4.6 Article

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

Journal

SYNTHETIC AND SYSTEMS BIOTECHNOLOGY
Volume 6, Issue 4, Pages 402-413

Publisher

KEAI PUBLISHING LTD
DOI: 10.1016/j.synbio.2021.11.004

Keywords

D-peptide; Web server; Evolutionary algorithm; Peptide design; Molecular docking; Mirror-image phage display

Funding

  1. High Performance and Cloud Computing Group at the Zentrum fur Datenverarbeitung of the University of Tubingen
  2. state of Baden-Wurttemberg through bwHPC
  3. German Research Foundation (Deutsche Forschungsgemeinschaft DFG) [INST 37/935-1 FUGG]
  4. CIBSS -Centre for Integrative Biological Signalling Studies/BIOSS -Centre for Biological Signalling Studies (University of Freiburg)
  5. Student deanery (Studiendekanat) Molecular Medicine (University of Freiburg)
  6. Integrated DNA Technologies (IDT)
  7. Maria Ladenburger Stiftung (Freiburg, Germany)
  8. Friends of the University of Freiburg
  9. OFAMED Open Student Council Medicine (Offene Fachschaft Medizin e. V.) -University of Freiburg
  10. Neue Universitatsstiftung Freiburg
  11. Abcam
  12. Geneious
  13. Institute for Biochemistry (University of Freiburg)
  14. Thorsten Hugel Group (University of Freiburg)
  15. BioCopy GmbH (Emmendingen, Germany)
  16. Hahn-Schickard Institute (Freiburg, Germany)
  17. Zahnarztpraxis Thomas Ruckes (Germany)
  18. Merck Millipore
  19. New England Biolabs GmbH
  20. Zymo Research
  21. Carl Roth GmbH + Co. KG (Germany)
  22. Eurofins Scientific
  23. Faust Lab Science GmbH (Germany)
  24. Macherey-Nagel (Germany)
  25. Jena Bioscience (Germany)
  26. NIPPON Genetics Europe (Germany)
  27. GENEWIZ Europe -A Brooks Life Sciences Company (Germany)
  28. Institute for Biology III (University of Freiburg)
  29. Sparkasse Freiburg Nordlicher Breisgau (Germany)
  30. Greiner Bio-One
  31. La Luna Baila
  32. Faculty of Biology
  33. Dr. Falk Pharma GmbH (Freiburg, Germany)

Ask authors/readers for more resources

The use of D-peptides, composed of dextrorotatory enantiomers, offers improved stability and efficacy in peptide therapeutics. The web server finDr allows for the computational identification and optimization of D-peptide ligands to any protein structure, providing a tool for predicting optimal binders. This approach facilitates D-peptide discovery in biotechnology and biomedicine, presenting a cost-effective and user-friendly alternative to conventional methods.
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 (PSM alpha 3), 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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