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TSCC: Two-Stage Combinatorial Clustering for virtual screening using protein-ligand interactions and physicochemical features

BACKGROUND: The increasing numbers of 3D compounds and protein complexes stored in databases contribute greatly to current advances in biotechnology, being employed in several pharmaceutical and industrial applications. However, screening and retrieving appropriate candidates as well as handling fal...

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Autores principales: Clinciu, Daniel L, Chen, Yen-Fu, Ko, Cheng-Neng, Lo, Chi-Chun, Yang, Jinn-Moon
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3005922/
https://www.ncbi.nlm.nih.gov/pubmed/21143810
http://dx.doi.org/10.1186/1471-2164-11-S4-S26
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author Clinciu, Daniel L
Chen, Yen-Fu
Ko, Cheng-Neng
Lo, Chi-Chun
Yang, Jinn-Moon
author_facet Clinciu, Daniel L
Chen, Yen-Fu
Ko, Cheng-Neng
Lo, Chi-Chun
Yang, Jinn-Moon
author_sort Clinciu, Daniel L
collection PubMed
description BACKGROUND: The increasing numbers of 3D compounds and protein complexes stored in databases contribute greatly to current advances in biotechnology, being employed in several pharmaceutical and industrial applications. However, screening and retrieving appropriate candidates as well as handling false positives presents a challenge for all post-screening analysis methods employed in retrieving therapeutic and industrial targets. RESULTS: Using the TSCC method, virtually screened compounds were clustered based on their protein-ligand interactions, followed by structure clustering employing physicochemical features, to retrieve the final compounds. Based on the protein-ligand interaction profile (first stage), docked compounds can be clustered into groups with distinct binding interactions. Structure clustering (second stage) grouped similar compounds obtained from the first stage into clusters of similar structures; the lowest energy compound from each cluster being selected as a final candidate. CONCLUSION: By representing interactions at the atomic-level and including measures of interaction strength, better descriptions of protein-ligand interactions and a more specific analysis of virtual screening was achieved. The two-stage clustering approach enhanced our post-screening analysis resulting in accurate performances in clustering, mining and visualizing compound candidates, thus, improving virtual screening enrichment.
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spelling pubmed-30059222010-12-22 TSCC: Two-Stage Combinatorial Clustering for virtual screening using protein-ligand interactions and physicochemical features Clinciu, Daniel L Chen, Yen-Fu Ko, Cheng-Neng Lo, Chi-Chun Yang, Jinn-Moon BMC Genomics Proceedings BACKGROUND: The increasing numbers of 3D compounds and protein complexes stored in databases contribute greatly to current advances in biotechnology, being employed in several pharmaceutical and industrial applications. However, screening and retrieving appropriate candidates as well as handling false positives presents a challenge for all post-screening analysis methods employed in retrieving therapeutic and industrial targets. RESULTS: Using the TSCC method, virtually screened compounds were clustered based on their protein-ligand interactions, followed by structure clustering employing physicochemical features, to retrieve the final compounds. Based on the protein-ligand interaction profile (first stage), docked compounds can be clustered into groups with distinct binding interactions. Structure clustering (second stage) grouped similar compounds obtained from the first stage into clusters of similar structures; the lowest energy compound from each cluster being selected as a final candidate. CONCLUSION: By representing interactions at the atomic-level and including measures of interaction strength, better descriptions of protein-ligand interactions and a more specific analysis of virtual screening was achieved. The two-stage clustering approach enhanced our post-screening analysis resulting in accurate performances in clustering, mining and visualizing compound candidates, thus, improving virtual screening enrichment. BioMed Central 2010-12-02 /pmc/articles/PMC3005922/ /pubmed/21143810 http://dx.doi.org/10.1186/1471-2164-11-S4-S26 Text en Copyright ©2010 Clinciu et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Proceedings
Clinciu, Daniel L
Chen, Yen-Fu
Ko, Cheng-Neng
Lo, Chi-Chun
Yang, Jinn-Moon
TSCC: Two-Stage Combinatorial Clustering for virtual screening using protein-ligand interactions and physicochemical features
title TSCC: Two-Stage Combinatorial Clustering for virtual screening using protein-ligand interactions and physicochemical features
title_full TSCC: Two-Stage Combinatorial Clustering for virtual screening using protein-ligand interactions and physicochemical features
title_fullStr TSCC: Two-Stage Combinatorial Clustering for virtual screening using protein-ligand interactions and physicochemical features
title_full_unstemmed TSCC: Two-Stage Combinatorial Clustering for virtual screening using protein-ligand interactions and physicochemical features
title_short TSCC: Two-Stage Combinatorial Clustering for virtual screening using protein-ligand interactions and physicochemical features
title_sort tscc: two-stage combinatorial clustering for virtual screening using protein-ligand interactions and physicochemical features
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3005922/
https://www.ncbi.nlm.nih.gov/pubmed/21143810
http://dx.doi.org/10.1186/1471-2164-11-S4-S26
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