Lead Finder: An Approach To Improve Accuracy of Protein−Ligand Docking, Binding Energy Estimation, and Virtual Screening
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MolTech Ltd., Leninskie gory, 1/75A, Moscow 119992, Russian Federation, and BioMolTech Corp., 226 York Mills Road, Toronto, Ontario M2L 1L1, Canada
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Тип публикации: Journal Article
Дата публикации: 2008-11-13
scimago Q1
wos Q1
БС1
SJR: 1.467
CiteScore: 9.8
Impact factor: 5.3
ISSN: 15499596, 1549960X
PubMed ID:
19007114
General Chemistry
Computer Science Applications
General Chemical Engineering
Library and Information Sciences
Краткое описание
An innovative molecular docking algorithm and three specialized high accuracy scoring functions are introduced in the Lead Finder docking software. Lead Finder's algorithm for ligand docking combines the classical genetic algorithm with various local optimization procedures and resourceful exploitation of the knowledge generated during docking process. Lead Finder's scoring functions are based on a molecular mechanics functional which explicitly accounts for different types of energy contributions scaled with empiric coefficients to produce three scoring functions tailored for (a) accurate binding energy predictions; (b) correct energy-ranking of docked ligand poses; and (c) correct rank-ordering of active and inactive compounds in virtual screening experiments. The predicted values of the free energy of protein-ligand binding were benchmarked against a set of experimentally measured binding energies for 330 diverse protein-ligand complexes yielding rmsd of 1.50 kcal/mol. The accuracy of ligand docking was assessed on a set of 407 structures, which included almost all published test sets of the following programs: FlexX, Glide SP, Glide XP, Gold, LigandFit, MolDock, and Surflex. rmsd of 2 A or less was observed for 80-96% of the structures in the test sets (80.0% on the Glide XP and FlexX test sets, 96.0% on the Surflex and MolDock test sets). The ability of Lead Finder to distinguish between active and inactive compounds during virtual screening experiments was benchmarked against 34 therapeutically relevant protein targets. Impressive enrichment factors were obtained for almost all of the targets with the average area under receiver operator curve being equal to 0.92.
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Stroganov O. V. et al. Lead Finder: An Approach To Improve Accuracy of Protein−Ligand Docking, Binding Energy Estimation, and Virtual Screening // Journal of Chemical Information and Modeling. 2008. Vol. 48. No. 12. pp. 2371-2385.
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Stroganov O. V., Novikov F., Stroylov V., Kulkov V., Chilov G. G. Lead Finder: An Approach To Improve Accuracy of Protein−Ligand Docking, Binding Energy Estimation, and Virtual Screening // Journal of Chemical Information and Modeling. 2008. Vol. 48. No. 12. pp. 2371-2385.
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TY - JOUR
DO - 10.1021/ci800166p
UR - https://doi.org/10.1021/ci800166p
TI - Lead Finder: An Approach To Improve Accuracy of Protein−Ligand Docking, Binding Energy Estimation, and Virtual Screening
T2 - Journal of Chemical Information and Modeling
AU - Stroganov, Oleg V
AU - Novikov, Fedor
AU - Stroylov, Victor
AU - Kulkov, Val
AU - Chilov, Ghermes G
PY - 2008
DA - 2008/11/13
PB - American Chemical Society (ACS)
SP - 2371-2385
IS - 12
VL - 48
PMID - 19007114
SN - 1549-9596
SN - 1549-960X
ER -
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@article{2008_Stroganov,
author = {Oleg V Stroganov and Fedor Novikov and Victor Stroylov and Val Kulkov and Ghermes G Chilov},
title = {Lead Finder: An Approach To Improve Accuracy of Protein−Ligand Docking, Binding Energy Estimation, and Virtual Screening},
journal = {Journal of Chemical Information and Modeling},
year = {2008},
volume = {48},
publisher = {American Chemical Society (ACS)},
month = {nov},
url = {https://doi.org/10.1021/ci800166p},
number = {12},
pages = {2371--2385},
doi = {10.1021/ci800166p}
}
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MLA
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Stroganov, Oleg V., et al. “Lead Finder: An Approach To Improve Accuracy of Protein−Ligand Docking, Binding Energy Estimation, and Virtual Screening.” Journal of Chemical Information and Modeling, vol. 48, no. 12, Nov. 2008, pp. 2371-2385. https://doi.org/10.1021/ci800166p.