Conformational diversity analysis reveals three functional mechanisms in proteins

PLoS Comput Biol. 2017 Feb 13;13(2):e1005398. doi: 10.1371/journal.pcbi.1005398. eCollection 2017 Feb.

Abstract

Protein motions are a key feature to understand biological function. Recently, a large-scale analysis of protein conformational diversity showed a positively skewed distribution with a peak at 0.5 Å C-alpha root-mean-square-deviation (RMSD). To understand this distribution in terms of structure-function relationships, we studied a well curated and large dataset of ~5,000 proteins with experimentally determined conformational diversity. We searched for global behaviour patterns studying how structure-based features change among the available conformer population for each protein. This procedure allowed us to describe the RMSD distribution in terms of three main protein classes sharing given properties. The largest of these protein subsets (~60%), which we call "rigid" (average RMSD = 0.83 Å), has no disordered regions, shows low conformational diversity, the largest tunnels and smaller and buried cavities. The two additional subsets contain disordered regions, but with differential sequence composition and behaviour. Partially disordered proteins have on average 67% of their conformers with disordered regions, average RMSD = 1.1 Å, the highest number of hinges and the longest disordered regions. In contrast, malleable proteins have on average only 25% of disordered conformers and average RMSD = 1.3 Å, flexible cavities affected in size by the presence of disordered regions and show the highest diversity of cognate ligands. Proteins in each set are mostly non-homologous to each other, share no given fold class, nor functional similarity but do share features derived from their conformer population. These shared features could represent conformational mechanisms related with biological functions.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Models, Chemical*
  • Models, Statistical*
  • Molecular Dynamics Simulation*
  • Protein Conformation*
  • Proteins / chemistry*
  • Proteins / ultrastructure*
  • Structure-Activity Relationship

Substances

  • Proteins

Grants and funding

Funding for this research was provided by COST Action (BM1405) Non-Globular Proteins-net (SCET) and Universidad Nacional de Quilmes (PUNQ 1004/11) (GP). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.