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A new approach for extracting information from protein dynamics.
Liu, Jenny; Amaral, Luís A N; Keten, Sinan.
  • Liu J; Department of Mechanical Engineering, Northwestern University, Evanston, Illinois, USA.
  • Amaral LAN; Department of Civil and Environmental Engineering, Northwestern University, Evanston, USA.
  • Keten S; Northwestern Institute on Complex Systems, Northwestern University, Evanston, Illinois, USA.
Proteins ; 2022 Sep 12.
Article in English | MEDLINE | ID: covidwho-2242782
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.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal subject: Biochemistry Year: 2022 Document Type: Article Affiliation country: Prot.26421

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal subject: Biochemistry Year: 2022 Document Type: Article Affiliation country: Prot.26421