Lipid tempering simulation of model biological membranes on parallel platforms

Relative Binding Free Energy between Chemically Distant Compounds Using a Bidirectional Nonequilibrium Approach

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 bidirectional 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 RBFEs 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 coefficients, 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.

Computational Modeling of Realistic Cell Membranes

Cell membranes contain a large variety of lipid types and are crowded with proteins, endowing them with the plasticity needed to fulfill their key roles in cell functioning. The compositional complexity of cellular membranes gives rise to a heterogeneous lateral organization, which is still poorly understood. Computational models, in particular molecular dynamics simulations and related techniques, have provided important insight into the organizational principles of cell membranes over the past decades. Now, we are witnessing a transition from simulations of simpler membrane models to multicomponent systems, culminating in realistic models of an increasing variety of cell types and organelles. Here, we review the state of the art in the field of realistic membrane simulations and discuss the current limitations and challenges ahead.