nonequilibrium (NE) simulations. The technique has been implemented in a bi-directional fashion, applying the Crooks theorem to the NE work distributions for RBFE predictions. The dissipation of the NE process, negatively affecting accuracy, has been minimized by introducing a smooth regularization based on shifted electrostatic and Lennard-Jones non bonded potentials. As a challenging testbed, we have applied our method to the calculation of the RBFE’s in the recent host-guest SAMPL international contest, featuring a macrocyclic host with guests varying in the net charge, volume, and chemical fingerprints. Closure validation has been successfully verified in cycles involving compounds with disparate Tanimoto coefficient, volume, and net charge. NE-RBFE is specifically tailored for massively parallel facilities and can be used with little or no code modification on most of the popular software packages supporting nonequilibrium alchemical simulations such as Gromacs, Amber, NAMD, or OpenMM. The proposed methodology bypasses most of the entanglements and limitations of the standard single topology RBFE approach for strictly congeneric series based on free energy perturbation, such as slowly relaxing cavity water, sampling issues along the alchemical stratification, and the need for highly overlapping molecular fingerprints.


drug design
relative binding free energy
molecular dynamics
free energy perturbation
enhaced sampling
Tanimoto coefficient
chemical fingerprint

Supplementary materials

Supporting Information
Figure S1-S13: bound and unbound state work distributions for all eighteen forward and reverse transmutation of Table 2 of the main paper. Figure S14: dissipation in RBFE and ABFE calculations as measured by the variance of the work distributions.

Supplementary weblinks


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