Email updates

Keep up to date with the latest news and content from BMC Genomics and BioMed Central.

This article is part of the supplement: Eleventh International Conference on Bioinformatics (InCoB2012): Computational Biology

Open Access Proceedings

Space-related pharma-motifs for fast search of protein binding motifs and polypharmacological targets

Yi-Yuan Chiu1, Chun-Yu Lin1, Chih-Ta Lin1, Kai-Cheng Hsu1, Li-Zen Chang1 and Jinn-Moon Yang12*

Author affiliations

1 Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, 30050, Taiwan

2 Department of Biological Science and Technology, National Chiao Tung University, 75 Po-Ai Street, Hsinchu, 30050, Taiwan

For all author emails, please log on.

Citation and License

BMC Genomics 2012, 13(Suppl 7):S21  doi:10.1186/1471-2164-13-S7-S21

Published: 13 December 2012

Abstract

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/ webcite.

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. Pharma-motifs 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.