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Cited by 462

The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.

Docking Covalent Inhibitors: A Parameter Free Approach To Pose Prediction and Scoring

Zhu, Kai, Borrelli, Kenneth W., Greenwood, Jeremy R., Day, Tyler, Abel, Robert, Farid, Ramy S., Harder, Edward·2014·Journal of Chemical Information and Modeling

Abstract

Although 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.

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Metadata

Authors
Zhu, K., Borrelli, K. W., Greenwood, J. R., Day, T., Abel, R., Farid, R. S., & Harder, E.
Venue
Journal of Chemical Information and Modeling
Published
2014-06-26
Volume
54
Issue
7
Pages
1932-1940
ISSN
  • 1549-9596 (ISSN-L)
  • 1549-960X
OpenAlex
W1995770177
Cited by
462
References
21
FWCI
19.76
Type
journal article
Language
en
Open access
closed

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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