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PepPro: A Nonredundant Structure Data Set for Benchmarking Peptide-Protein Computational Docking.

Xianjin XuXiaoqin Zou
Published in: Journal of computational chemistry (2019)
We present a nonredundant benchmark, coined PepPro, for testing peptide-protein docking algorithms. Currently, PepPro contains 89 nonredundant experimentally determined peptide-protein complex structures, with peptide sequence lengths ranging from 5 to 30 amino acids. The benchmark covers peptides with distinct secondary structures, including helix, partial helix, a mixture of helix and β-sheet, β-sheet formed through binding, β-sheet formed through self-folding, and coil. In addition, unbound proteins' structures are provided for 58 complexes and can be used for testing the ability of a docking algorithm handling the conformational changes of proteins during the binding process. PepPro should benefit the docking community for the development and improvement of peptide docking algorithms. The benchmark is available at http://zoulab.dalton.missouri.edu/PepPro_benchmark. © 2019 Wiley Periodicals, Inc.
Keyphrases
  • protein protein
  • molecular dynamics simulations
  • molecular dynamics
  • amino acid
  • small molecule
  • machine learning
  • dna binding
  • high resolution
  • binding protein
  • deep learning
  • healthcare
  • artificial intelligence