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Virtual screening consensus scoring

The calculation of the binding affinity with con.sidcration of all tbc.se effects for virtual screening is not possible. In order to circumvent thus difficulty, scoring functions arc used instead, c.g., the Liidi scoring function [80, or consensus scoring functions derived from FlevX score, DOCK score, GOLD score, ChemScore, or PMF score [81 ]. [Pg.611]

Wang RX, Wang SM. How does consensus scoring work for virtual library screening An idealized computer experiment. J Chem Inf Comput Sci 2001 41 1422-6. [Pg.416]

Wang RX, Wang SM. (2001) How does Consensus Scoring Work for Virtual Library Screening An Ideahzed Computer Experiment. /. Chem. Inf. Comp. Set. 41 1422-1426. [Pg.155]

Teramoto, R. and Fukunishi, H. (2007). Supervised consensus scoring for docking and virtual screening. J. Chem. Inf. Model. 47, 526-534. [Pg.133]

Surflex-Dock 2.1 virtual screening package (14-17) and CScore consensus scoring module (18), Tripos, Inc. [Pg.178]

Empirical Scoring, 264 2.4.3.S Knowledge-Based Scoring, 264 2.4.3.4 Consensus Scoring, 265 2.4.4 Docking as Virtual Screening Tool, 266 2.5 Filter Cascade, 267 3 Applications, 267... [Pg.244]

Mozziconacci et al.61 used Cox-2 as their test case. The first part of the paper looks at the selection of the optimal parameters for the docking protocol (here using DOCK), followed by a consensus scoring approach. Having optimised the protocol with known ligands, a large (13,711) virtual library was screened. Of the 12 compounds selected and available for assay, 4 had IC50 s < 1 /iM. [Pg.10]

Some work on consensus scoring in ligand-based virtual screening has indicated that much of the improvement from combining scores originates from the fact that different methods have different systematic errors [123]. It has also been shown on a theoretical basis that the combination of individual functions improves the enrichment of true actives only if each individual function is distinctive and has already a high performance [124]. [Pg.195]

B.S., and Hsu, D.F. (2005) Consensus scoring criteria for improving enrichment in virtual screening. Journal of Chemical Information and Modeling, 45, 1134-1146. [Pg.217]


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See also in sourсe #XX -- [ Pg.265 , Pg.291 , Pg.319 ]

See also in sourсe #XX -- [ Pg.265 , Pg.291 , Pg.319 ]




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