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Curr Opin Struct Biol. 2019 Jun;56:11-17. doi: 10.1016/j.sbi.2018.10.007. Epub 2018 Nov 12.

Developments in integrative modeling with dynamical interfaces.

Author information

1
Department of Chemical and Biological Engineering, Koc University, Istanbul 34450, Turkey.
2
Cancer and Inflammation Program, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, National Cancer Institute at Frederick, Frederick, MD 21702, USA; Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel.
3
Department of Computer Engineering, Koc University, Istanbul 34450, Turkey; Research Center for Translational Medicine, Koc University, Istanbul 34450, Turkey. Electronic address: agursoy@ku.edu.tr.
4
Department of Chemical and Biological Engineering, Koc University, Istanbul 34450, Turkey; Research Center for Translational Medicine, Koc University, Istanbul 34450, Turkey. Electronic address: okeskin@ku.edu.tr.

Abstract

Proteins are dynamic, and this holds especially for their surfaces. They display ensembles of conformations, which allows them to interact with diverse partners, often via the same patch of surface, and execute their distinct functions. Binding a specific partner can stimulate - or suppress - a distinct signaling pathway. This diversity poses a challenge: how to reliably model a specific protein-protein interaction (PPI)? This problem is compounded in protein assemblies, which are typically large, involving multiple protein-protein interfaces. Integrative modeling (IM), which combines diverse data, has emerged as the most promising strategy; however, modeling dynamical interfaces, often at the detailed level, which are at the heart of reliable predictions of assemblies, still poses a challenge. Here we review hurdles and advances in integrative modeling of dynamical interfaces; while some could have been predicted or expected, others transformed modeling in unanticipated ways. We further comment on what we believe could be possible future advances.

PMID:
30439586
DOI:
10.1016/j.sbi.2018.10.007

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