pyProGA-A PyMOL plugin for protein residue network analysis

PLoS One. 2021 Jul 30;16(7):e0255167. doi: 10.1371/journal.pone.0255167. eCollection 2021.

Abstract

The field of protein residue network (PRN) research has brought several useful methods and techniques for structural analysis of proteins and protein complexes. Many of these are ripe and ready to be used by the proteomics community outside of the PRN specialists. In this paper we present software which collects an ensemble of (network) methods tailored towards the analysis of protein-protein interactions (PPI) and/or interactions of proteins with ligands of other type, e.g. nucleic acids, oligosaccharides etc. In parallel, we propose the use of the network differential analysis as a method to identify residues mediating key interactions between proteins. We use a model system, to show that in combination with other, already published methods, also included in pyProGA, it can be used to make such predictions. Such extended repertoire of methods allows to cross-check predictions with other methods as well, as we show here. In addition, the possibility to construct PRN models from various kinds of input is so far a unique asset of our code. One can use structural data as defined in PDB files and/or from data on residue pair interaction energies, either from force-field parameters or fragment molecular orbital (FMO) calculations. pyProGA is a free open-source software available from https://gitlab.com/Vlado_S/pyproga.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Amino Acids / analysis*
  • Protein Interaction Maps*
  • Proteins / chemistry*
  • Software*

Substances

  • Amino Acids
  • Proteins

Grants and funding

This research was supported by the Slovak Research and Development Agency (APVV, https://www.apvv.sk/?lang=en) in the form of a grant awarded to VS (APVV-19-0376), the Scientific Grant Agency of the Ministry of Education, Science, Research and Sport of the Slovak Republic and The Slovak Academy of Sciences (VEGA, https://www.minedu.sk/vedecka-grantova-agentura-msvvas-sr-a-sav-vega/) in the form of grants awarded to VS (VEGA-2/0031/19, VEGA-2/0061/20), the MEXT Quantum Leap Flagship Program (MEXT Q-LEAP, https://www.jst.go.jp/stpp/q-leap/en/index.html) in the form of a grant awarded to YS (JPMXS0120330644), and in part by the Japan Agency for Medical Research and Development (AMED, https://www.amed.go.jp/en/) in the form of a grant awarded to YS (JP20ae0101047h0001). Part of the calculations were done at the Computing Center of SAS using the infrastructure from Project Nos. ITMS 26230120002 and 26210120002, supported by the Research and Development Operational Program funded by the ERDF. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.