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Devocelle, Marc
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Devocelle, Marc
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Devocelle, Marc
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Now showing 1 - 3 of 3
- PublicationCycloPs : generating virtual libraries of cyclized and constrained peptides including nonnatural amino acids(ACS Publications, 2011-03-24)
; ; ; ; ; We introduce CycloPs, software for the generation of virtual libraries of constrained peptides including natural and nonnatural commercially available amino acids. The software is written in the cross-platform Python programming language, and features include generating virtual libraries in one-dimensional SMILES and three-dimensional SDF formats, suitable for virtual screening. The stand-alone software is capable of filtering the virtual libraries using empirical measurements, including peptide synthesizability by standard peptide synthesis techniques, stability, and the druglike properties of the peptide. The software and accompanying Web interface is designed to enable the rapid generation of large, structurally diverse, synthesizable virtual libraries of constrained peptides quickly and conveniently, for use in virtual screening experiments. The stand-alone software, and the Web interface for evaluating these empirical properties of a single peptide, are available at http://bioware.ucd.ie.2623Scopus© Citations 36 - PublicationComputational Approaches to Developing Short Cyclic Peptide Modulators of Protein-Protein InteractionsCyclic peptides are a promising class of bioactive molecules potentially capable of modulating 'difficult' targets, such as protein–protein interactions. Cyclic peptides have long been used as therapeutics derived from natural product derivatives, but remain an underexplored class of compounds from the perspective of rational drug design, possibly due to the known weaknesses of peptide drugs in general. While cyclic peptides are non 'druglike' by the accepted empirical rules, their unique structure may lend itself to both membrane permeability and proteolytic resistance—the main barriers to oral delivery. The constrained shape of cyclic peptides also lends itself better to virtual screening approaches, and new tools and successes in this area have been recently noted. An increasing number of strategies are available, both to generate and screen cyclic peptide libraries, and best practises and current successes are described within. This chapter will describe various computational strategies for virtual screening cyclic peptides, along with known implementations and applications. We will explore the generation and screening of diverse combinatorial virtual libraries, incorporating a range of cyclization strategies and structural modifications. More advanced approaches covered include evolutionary algorithms designed to aid in screening large structural libraries, machine learning approaches, and harnessing bioinformatics resources to bias cyclic peptide virtual libraries towards known bioactive structures.
Scopus© Citations 13 1342 - PublicationVirtual Screening Using Combinatorial Cyclic Peptide Libraries Reveals Protein Interfaces Readily Targetable by Cyclic Peptides(American Chemical Society, 2015-02-10)
; ; ; ; ; 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.1041Scopus© Citations 12