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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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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
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author 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
author_facet 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
author_sort Engel, Helena
collection PubMed
description 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.
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spelling pubmed-86327242021-12-09 finDr: A web server for in silico D-peptide ligand identification 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 Synth Syst Biotechnol Article 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. KeAi Publishing 2021-11-23 /pmc/articles/PMC8632724/ /pubmed/34901479 http://dx.doi.org/10.1016/j.synbio.2021.11.004 Text en © 2021 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
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
finDr: A web server for in silico D-peptide ligand identification
title finDr: A web server for in silico D-peptide ligand identification
title_full finDr: A web server for in silico D-peptide ligand identification
title_fullStr finDr: A web server for in silico D-peptide ligand identification
title_full_unstemmed finDr: A web server for in silico D-peptide ligand identification
title_short finDr: A web server for in silico D-peptide ligand identification
title_sort findr: a web server for in silico d-peptide ligand identification
topic Article
url 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
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