Use of fast conformational sampling to improve the characterization of VEGF A–peptide interactions

Abstract

Protein–peptide interaction is fundamentally important for signal transduction, transcription regulation, protein degradation, cell regeneration, and immune response. Here, we report the use of a fast conformational sampling strategy to improve the prediction of protein–peptide binding affinity. This method generates hundreds of alternative conformers for a protein–peptide complex and then performs classical MM-PB/SA analysis over these conformers to derive a consistent binding energy expression for the complex. We show a proof-of-concept study on vascular endothelial growth factor A (VEGF A) interaction with its peptide ligands. The structures of VEGF A complexed with 13 peptides are modeled with a virtual mutagenesis protocol and their binding energies are subsequently calculated by using the conformational sampling-based method. A good linear correlation between the calculated and experimental values is observed, and we demonstrate that the correlation could be further improved by fitting the decomposed energy terms to experimentally measured affinity. Furthermore, the obtained results are discussed in detail in order to elucidate the structural basis and energetic implication underlying VEGF A–peptide recognition and association. We also give a detailed comparison between the proposed method and other widely used approaches, from which it is suggested that our method exhibits a good compromise between the effectiveness and efficiency in evaluating protein–peptide affinity.