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
Diverse, High-Quality Test Set for the Validation of Protein−Ligand Docking Performance
Michael J. Hartshorn,Marcel L. Verdonk,Gianni Chessari,Suzanne C. Brewerton,Wijnand T. M. Mooij,Paul N. Mortenson,Christopher William Murray +6 more
TL;DR: A procedure for analyzing and classifying publicly available crystal structures has been developed and has been used to identify high-resolution protein-ligand complexes that can be assessed by reconstructing the electron density for the ligand using the deposited structure factors.
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Virtual Screening with AutoDock: Theory and Practice.
Sandro Cosconati,Stefano Forli,Alexander L. Perryman,Rodney Harris,David S. Goodsell,Arthur J. Olson +5 more
TL;DR: An overview of the challenges of virtual screening is presented, along with the tools available in the AutoDock suite of programs for addressing these challenges, and the free, open source program AutoD dock is an effective tool for virtual screening.
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Virtual screening strategies in drug discovery: a critical review.
Antonio Lavecchia,C. Di Giovanni +1 more
TL;DR: This review provides a comprehensive appraisal of several VS approaches currently available and special emphasis will be given to in silico chemogenomics approaches which utilize annotated ligand-target as well as protein-ligand interaction databases and which could predict or reveal promiscuous binding and polypharmacology.
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Diversity-oriented synthesis: exploring the intersections between chemistry and biology
TL;DR: Diversity-oriented synthesis has provided powerful probes to investigate biological mechanisms and also served as a new driving force for advancing synthetic organic chemistry.
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Network of Time-Multiplexed Optical Parametric Oscillators as a Coherent Ising Machine
Alireza Marandi,Alireza Marandi,Zhe Wang,Kenta Takata,Kenta Takata,Robert L. Byer,Yoshihisa Yamamoto,Yoshihisa Yamamoto,Yoshihisa Yamamoto +8 more
TL;DR: In this article, a network of four degenerate optical parametric oscillators (OPOs) is employed to find the ground state of the Ising Hamiltonian, and a small non-deterministic polynomial time-hard problem is solved on a 4-OPO Ising machine.
References
Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings
TL;DR: Experimental and computational approaches to estimate solubility and permeability in discovery and development settings are described in this article, where the rule of 5 is used to predict poor absorption or permeability when there are more than 5 H-bond donors, 10 Hbond acceptors, and the calculated Log P (CLogP) is greater than 5 (or MlogP > 415).
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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.
Development and validation of a genetic algorithm for flexible docking.
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.