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

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.

Virtual Screening of Peptide Libraries: The Search for Peptide-Based Therapeutics Using Computational Tools

“…finDr works similarly to a mirror-image phage display where the peptides are assayed in the L-configuration while the target is produced in the D-configuration. If an L-peptide interacts with the D-form of a protein, its mirror images (D-peptide) will be able to interact in a similar manner to the same natural protein in the L-configuration [54]. Starting from this concept, the virtual library employed by finDr consists of helical peptide fragments (12 amino acid long) extracted from Protein Data Bank (PDB) entries.…”

“…Such a library is screened against the chosen protein target in the D-configuration through Mirror-Image Virtual Screening (MIVS). This leads to a prediction by molecular-docking of L-peptide ligands, the configuration of which can be inverted to obtain D-peptides interacting with the naturally occurring L-protein [54].…”

Rational and Translational Implications of D-Amino Acids for Treatment-Resistant Schizophrenia: From Neurobiology to the Clinics

“…Despite limited clinical evidence, D-peptide therapeutics is a rapidly expanding field [ 404 ] offering multiple advantages, including low-cost synthesis, low immunogenicity, and serum stability compared to L-peptides analogues that are faster degraded in serum by active endopeptidase. Thus, D-peptides are currently designed and tested in preclinical research setting for a variety of medical conditions, including infections and cancer [ 405 , 406 , 407 ].…”