Virtual Screening Using Combinatorial Cyclic Peptide Libraries Reveals Protein Interfaces Readily Targetable by Cyclic Peptides

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Title: Virtual Screening Using Combinatorial Cyclic Peptide Libraries Reveals Protein Interfaces Readily Targetable by Cyclic Peptides
Authors: Duffy, Fergal J.
O'Donovan, Darragh
Devocelle, Marc
Moran, Niamh
O'Connell, David J.
Shields, Denis C.
Permanent link: http://hdl.handle.net/10197/7474
Date: 10-Feb-2015
Abstract: Protein–protein and protein–peptide interactions are responsible for the vast majority of biological functions in vivo, but targeting these interactions with small molecules has historically been difficult. What is required are efficient combined computational and experimental screening methods to choose among a number of potential protein interfaces worthy of targeting lead macrocyclic compounds for further investigation. To achieve this, we have generated combinatorial 3D virtual libraries of short disulfide-bonded peptides and compared them to pharmacophore models of important protein–protein and protein–peptide structures, including short linear motifs (SLiMs), protein-binding peptides, and turn structures at protein–protein interfaces, built from 3D models available in the Protein Data Bank. We prepared a total of 372 reference pharmacophores, which were matched against 108,659 multiconformer cyclic peptides. After normalization to exclude nonspecific cyclic peptides, the top hits notably are enriched for mimetics of turn structures, including a turn at the interaction surface of human α thrombin, and also feature several protein-binding peptides. The top cyclic peptide hits also cover the critical 'hot spot' interaction sites predicted from the interaction crystal structure. We have validated our method by testing cyclic peptides predicted to inhibit thrombin, a key protein in the blood coagulation pathway of important therapeutic interest, identifying a cyclic peptide inhibitor with lead-like activity. We conclude that protein interfaces most readily targetable by cyclic peptides and related macrocyclic drugs may be identified computationally among a set of candidate interfaces, accelerating the choice of interfaces against which lead compounds may be screened.
Funding Details: Science Foundation Ireland
Type of material: Journal Article
Publisher: American Chemical Society
Journal: Journal of Chemical Information and Modeling
Volume: 55
Issue: 3
Start page: 600
End page: 613
Copyright (published version): 2015 American Chemical Society
Keywords: Protein-protein interactionsReference structuresCyclic peptidesPharmacophore modelsThrombin inhibitors
DOI: 10.1021/ci500431q
Language: en
Status of Item: Peer reviewed
Appears in Collections:Conway Institute Research Collection
CASL Research Collection
Biomolecular and Biomedical Science Research Collection
Medicine Research Collection

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