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

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.

Polar/apolar interfaces modulate the conformational behavior of cyclic peptides with impact on their passive membrane permeability

“…1,2 In contrast, macrocyclic drugs like cyclic peptides can bind to larger binding sites with at proles or protein-protein interfaces. [6][7][8][9][10][11][12] Cyclization has the added benet that it prevent rapid metabolic clearance. 13 Therefore, cyclic peptides have the potential to vastly extend the scope of druggable proteins and lead to therapeutics for currently untreatable diseases.…”

Rapid in silico Design of Potential Cyclic Peptide Binders Targeting Protein-Protein Interfaces

“…It is applicable if the structure of a protein-protein complex is known and even potentially useful if the receptor is flexible and adopts a different structure in the unbound form (as long as it can adopt the structure in the bound form). Most related to our method is an approach by Duffy et al ( 2015 ) to identify both protein–protein interactions suitable for inhibition by cyclic peptides and the accompanying cyclic peptides that represent promising lead compounds. This approach is, however, based on a pharmacophore matching of the PPI interface region with corresponding side chains on sets of cyclic peptides whereas our method is entirely based on structural matching of the interface backbone onto segments of cyclic peptides with known structure.…”

“…Different chemical strategies can be used to create cyclized peptides, including head-to-tail, disulfide, other side-chain to side-chain, and side-chain to terminus bonding (Martins and Carvalho, 2007 ; Wells and McClendon, 2007 ; Huigens et al, 2013 ; Duffy et al, 2015 ; Kuenemann et al, 2015 ; Milhas et al, 2016 ). Incorporating multiple cyclizations to generate peptides that are bicyclic, tricyclic, etc., can provide additional restraints to rigidify the peptide and provide further complexity of design space (Villoutreix et al, 2014 ; Che, 2019 ; Duffy et al, 2019 ).…”

“…Early and recent work has demonstrated the possibility to use cyclic peptides that could bind at protein-protein interface regions and interfere with protein-protein binding (Schreiber and Crabtree, 1992 ; Dechantsreiter et al, 1999 ; Sulyok et al, 2001 ; Shi et al, 2004 ; Zhang et al, 2014 ; Siegert et al, 2016 ; Shin et al, 2017 ). Identification of potential appropriate cyclic peptides can be achieved using techniques used in small-molecule drug design efforts such as virtual screening and pharmacophore matching approaches (Zhang et al, 2014 ; Duffy et al, 2015 ; Qian et al, 2017 ). In this study, we propose a straight forward automated process for the rapid search and optimization of cyclic peptides as protein-protein interaction inhibitors based on known structures of cyclic peptides.…”

Lessons for Oral Bioavailability: How Conformationally Flexible Cyclic Peptides Enter and Cross Lipid Membranes

“…[10][11][12] In comparison to small-molecules, macrocyclic compounds hold the potential to vastly extend the scope of druggable proteins. Due to their ability to target larger binding sites with flat profiles, [4,[13][14][15][16][17] like protein-protein interaction (PPI) interfaces, [18][19][20] they can lead to new therapeutics for currently untreatable diseases. However, high binding affinity to a target is not enough for a molecule to be pharmaceutically relevant.…”