A new approach for extracting information from protein dynamics

Jenny Liu, Luís A.N. Amaral, Sinan Keten*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Increased ability to predict protein structures is moving research focus towards understanding protein dynamics. A promising approach is to represent protein dynamics through networks and take advantage of well-developed methods from network science. Most studies build protein dynamics networks from correlation measures, an approach that only works under very specific conditions, instead of the more robust inverse approach. Thus, we apply the inverse approach to the dynamics of protein dihedral angles, a system of internal coordinates, to avoid structural alignment. Using the well-characterized adhesion protein, FimH, we show that our method identifies networks that are physically interpretable, robust, and relevant to the allosteric pathway sites. We further use our approach to detect dynamical differences, despite structural similarity, for Siglec-8 in the immune system, and the SARS-CoV-2 spike protein. Our study demonstrates that using the inverse approach to extract a network from protein dynamics yields important biophysical insights.

Original languageEnglish (US)
Pages (from-to)183-195
Number of pages13
JournalProteins: Structure, Function and Bioinformatics
Volume91
Issue number2
DOIs
StatePublished - Feb 2023

Keywords

  • SARS-CoV-2
  • fimbrial adhesins
  • molecular dynamics simulation
  • protein
  • sialic acid binding immunoglobulin-like lectins

ASJC Scopus subject areas

  • Molecular Biology
  • Structural Biology
  • Biochemistry

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