TY - JOUR
T1 - PinaColada
T2 - Peptide-inhibitor ant colony ad-hoc design algorithm
AU - Zaidman, Daniel
AU - Wolfson, Haim J.
N1 - Publisher Copyright:
© 2016 The Author 2016. Published by Oxford University Press. All rights reserved.
PY - 2016/8/1
Y1 - 2016/8/1
N2 - Motivation: Design of protein-protein interaction (PPI) inhibitors is a major challenge in Structural Bioinformatics. Peptides, especially short ones (5-15 amino acid long), are natural candidates for inhibition of protein-protein complexes due to several attractive features such as high structural compatibility with the protein binding site (mimicking the surface of one of the proteins), small size and the ability to form strong hotspot binding connections with the protein surface. Efficient rational peptide design is still a major challenge in computer aided drug design, due to the huge space of possible sequences, which is exponential in the length of the peptide, and the high flexibility of peptide conformations. Results: In this article we present PinaColada, a novel computational method for the design of peptide inhibitors for protein-protein interactions. We employ a version of the ant colony optimization heuristic, which is used to explore the exponential space (20n) of length n peptide sequences, in combination with our fast robotics motivated PepCrawler algorithm, which explores the conformational space for each candidate sequence. PinaColada is being run in parallel, on a DELL PowerEdge 2.8 GHZ computer with 20 cores and 256 GB memory, and takes up to 24 h to design a peptide of 5-15 amino acids length. Availability and implementation: An online server available at: http://bioinfo3d.cs.tau.ac.il/PinaColada/.
AB - Motivation: Design of protein-protein interaction (PPI) inhibitors is a major challenge in Structural Bioinformatics. Peptides, especially short ones (5-15 amino acid long), are natural candidates for inhibition of protein-protein complexes due to several attractive features such as high structural compatibility with the protein binding site (mimicking the surface of one of the proteins), small size and the ability to form strong hotspot binding connections with the protein surface. Efficient rational peptide design is still a major challenge in computer aided drug design, due to the huge space of possible sequences, which is exponential in the length of the peptide, and the high flexibility of peptide conformations. Results: In this article we present PinaColada, a novel computational method for the design of peptide inhibitors for protein-protein interactions. We employ a version of the ant colony optimization heuristic, which is used to explore the exponential space (20n) of length n peptide sequences, in combination with our fast robotics motivated PepCrawler algorithm, which explores the conformational space for each candidate sequence. PinaColada is being run in parallel, on a DELL PowerEdge 2.8 GHZ computer with 20 cores and 256 GB memory, and takes up to 24 h to design a peptide of 5-15 amino acids length. Availability and implementation: An online server available at: http://bioinfo3d.cs.tau.ac.il/PinaColada/.
UR - http://www.scopus.com/inward/record.url?scp=84991471674&partnerID=8YFLogxK
U2 - 10.1093/bioinformatics/btw133
DO - 10.1093/bioinformatics/btw133
M3 - ???researchoutput.researchoutputtypes.contributiontojournal.article???
C2 - 27153578
AN - SCOPUS:84991471674
SN - 1367-4803
VL - 32
SP - 2289
EP - 2296
JO - Bioinformatics
JF - Bioinformatics
IS - 15
ER -