Customizable de novo design strategies for DOCK: Application to HIVgp41 and other therapeutic targets
Abstract
De novo design can be used to explore vast areas of chemical space in computational lead discovery. As a complement to virtual screening, from‐scratch construction of molecules is not limited to compounds in pre‐existing vendor catalogs. Here, we present an iterative fragment growth method, integrated into the program DOCK, in which new molecules are built using rules for allowable connections based on known molecules. The method leverages DOCK's advanced scoring and pruning approaches and users can define very specific criteria in terms of properties or features to customize growth toward a particular region of chemical space. The code was validated using three increasingly difficult classes of calculations: (1) Rebuilding known X‐ray ligands taken from 663 complexes using only their component parts (focused libraries), (2) construction of new ligands in 57 drug target sites using a library derived from ∼13M drug‐like compounds (generic libraries), and (3) application to a challenging protein‐protein interface on the viral drug target HIVgp41. The computational testing confirms that the de novo DOCK routines are robust and working as envisioned, and the compelling results highlight the potential utility for designing new molecules against a wide variety of important protein targets. © 2017 Wiley Periodicals, Inc.
- Authors:
-
- Department of Applied Mathematics and Statistics Stony Brook University Stony Brook New York 11794
- Department of Biochemistry and Cell Biology Stony Brook University Stony Brook New York 11794
- Department of Pharmaceutical Chemistry University of California, San Francisco San Francisco California 94158
- Department of Applied Mathematics and Statistics Stony Brook University Stony Brook New York 11794, Institute of Chemical Biology and Drug Discovery, Stony Brook University Stony Brook New York 11794, Laufer Center for Physical and Quantitative Biology, Stony Brook University Stony Brook New York 11794
- Publication Date:
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1393999
- Grant/Contract Number:
- DE‐AC02‐98CH10886
- Resource Type:
- Publisher's Accepted Manuscript
- Journal Name:
- Journal of Computational Chemistry
- Additional Journal Information:
- Journal Name: Journal of Computational Chemistry Journal Volume: 38 Journal Issue: 30; Journal ID: ISSN 0192-8651
- Publisher:
- Wiley Blackwell (John Wiley & Sons)
- Country of Publication:
- United States
- Language:
- English
Citation Formats
Allen, William J., Fochtman, Brian C., Balius, Trent E., and Rizzo, Robert C. Customizable de novo design strategies for DOCK: Application to HIVgp41 and other therapeutic targets. United States: N. p., 2017.
Web. doi:10.1002/jcc.25052.
Allen, William J., Fochtman, Brian C., Balius, Trent E., & Rizzo, Robert C. Customizable de novo design strategies for DOCK: Application to HIVgp41 and other therapeutic targets. United States. https://doi.org/10.1002/jcc.25052
Allen, William J., Fochtman, Brian C., Balius, Trent E., and Rizzo, Robert C. Fri .
"Customizable de novo design strategies for DOCK: Application to HIVgp41 and other therapeutic targets". United States. https://doi.org/10.1002/jcc.25052.
@article{osti_1393999,
title = {Customizable de novo design strategies for DOCK: Application to HIVgp41 and other therapeutic targets},
author = {Allen, William J. and Fochtman, Brian C. and Balius, Trent E. and Rizzo, Robert C.},
abstractNote = {De novo design can be used to explore vast areas of chemical space in computational lead discovery. As a complement to virtual screening, from‐scratch construction of molecules is not limited to compounds in pre‐existing vendor catalogs. Here, we present an iterative fragment growth method, integrated into the program DOCK, in which new molecules are built using rules for allowable connections based on known molecules. The method leverages DOCK's advanced scoring and pruning approaches and users can define very specific criteria in terms of properties or features to customize growth toward a particular region of chemical space. The code was validated using three increasingly difficult classes of calculations: (1) Rebuilding known X‐ray ligands taken from 663 complexes using only their component parts (focused libraries), (2) construction of new ligands in 57 drug target sites using a library derived from ∼13M drug‐like compounds (generic libraries), and (3) application to a challenging protein‐protein interface on the viral drug target HIVgp41. The computational testing confirms that the de novo DOCK routines are robust and working as envisioned, and the compelling results highlight the potential utility for designing new molecules against a wide variety of important protein targets. © 2017 Wiley Periodicals, Inc.},
doi = {10.1002/jcc.25052},
journal = {Journal of Computational Chemistry},
number = 30,
volume = 38,
place = {United States},
year = {Fri Sep 22 00:00:00 EDT 2017},
month = {Fri Sep 22 00:00:00 EDT 2017}
}
https://doi.org/10.1002/jcc.25052
Web of Science
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