標題: Space-related pharma-motifs for fast search of protein binding motifs and polypharmacological targets
作者: Chiu, Yi-Yuan
Lin, Chun-Yu
Lin, Chih-Ta
Hsu, Kai-Cheng
Chang, Li-Zen
Yang, Jinn-Moon
生物科技學系
生物資訊及系統生物研究所
Department of Biological Science and Technology
Institude of Bioinformatics and Systems Biology
公開日期: 13-Dec-2012
摘要: Background: To discover a compound inhibiting multiple proteins (i.e. polypharmacological targets) is a new paradigm for the complex diseases (e.g. cancers and diabetes). In general, the polypharmacological proteins often share similar local binding environments and motifs. As the exponential growth of the number of protein structures, to find the similar structural binding motifs (pharma-motifs) is an emergency task for drug discovery (e. g. side effects and new uses for old drugs) and protein functions. Results: We have developed a Space-Related Pharmamotifs (called SRPmotif) method to recognize the binding motifs by searching against protein structure database. SRPmotif is able to recognize conserved binding environments containing spatially discontinuous pharma-motifs which are often short conserved peptides with specific physico-chemical properties for protein functions. Among 356 pharma-motifs, 56.5% interacting residues are highly conserved. Experimental results indicate that 81.1% and 92.7% polypharmacological targets of each protein-ligand complex are annotated with same biological process (BP) and molecular function (MF) terms, respectively, based on Gene Ontology (GO). Our experimental results show that the identified pharma-motifs often consist of key residues in functional (active) sites and play the key roles for protein functions. The SRPmotif is available at http://gemdock.life.nctu.edu.tw/SRP/. Conclusions: SRPmotif is able to identify similar pharma-interfaces and pharma-motifs sharing similar binding environments for polypharmacological targets by rapidly searching against the protein structure database. Pharmamotifs describe the conservations of binding environments for drug discovery and protein functions. Additionally, these pharma-motifs provide the clues for discovering new sequence-based motifs to predict protein functions from protein sequence databases. We believe that SRPmotif is useful for elucidating protein functions and drug discovery.
URI: http://dx.doi.org/10.1186/1471-2164-13-S7-S21
http://hdl.handle.net/11536/21514
ISSN: 1471-2164
DOI: 10.1186/1471-2164-13-S7-S21
期刊: BMC GENOMICS
Volume: 13
Issue: 
結束頁: 
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