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Daniel Zaidman

dblp:183/8815 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2016
0000-0003-2695-1675ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › drug discovery › peptide drug discovery
peptide inhibitor design
0.212016
PinaColada: peptide-inhibitor ant colony ad-hoc design algorithm · Bioinform. 2016
Bioinformatics and computational biology
protein design
0.212016
PinaColada: peptide-inhibitor ant colony ad-hoc design algorithm · Bioinform. 2016
Bioinformatics and computational biology › protein analysis
protein-protein interaction
0.112016
PinaColada: peptide-inhibitor ant colony ad-hoc design algorithm · Bioinform. 2016
Bioinformatics and computational biology
structural bioinformatics
0.112016
PinaColada: peptide-inhibitor ant colony ad-hoc design algorithm · Bioinform. 2016

Methods — techniques the papers use, named apart from their topics

robotics-inspired conformational search · 0.2ant colony optimization · 0.2
YearPublicationVenuePosition
2016 PinaColada: peptide-inhibitor ant colony ad-hoc design algorithm
abstract
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 ([Formula: see text]) 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/. CONTACT: [email protected]; [email protected].
Daniel Zaidman, Haim J. Wolfson
Bioinform.1