Comparison of simple potential functions for simulating liquid water

Abstract

Extremely precise free energy calculations of amino acid side chain analogs: Comparison of common molecular mechanics force fields for proteins Computational techniques see widespread use in pharmaceutical drug discovery, but typically prove unreliable in predicting trends in protein-ligand binding. Alchemical free energy calculations seek to change that by providing rigorous binding free energies from molecular simulations. Given adequate sampling and an accurate enough force field, these techniques yield accurate free energy estimates. Recent innovations in alchemical techniques have sparked a resurgence of interest in these calculations. Still, many obstacles stand in the way of their routine application in a drug discovery context, including the one we focus on here, sampling. Sampling of binding modes poses a particular challenge as binding modes are often separated by large energy barriers, leading to slow transitions. Binding modes are difficult to predict, and in some cases multiple binding modes may contribute to binding. In view of these hurdles, we present a framework for dealing carefully with uncertainty in binding mode or conformation in the context of free energy calculations. With careful sampling, free energy techniques show considerable promise for aiding drug discovery.

Combined QM/MM and path integral simulations of kinetic isotope effects in the proton transfer reaction between nitroethane and acetate ion in water

“…43 The details have been described in a number of articles. In the deprotonation of nitroethane by acetate ion, the standard semiempirical AM1 model 44 failed to yield adequate energetic results.…”

Functional analyses and molecular modeling of two c-Kit mutations responsible for imatinib secondary resistance in GIST patients

“…Mutations T670I and V654A were introduced into the wild-type structure of KIT/imatinib complex using the Biopolymer module of Insight II (v. 2001, Accerlys Inc., San Diego, CA, USA) by swapping the mutant residue into the specific site, according to a dedicated and well-validated procedure (Reyes and Kollman, 2000;Pricl et al, 2005). To set up each resulting complex for the simulation, we adopted the following ansatz: first, each complex was immersed in a sphere of TIP3P water molecules (Jorgensen et al, 1983). To achieve electroneutrality, a suitable number of counterions were added, in the positions of largest electrostatic potential, as determined by the module Cion within AMBER 7.0.…”

Molecular dynamics simulations of galectin‐1‐oligosaccharide complexes reveal the molecular basis for ligand diversity

“…All histidine residues were assumed to be neutral and were protonated at the Nε position. For the water droplet, a sphere of TIP3P waters 31 with a radius of 26 Å was centered at the ligand center of mass. Diffusion of waters out of this droplet was prevented through the use of a half-harmonic potential applied at the droplet surface.…”