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Binary image representation of a ligand binding site: its application to efficient sampling of a conformational ensemble

BACKGROUND: Modelling the ligand binding site of a protein is an important component of understanding protein-ligand interactions and is being actively studied. Even if the side chains are restricted to rotamers, a set of commonly-observed low-energy conformations, the exhaustive combinatorial searc...

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Autores principales: Sung, Edon, Kim, Sangsoo, Shin, Whanchul
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3098062/
https://www.ncbi.nlm.nih.gov/pubmed/20478076
http://dx.doi.org/10.1186/1471-2105-11-256
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author Sung, Edon
Kim, Sangsoo
Shin, Whanchul
author_facet Sung, Edon
Kim, Sangsoo
Shin, Whanchul
author_sort Sung, Edon
collection PubMed
description BACKGROUND: Modelling the ligand binding site of a protein is an important component of understanding protein-ligand interactions and is being actively studied. Even if the side chains are restricted to rotamers, a set of commonly-observed low-energy conformations, the exhaustive combinatorial search of ligand binding site conformers is known as NP-hard. Here we propose a new method, ROTAIMAGE, for modelling the plausible conformers for the ligand binding site given a fixed backbone structure. RESULTS: ROTAIMAGE includes a procedure of selecting ligand binding site residues, exhaustively searching rotameric conformers, clustering them by dissimilarities in pocket shape, and suggesting a representative conformer per cluster. Prior to the clustering, the list of conformers generated by exhaustive search can be reduced by pruning the conformers that have near identical pocket shapes, which is done using simple bit operations. We tested our approach by modelling the active-site inhibitor binding pockets of matrix metalloproteinase-1 and -13. For both cases, analyzing the conformers based on their pocket shapes substantially reduced the 'computational complexity' (10 to 190 fold). The subsequent clustering revealed that the pocket shapes of both proteins could be grouped into approximately 10 distinct clusters. At this level of clustering, the conformational space spanned by the known crystal structures was well covered. Heatmap analysis identified a few bit blocks that combinatorially dictated the clustering pattern. Using this analytical approach, we demonstrated that each of the bit blocks was associated with a specific pocket residue. Identification of residues that influenced the shape of the pocket is an interesting feature unique to the ROTAIMAGE algorithm. CONCLUSIONS: ROTAIMAGE is a novel algorithm that was efficient in exploring the conformational space of the ligand binding site. Its ability to identify 'key' pocket residues also provides further insight into conformational flexibility with specific implications for protein-ligand interactions.
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spelling pubmed-30980622011-05-20 Binary image representation of a ligand binding site: its application to efficient sampling of a conformational ensemble Sung, Edon Kim, Sangsoo Shin, Whanchul BMC Bioinformatics Research Article BACKGROUND: Modelling the ligand binding site of a protein is an important component of understanding protein-ligand interactions and is being actively studied. Even if the side chains are restricted to rotamers, a set of commonly-observed low-energy conformations, the exhaustive combinatorial search of ligand binding site conformers is known as NP-hard. Here we propose a new method, ROTAIMAGE, for modelling the plausible conformers for the ligand binding site given a fixed backbone structure. RESULTS: ROTAIMAGE includes a procedure of selecting ligand binding site residues, exhaustively searching rotameric conformers, clustering them by dissimilarities in pocket shape, and suggesting a representative conformer per cluster. Prior to the clustering, the list of conformers generated by exhaustive search can be reduced by pruning the conformers that have near identical pocket shapes, which is done using simple bit operations. We tested our approach by modelling the active-site inhibitor binding pockets of matrix metalloproteinase-1 and -13. For both cases, analyzing the conformers based on their pocket shapes substantially reduced the 'computational complexity' (10 to 190 fold). The subsequent clustering revealed that the pocket shapes of both proteins could be grouped into approximately 10 distinct clusters. At this level of clustering, the conformational space spanned by the known crystal structures was well covered. Heatmap analysis identified a few bit blocks that combinatorially dictated the clustering pattern. Using this analytical approach, we demonstrated that each of the bit blocks was associated with a specific pocket residue. Identification of residues that influenced the shape of the pocket is an interesting feature unique to the ROTAIMAGE algorithm. CONCLUSIONS: ROTAIMAGE is a novel algorithm that was efficient in exploring the conformational space of the ligand binding site. Its ability to identify 'key' pocket residues also provides further insight into conformational flexibility with specific implications for protein-ligand interactions. BioMed Central 2010-05-18 /pmc/articles/PMC3098062/ /pubmed/20478076 http://dx.doi.org/10.1186/1471-2105-11-256 Text en Copyright ©2010 Sung 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 Research Article
Sung, Edon
Kim, Sangsoo
Shin, Whanchul
Binary image representation of a ligand binding site: its application to efficient sampling of a conformational ensemble
title Binary image representation of a ligand binding site: its application to efficient sampling of a conformational ensemble
title_full Binary image representation of a ligand binding site: its application to efficient sampling of a conformational ensemble
title_fullStr Binary image representation of a ligand binding site: its application to efficient sampling of a conformational ensemble
title_full_unstemmed Binary image representation of a ligand binding site: its application to efficient sampling of a conformational ensemble
title_short Binary image representation of a ligand binding site: its application to efficient sampling of a conformational ensemble
title_sort binary image representation of a ligand binding site: its application to efficient sampling of a conformational ensemble
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3098062/
https://www.ncbi.nlm.nih.gov/pubmed/20478076
http://dx.doi.org/10.1186/1471-2105-11-256
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