Saighi, P. | bioRxiv Science

bioRxiv2021

DAVI: a tool for clustering and visualising protein domain architectures

The characterization of protein functions is one of the main challenges in bioinformatics. Proteins are often composed of individual units termed domains, motifs that can evolve independently. The domain architecture of a given protein is the particular order and the content of its numerous domains. Some computational approaches predict the most likely domain architecture for a set of proteins. However, a few numbers of visualization tools exist, and most of them are unavailable. Here we present DAVI, an efficient and user-friendly web server for protein domain architecture clustering and visualization. DAVI accepts the output of most used domain architecture prediction tools and also produces domain architectures for a set of protein sequences. It provides a rich visualization for comparing, analyzing, and visualizing domain architectures. Availabilityhttp://genome.lcqb.upmc.fr/Domain-Architecture-Viewer

bioinformatics↗

bioRxiv2020

Predicting substitutions to modulate disorder and stability in coiled-coils

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 (IDRs) 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. 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, without requiring the input MD trajectory to actually sample the unfolded states of these regions. 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. Consequently, our method can be considered as a platform to reason about how to design substitutions aimed at regulating flexibility and stability.

bioinformatics↗