Abstract
Protein–peptide interactions (PpIs) are a subset of the overall protein–protein interaction (PPI) network in the living cell and are pivotal for the majority of cell processes and functions. High-throughput methods to detect PpIs and PPIs usually require time and costs that are not always affordable. Therefore, reliable in silico predictions represent a valid and effective alternative. In this work, a new algorithm is described, implemented in a freely available tool, i.e., “PepThreader”, to carry out PPIs and PpIs prediction and analysis. PepThreader threads multiple fragments derived from a full-length protein sequence (or from a peptide library) onto a second template peptide, in complex with a protein target, “spotting” the potential binding peptides and ranking them according to a sequence-based and structure-based threading score. The threading algorithm first makes use of a scoring function that is based on peptides sequence similarity. Then, a rerank of the initial hits is performed, according to structure-based scoring functions. PepThreader has been benchmarked on a dataset of 292 protein–peptide complexes that were collected from existing databases of experimentally determined protein–peptide interactions. An accuracy of 80%, when considering the top predicted 25 hits, was achieved, which performs in a comparable way with the other state-of-art tools in PPIs and PpIs modeling. Nonetheless, PepThreader is unique in that it is able at the same time to spot a binding peptide within a full-length sequence involved in PPI and model its structure within the receptor. Therefore, PepThreader adds to the already-available tools supporting the experimental PPIs and PpIs identification and characterization.
Highlights
Protein functions are primarily based on their ability to establish interactions both with other proteins and other biomolecules [1,2,3,4]
Experimental methods used to investigate protein–peptide interactions (PpIs) are similar to those used in protein–protein interaction (PPI) studies and can be divided into three main classes: atomic-resolution approaches, mass spectrometry [9,10], and other biochemical/biophysical methods [11,12,13,14]
The rate limiting step of in vitro PPIs and PpIs characterization is often the expression and purification of proteins involved in the interaction: many are insoluble
Summary
Protein functions are primarily based on their ability to establish interactions both with other proteins and other biomolecules [1,2,3,4]. Since protein–protein interactions (PPIs) play a key role in cell complexity and functionality, there is considerable interest in this field and, as a consequence, an ever-increasing availability of different methods and approaches for such studies. Experimental methods used to investigate protein–peptide interactions (PpIs) are similar to those used in PPIs studies and can be divided into three main classes: atomic-resolution approaches (crystallography [5,6], NMR [7], cryo-EM [8]), mass spectrometry [9,10], and other biochemical/biophysical methods [11,12,13,14]. The use of peptide arrays [18], has boosted peptide-based studies. Such information, in turn, can be used for drug design purposes, e.g., to design peptide derivatives able to hamper the interactions of therapeutic targets, known as peptidomimetics [19].
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