Proteins must fold into their native structure and maintain it during their lifespan to display the desired activity. To ensure proper folding and stability, and avoid generation of misfolded conformations that can be potentially cytotoxic, cells synthesize a wide variety of molecular chaperones that assist folding of other proteins and avoid their aggregation, which unfortunately is unavoidable under acute stress conditions. A protein machinery in metazoa, composed of representatives of the Hsp70, Hsp40, and Hsp110 chaperone families, can reactivate protein aggregates. We revised herein the phosphorylation sites found so far in members of these chaperone families and the functional consequences associated with some of them. We also discuss how phosphorylation might regulate the chaperone activity and the interaction of human Hsp70 with its accessory and client proteins. Finally, we present the information that would be necessary to decrypt the effect that post-translational modifications, and especially phosphorylation, could have on the biological activity of the Hsp70 system, known as the “chaperone code”.

With a large amount of research dedicated to decoding how metallic species bind to protein, in silico methods are interesting allies for experimental procedures. To date, computational predictors mostly work by identifying the best possible sequence or structural match of the target protein with metal binding templates.These approaches are fundamentally focused on the first coordination sphere of the metal. Here, we present the BioMetAll predictor that is based on a different postulate: the formation of a potential metal-binding site is related to the geometric organization of the protein backbone. We first report the set of convenient geometric descriptors of the backbone needed for the algorithm and their parametrization from a statistical analysis.Then, the successful benchmark of BioMetAll on a set of more than 50 metal-binding X-Ray structures is presented. Because BioMetAll allows structural predictions regardless of the exact geometry of the side chains, it appears extremely valuable for systems which structures (either experimental or theoretical) are not optimal for metal binding sites. We report here its application on three different challenging cases i) the modulation of metal-binding sites during conformational transition in human serum albumin, ii) the identification of possible routes of metal migration in hemocyanins, and iii) the prediction of mutations to generate convenient metal-binding sites for de novo biocatalysts. This study shows that BioMetAll offers a versatile platform for numerous fields of research at the interface between inorganic chemistry and biology, and allows to highlight the role of the preorganization of the protein backbone as a marker for metal binding. File list (2)download file view on ChemRxiv BioMetAll.pdf (20.92 MiB) download file view on ChemRxiv BioMetAll_SI.pdf (5.62 MiB)

<p>OpenMM is a free and GPU-accelerated Molecular Dynamics (MD) engine written as a layered and reusable library. This approach allows maximum flexibility to configure MD simulations and develop new molecular mechanics (MM) methods. However, this powerful versatility comes at a cost: the user is expected to write Python scripts to run a simulation. OMMProtocol aims to fill this gap by stitching OpenMM and additional third-party modules together, providing an easy way to create an input file to configure a full multi-stage simulation protocol, from minimization to equilibration and production. OMMProtocol is LGPL-licensed and freely available at <a href="https://github.com/insilichem/ommprotocol">https://github.com/insilichem/ommprotocol</a>. </p>