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Protein Interaction Z Score Assessment (PIZSA): an empirical scoring scheme for evaluation of protein-protein interactions. | LitMetric

AI Article Synopsis

  • - PIZSA is a web server that evaluates protein-protein interactions by using a Z Score based on contact between residue interfaces, factoring in the type of atomic interactions involved.
  • - When tested against 174 native interactions and 100 decoys each, PIZSA significantly outperformed these decoys, ranking within the 95th percentile in most cases, and its performance was comparable to a competing method called CIPS.
  • - The server is user-friendly, allows the analysis of complex protein interactions without specifying roles, and offers the option for users to upload their own scoring potentials.

Article Abstract

Our web server, PIZSA (http://cospi.iiserpune.ac.in/pizsa), assesses the likelihood of protein-protein interactions by assigning a Z Score computed from interface residue contacts. Our score takes into account the optimal number of atoms that mediate the interaction between pairs of residues and whether these contacts emanate from the main chain or side chain. We tested the score on 174 native interactions for which 100 decoys each were constructed using ZDOCK. The native structure scored better than any of the decoys in 146 cases and was able to rank within the 95th percentile in 162 cases. This easily outperforms a competing method, CIPS. We also benchmarked our scoring scheme on 15 targets from the CAPRI dataset and found that our method had results comparable to that of CIPS. Further, our method is able to analyse higher order protein complexes without the need to explicitly identify chains as receptors or ligands. The PIZSA server is easy to use and could be used to score any input three-dimensional structure and provide a residue pair-wise break up of the results. Attractively, our server offers a platform for users to upload their own potentials and could serve as an ideal testing ground for this class of scoring schemes.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6602501PMC
http://dx.doi.org/10.1093/nar/gkz368DOI Listing

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