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![Noteworthy comment: Structure-based virtual screening of compound collections can help identify hits that can be optimized to lead and result in potential drug candidate. This method can also be used to probe the molecular function of a macromolecular target and thus helps understand structure-function relationships. Further, docking of a compound to an Xray or NMR structure or homology model can definitively assist the drug discovery process. However, there are numerous problems and limitations associated with docking, one of these problems is to be able to assess or be confident with predicted pose of the potential drug candidate on the surface of the macromolecular target possibly involved in the health and disease state. In the paper by Mantsyzov et al, some strategies are proposed to address this problem, the benchmarking of the approach and the overall results suggest that their approach is valuable. As such, this paper should be of interest to the scientific community working in the field of drug design.
Evaluation of docking results is one of the most important problems for virtual screening and in silico drug design.](assets/img/article_icons/noteworthy.png)
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Contact-based ligand-clustering approach for the identification of active compounds in virtual screening
Authors Mantsyzov, Bouvier, Evrard-Todeschi, Bertho G
Received 15 February 2012
Accepted for publication 5 April 2012
Published 6 September 2012 Volume 2012:5 Pages 61—79
DOI https://doi.org/10.2147/AABC.S30881
Review by Single anonymous peer review
Peer reviewer comments 7
Alexey B Mantsyzov,1 Guillaume Bouvier,2 Nathalie Evrard-Todeschi,1 Gildas Bertho1
1Université Paris Descartes, Sorbonne, Paris, France; 2Institut Pasteur, Paris, France
Abstract: Evaluation of docking results is one of the most important problems for virtual screening and in silico drug design. Modern approaches for the identification of active compounds in a large data set of docked molecules use energy scoring functions. One of the general and most significant limitations of these methods relates to inaccurate binding energy estimation, which results in false scoring of docked compounds. Automatic analysis of poses using self-organizing maps (AuPosSOM) represents an alternative approach for the evaluation of docking results based on the clustering of compounds by the similarity of their contacts with the receptor. A scoring function was developed for the identification of the active compounds in the AuPosSOM clustered dataset. In addition, the AuPosSOM efficiency for the clustering of compounds and the identification of key contacts considered as important for its activity, were also improved. Benchmark tests for several targets revealed that together with the developed scoring function, AuPosSOM represents a good alternative to the energy-based scoring functions for the evaluation of docking results.
Keywords: scoring, docking, virtual screening, CAR, AuPosSOM
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