2 Works

Binding Modes of Ligands Using Enhanced Sampling (BLUES): Rapid Decorrelation of Ligand Binding Modes via Nonequilibrium Candidate Monte Carlo

Samuel Gill, Nathan Lim, Patrick Grinaway, Arie╠łn Rustenburg, Josh Fass, Gregory Ross, John Chodera & David Mobley
Accurately predicting protein-ligand binding affinities and binding modes is a major goal in computational chemistry, but even the prediction of ligand binding modes in proteins poses major challenges. Here, we focus on solving the binding mode prediction problem for rigid fragments. That is, we focus on computing the dominant placement, conformation, and orientations of a relatively rigid, fragment-like ligand in a receptor, and the populations of the multiple binding modes which may be relevant. This...

Supporting Information: Toward learned chemical perception of force field typing rules

Camila Zanette, Caitlin C. Bannan, Christopher I. Bayly, Josh Fass, Michael K. Gilson, Michael R. Shirts, John D. Chodera & David L. Mobley
The Open Force Field Initiative seeks to to automate force field development in order to advance force fields and improve accuracy (openforcefield.org). An important part of this effort includes automating the determination of chemical perception --- that is, the way force field parameters are assigned to a molecule based on chemical environment. We developed a novel technology for this purpose, termed SMARTY. It generalizes atom typing by using direct chemical perception with SMARTS strings adopting...

Registration Year

  • 2018

Resource Types

  • Dataset


  • Memorial Sloan Kettering Cancer Center
  • University of California, Irvine
  • Santa Fe College
  • University of California, San Diego
  • University of Colorado Boulder