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Pep-Whisperer: Inhibitory peptide design.
Hurwitz, Naama; Zaidman, Daniel; Wolfson, Haim J.
Afiliação
  • Hurwitz N; Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel.
  • Zaidman D; Department of Organic Chemistry, Weizmann Institute of Science, Rehovot, Israel.
  • Wolfson HJ; Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel.
Proteins ; 90(11): 1886-1895, 2022 11.
Article em En | MEDLINE | ID: mdl-35598299
ABSTRACT
Designing peptides for protein-protein interaction inhibition is of significant interest in computer-aided drug design. Such inhibitory peptides could mimic and compete with the binding of the partner protein to the inhibition target. Experimental peptide design is a laborious, time consuming, and expensive multi-step process. Therefore, in silico peptide design can be beneficial for achieving this task. We present a novel algorithm, Pep-Whisperer, which aims to design inhibitory peptides for protein-protein interaction. The desirable peptides would have a relatively high predicted binding affinity to the target protein in a given protein-protein complex. The algorithm outputs linear peptides which are based on an initial template. The template could either be a peptide which is retrieved from the interaction site, or a patch of nonconsecutive amino acids from the protein-protein interface which is completed to a linear peptide by short polyalanine linkers. In addition, the algorithm takes into consideration the conservation of the amino acids in the ligand-protein binding site by using evolutionary information for choosing the preferred amino acids in each position of the designed peptide. Our algorithm was able to design peptides with high predicted binding affinity to the target protein. The method is fully automated and available as a web server at http//bioinfo3d.cs.tau.ac.il/PepWhisperer/.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Peptídeos / Proteínas Tipo de estudo: Prognostic_studies Idioma: En Revista: Proteins Assunto da revista: BIOQUIMICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Israel

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Peptídeos / Proteínas Tipo de estudo: Prognostic_studies Idioma: En Revista: Proteins Assunto da revista: BIOQUIMICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Israel