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

Authors :
Paulina Kaas
Alisa Zinina
Tahira Aslan
Daniel Georg Weis
Philipp Franke
Nicole Gensch
Salomé Hahne
Fabian Baezner
Klara L. Lesch
Karsten Voigt
Emir Bora Akmeriç
Niklas Vesper
Enoch B. Antwi
Joshua Weygant
Felix Guischard
Mehmet Ali Öztürk
Helena Engel
Maja Köhn
Nico Höfflin
Dennis Dombrovskij
Janina Nandy
Fabian Krause
Barbara Di Ventura
Carolin Ruckes
Steffen Wolf
Normann Kilb
Source :
Synthetic and Systems Biotechnology, Vol 6, Iss 4, Pp 402-413 (2021)
Publication Year :
2021
Publisher :
KeAi Communications Co., Ltd., 2021.

Abstract

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.

Details

Language :
English
Volume :
6
Issue :
4
Database :
OpenAIRE
Journal :
Synthetic and Systems Biotechnology
Accession number :
edsair.doi.dedup.....4e6ecf5bc50095680a8f03599a60583d