Journal Article10.1038/NRD1549
Docking and scoring in virtual screening for drug discovery: methods and applications.
TL;DR: Key concepts and specific features of small-molecule–protein docking methods are reviewed, selected applications are highlighted and recent advances that aim to address the acknowledged limitations of established approaches are discussed.
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Abstract: Computational approaches that 'dock' small molecules into the structures of macromolecular targets and 'score' their potential complementarity to binding sites are widely used in hit identification and lead optimization Indeed, there are now a number of drugs whose development was heavily influenced by or based on structure-based design and screening strategies, such as HIV protease inhibitors Nevertheless, there remain significant challenges in the application of these approaches, in particular in relation to current scoring schemes Here, we review key concepts and specific features of small-molecule-protein docking methods, highlight selected applications and discuss recent advances that aim to address the acknowledged limitations of established approaches
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Citations
An introduction to biomolecular simulations and docking
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Knowledge-based scoring functions in drug design: 2. Can the knowledge base be enriched?
Qiancheng Shen,Bing Xiong,Mingyue Zheng,Xiaomin Luo,Cheng Luo,Xian Liu,Yun Du,Jing Li,Weiliang Zhu,Jingkang Shen,Hualiang Jiang,Hualiang Jiang +11 more
TL;DR: A scoring function named IPMF is reported that integrates additional experimental binding affinity information into the extracted potentials, on the assumption that a scoring function with the "enriched" knowledge base may achieve increased accuracy in binding affinity prediction.
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References
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Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function
Garrett M. Morris,David S. Goodsell,Robert Scott Halliday,Ruth Huey,William E. Hart,Richard K. Belew,Arthur J. Olson +6 more
TL;DR: It is shown that both the traditional and Lamarckian genetic algorithms can handle ligands with more degrees of freedom than the simulated annealing method used in earlier versions of AUTODOCK, and that the Lamarckia genetic algorithm is the most efficient, reliable, and successful of the three.
Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy.
Richard A. Friesner,Jay L. Banks,Robert B. Murphy,Thomas A. Halgren,Jasna Klicic,Daniel T. Mainz,Matthew P. Repasky,Eric H. Knoll,Mee Shelley,Jason K. Perry,David E. Shaw,Perry Francis,Peter S Shenkin +12 more
TL;DR: Glide approximates a complete systematic search of the conformational, orientational, and positional space of the docked ligand to find the best docked pose using a model energy function that combines empirical and force-field-based terms.
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TL;DR: GOLD (Genetic Optimisation for Ligand Docking) is an automated ligand docking program that uses a genetic algorithm to explore the full range of ligand conformational flexibility with partial flexibility of the protein, and satisfies the fundamental requirement that the ligand must displace loosely bound water on binding.
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Glide: a new approach for rapid, accurate docking and scoring. 2. Enrichment factors in database screening.
Thomas A. Halgren,Robert B. Murphy,Richard A. Friesner,Hege S. Beard,Leah L. Frye,W. Thomas Pollard,Jay L. Banks +6 more
TL;DR: Comparisons to results for the thymidine kinase and estrogen receptors published by Rognan and co-workers show that Glide 2.5 performs better than GOLD 1.1, FlexX 1.8, or DOCK 4.01.