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Docking Covalent Inhibitors: A Parameter Free Approach To Pose Prediction and Scoring
journal contribution
posted on 2014-07-28, 00:00 authored by Kai Zhu, Kenneth
W. Borrelli, Jeremy R. Greenwood, Tyler Day, Robert Abel, Ramy S. Farid, Edward HarderAlthough
many popular docking programs include a facility to account
for covalent ligands, large-scale systematic docking validation studies
of covalent inhibitors have been sparse. In this paper, we present
the development and validation of a novel approach for docking and
scoring covalent inhibitors, which consists of conventional noncovalent
docking, heuristic formation of the covalent attachment point, and
structural refinement of the protein–ligand complex. This approach
combines the strengths of the docking program Glide and the protein
structure modeling program Prime and does not require any parameter
fitting for the study of additional covalent reaction types. We first
test this method by predicting the native binding geometry of 38 covalently
bound complexes. The average RMSD of the predicted poses is 1.52 Å,
and 76% of test set inhibitors have an RMSD of less than 2.0 Å.
In addition, the apparent affinity score constructed herein is tested
on a virtual screening study and the characterization of the SAR properties
of two different series of congeneric compounds with satisfactory
success.