Literature DB >> 35298817

Rapid Rational Design of Cyclic Peptides Mimicking Protein-Protein Interfaces.

Brianda L Santini1, Martin Zacharias2.   

Abstract

The cPEPmatch approach is a rapid computational methodology for the rational design of cyclic peptides to target desired regions of protein-protein interfaces. The method selects cyclic peptides that structurally match backbone structures of short segments at a protein-protein interface. In a second step, the cyclic peptides act as templates for designed binders by adapting the amino acid side chains to the side chains found in the target complex. A link to access the different tools that comprise the cPEPmatch method and a detailed step-by-step guide is provided. We outline the protocol by following the application to a trypsin protease in complex with the bovine inhibitor protein (BPTI). An extension of our original approach is also presented, where we give a detailed description of the usage of the cPEPmatch methodology focusing on identifying hot regions of protein-protein interfaces prior to the matching. This extension allows one to reduce the amount of evaluated putative cyclic peptides and to specifically design only those that compete with the strongest protein-protein binding regions. It is illustrated by an application to an MHC class I protein complex.
© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Cyclic peptide design; Drug design with cyclic peptides; Peptidomimetics; Protein binding modulation; Protein interaction inhibition; Protein–protein interactions; Rational cyclic peptide binders

Mesh:

Substances:

Year:  2022        PMID: 35298817     DOI: 10.1007/978-1-0716-1855-4_12

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  12 in total

Review 1.  Targeting protein-protein interactions: lessons from p53/MDM2.

Authors:  Justin K Murray; Samuel H Gellman
Journal:  Biopolymers       Date:  2007       Impact factor: 2.505

Review 2.  Reaching for high-hanging fruit in drug discovery at protein-protein interfaces.

Authors:  James A Wells; Christopher L McClendon
Journal:  Nature       Date:  2007-12-13       Impact factor: 49.962

3.  The atomic structure of protein-protein recognition sites.

Authors:  L Lo Conte; C Chothia; J Janin
Journal:  J Mol Biol       Date:  1999-02-05       Impact factor: 5.469

4.  Computational approaches to developing short cyclic peptide modulators of protein-protein interactions.

Authors:  Fergal J Duffy; Marc Devocelle; Denis C Shields
Journal:  Methods Mol Biol       Date:  2015

Review 5.  Small-molecule inhibitors of protein-protein interactions: progressing toward the reality.

Authors:  Michelle R Arkin; Yinyan Tang; James A Wells
Journal:  Chem Biol       Date:  2014-09-18

Review 6.  Small molecules, big targets: drug discovery faces the protein-protein interaction challenge.

Authors:  Duncan E Scott; Andrew R Bayly; Chris Abell; John Skidmore
Journal:  Nat Rev Drug Discov       Date:  2016-04-11       Impact factor: 84.694

Review 7.  Computational methods-guided design of modulators targeting protein-protein interactions (PPIs).

Authors:  Yuran Qiu; Xinyi Li; Xinheng He; Jun Pu; Jian Zhang; Shaoyong Lu
Journal:  Eur J Med Chem       Date:  2020-08-23       Impact factor: 6.514

8.  Hot spots and transient pockets: predicting the determinants of small-molecule binding to a protein-protein interface.

Authors:  Alexander Metz; Christopher Pfleger; Hannes Kopitz; Stefania Pfeiffer-Marek; Karl-Heinz Baringhaus; Holger Gohlke
Journal:  J Chem Inf Model       Date:  2011-12-27       Impact factor: 4.956

9.  Hot regions in protein--protein interactions: the organization and contribution of structurally conserved hot spot residues.

Authors:  Ozlem Keskin; Buyong Ma; Ruth Nussinov
Journal:  J Mol Biol       Date:  2004-12-02       Impact factor: 5.469

10.  ff14SB: Improving the Accuracy of Protein Side Chain and Backbone Parameters from ff99SB.

Authors:  James A Maier; Carmenza Martinez; Koushik Kasavajhala; Lauren Wickstrom; Kevin E Hauser; Carlos Simmerling
Journal:  J Chem Theory Comput       Date:  2015-07-23       Impact factor: 6.006

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