Document Detail

Classification of ligand molecules in PDB with fast heuristics graph match algorithm COMPLIG.
MedLine Citation:
PMID:  23041414     Owner:  NLM     Status:  Publisher    
A fast heuristic graph matching algorithm, COMPLIG, was devised to classify the small molecule ligands in the Protein Data Bank, which are currently not properly classified on structure basis. By concurrently classifying proteins and ligands, the most appropriate parameter for categorizing ligands was determined to be more than 60% identity of atoms and bonds between molecules, and 11,585 types of ligands were classified into 1,946 clusters. Although the large clusters were composed of nucleotides or amino acids, a significant presence of drug compounds was also observed. Application of the system to classify the natural ligand status of human proteins in the current database suggested that at most 37% of the experimental structures of human proteins were in complex with natural ligands. However, protein homology- and/or ligand similarity-based modeling was implied to provide models of natural interactions for an additional 28% of the total, which might be used to increase the knowledge of intrinsic protein-metabolite interactions.
Mihoko Saito; Naomi Takemura; Tsuyoshi Shirai
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2012-10-4
Journal Detail:
Title:  Journal of molecular biology     Volume:  -     ISSN:  1089-8638     ISO Abbreviation:  J. Mol. Biol.     Publication Date:  2012 Oct 
Date Detail:
Created Date:  2012-10-8     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  2985088R     Medline TA:  J Mol Biol     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
Copyright © 2012. Published by Elsevier Ltd.
Nagahama Institute of Bio-Science and Technology, and Japan Science and Technology Agency, Bioinformatics Research Division, Nagahama, Shiga 526-0829, Japan.
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