Predicting substitutions to modulate disorder and stability in coiled-coils.

Yasaman Karami, Paul Saighi, Rémy Vanderhaegen, Denis Gerlier, Sonia Longhi, Elodie Laine, Alessandra Carbone

Journal: BMC bioinformatics 2021;21(Suppl 19):573

PMID: 33349244

Abstract

BACKGROUND

Coiled-coils are described as stable structural motifs, where two or more helices wind around each other. However, coiled-coils are associated with local mobility and intrinsic disorder. Intrinsically disordered regions in proteins are characterized by lack of stable secondary and tertiary structure under physiological conditions in vitro. They are increasingly recognized as important for protein function. However, characterizing their behaviour in solution and determining precisely the extent of disorder of a protein region remains challenging, both experimentally and computationally.

RESULTS

In this work, we propose a computational framework to quantify the extent of disorder within a coiled-coil in solution and to help design substitutions modulating such disorder. Our method relies on the analysis of conformational ensembles generated by relatively short all-atom Molecular Dynamics (MD) simulations. We apply it to the phosphoprotein multimerisation domains (PMD) of Measles virus (MeV) and Nipah virus (NiV), both forming tetrameric left-handed coiled-coils. We show that our method can help quantify the extent of disorder of the C-terminus region of MeV and NiV PMDs from MD simulations of a few tens of nanoseconds, and without requiring an extensive exploration of the conformational space. Moreover, this study provided a conceptual framework for the rational design of substitutions aimed at modulating the stability of the coiled-coils. By assessing the impact of four substitutions known to destabilize coiled-coils, we derive a set of rules to control MeV PMD structural stability and cohesiveness. We therefore design two contrasting substitutions, one increasing the stability of the tetramer and the other increasing its flexibility.

CONCLUSIONS

Our method can be considered as a platform to reason about how to design substitutions aimed at regulating flexibility and stability.

Address: CNRS, IBPS, UMR 7238, Laboratoire de Biologie Computationnelle et Quantitative (LCQB), Sorbonne Université, 75005, Paris, France. [email protected].; Institute of Computing and Data Sciences (ISCD), Sorbonne Université, 75005, Paris, France. [email protected].; CNRS, IBPS, UMR 7238, Laboratoire de Biologie Computationnelle et Quantitative (LCQB), Sorbonne Université, 75005, Paris, France.; CIRI, International Center for Infectiology Research, INSERM, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, Ecole Normale Supérieure de Lyon, Univ Lyon, Lyon, France.; CNRS, Architecture et Fonction des Macromolécules Biologiques (AFMB), UMR 7257, Aix-Marseille University, Marseille, France.; CNRS, IBPS, UMR 7238, Laboratoire de Biologie Computationnelle et Quantitative (LCQB), Sorbonne Université, 75005, Paris, France. [email protected].; CNRS, IBPS, UMR 7238, Laboratoire de Biologie Computationnelle et Quantitative (LCQB), Sorbonne Université, 75005, Paris, France. [email protected].; Institut Universitaire de France, 75005, Paris, France. [email protected].
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