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finDr: A web server for in silico D-peptide ligand identification

In the rapidly expanding field of peptide therapeutics, the short in vivo half-life of peptides represents a considerable limitation for drug action. D-peptides, consisting entirely of the dextrorotatory enantiomers of naturally occurring levorotatory amino acids (AAs), do not suffer from these shor...

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Detalles Bibliográficos
Autores principales: Engel, Helena, Guischard, Felix, Krause, Fabian, Nandy, Janina, Kaas, Paulina, Höfflin, Nico, Köhn, Maja, Kilb, Normann, Voigt, Karsten, Wolf, Steffen, Aslan, Tahira, Baezner, Fabian, Hahne, Salomé, Ruckes, Carolin, Weygant, Joshua, Zinina, Alisa, Akmeriç, Emir Bora, Antwi, Enoch B., Dombrovskij, Dennis, Franke, Philipp, Lesch, Klara L., Vesper, Niklas, Weis, Daniel, Gensch, Nicole, Di Ventura, Barbara, Öztürk, Mehmet Ali
Formato: Online Artículo Texto
Lenguaje:English
Publicado: KeAi Publishing 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8632724/
https://www.ncbi.nlm.nih.gov/pubmed/34901479
http://dx.doi.org/10.1016/j.synbio.2021.11.004
Descripción
Sumario:In the rapidly expanding field of peptide therapeutics, the short in vivo half-life of peptides represents a considerable limitation for drug action. D-peptides, consisting entirely of the dextrorotatory enantiomers of naturally occurring levorotatory amino acids (AAs), do not suffer from these shortcomings as they are intrinsically resistant to proteolytic degradation, resulting in a favourable pharmacokinetic profile. To experimentally identify D-peptide binders to interesting therapeutic targets, so-called mirror-image phage display is typically performed, whereby the target is synthesized in D-form and L-peptide binders are screened as in conventional phage display. This technique is extremely powerful, but it requires the synthesis of the target in D-form, which is challenging for large proteins. Here we present finDr, a novel web server for the computational identification and optimization of D-peptide ligands to any protein structure (https://findr.biologie.uni-freiburg.de/). finDr performs molecular docking to virtually screen a library of helical 12-mer peptides extracted from the RCSB Protein Data Bank (PDB) for their ability to bind to the target. In a separate, heuristic approach to search the chemical space of 12-mer peptides, finDr executes a customizable evolutionary algorithm (EA) for the de novo identification or optimization of D-peptide ligands. As a proof of principle, we demonstrate the validity of our approach to predict optimal binders to the pharmacologically relevant target phenol soluble modulin alpha 3 (PSMα3), a toxin of methicillin-resistant Staphylococcus aureus (MRSA). We validate the predictions using in vitro binding assays, supporting the success of this approach. Compared to conventional methods, finDr provides a low cost and easy-to-use alternative for the identification of D-peptide ligands against protein targets of choice without size limitation. We believe finDr will facilitate D-peptide discovery with implications in biotechnology and biomedicine.