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Ranking protein structure models is an elusive problem in bioinformatics. These models are evaluated on both the degree of similarity to the native structure and the folding pathway. Here, we simulated the use of the coarse-grained UNited RESidue (UNRES) force field as a tool to choose the best protein structure models for a given protein sequence among a pool of candidate models, using server data from the CASP11 experiment. Because the original UNRES was optimized for Molecular Dynamics simulations, we reoptimized UNRES using a deep feed-forward neural network, and we show that introducing additional descriptive features can produce better results. Overall, we found that the reoptimized UNRES performs better in selecting the best structures and tracking protein unwinding from its native state. We also found a relatively poor correlation between UNRES values and the model’s Template Modeling Score (TMS). This is remedied by reoptimization. We discuss some cases where our reoptimization procedure is useful. The reoptimized version of UNRES (OUNRES) is available at http://mamiris.com and http://www.unres.pl. 

The transition toward exascale computing will be accompanied by a performance dichotomy. Computational peak performance will rapidly increase; I/O performance will either grow slowly or be completely stagnant. Essentially, the rate at which data are generated will grow much faster than the rate at which data can be read from and written to the disk. MD simulations will soon face the I/O problem of efficiently writing to and reading from disk on the next generation of supercomputers. This article targets MD simulations at the exascale and proposes a novel technique forin situdata analysis and indexing of MD trajectories. Our technique maps individual trajectories' substructures (i.e.,α‐helices,β‐strands) to metadata frame by frame. The metadata captures the conformational properties of the substructures. The ensemble of metadata can be used for automatic, strategic analysis within a trajectory or across trajectories, without manually identify those portions of trajectories in which critical changes take place. We demonstrate our technique's effectiveness by applying it to 26.3k helices and 31.2k strands from 9917 PDB proteins and by providing three empirical case studies. © 2017 Wiley Periodicals, Inc.

 

The 70 kDa heat shock proteins (Hsp70) are a family of molecular chaperones involved in protein folding, aggregate prevention, and protein disaggregation. They consist of the substrate‐binding domain (SBD) that binds client substrates, and the nucleotide‐binding domain (NBD), whose cycles of nucleotide hydrolysis and exchange underpin the activity of the chaperone. To characterize the structure–function relationships that link the binding state of the NBD to its conformational behavior, we analyzed the dynamics of the NBD of the Hsp70 chaperone fromBos taurus(PDB 3C7N:B) by all‐atom canonical molecular dynamics simulations. It was found that essential motions within the NBD fall into three major classes: the mutual class, reflecting tendencies common to all binding states, and the ADP‐ and ATP‐unique classes, which reflect conformational trends that are unique to either the ADP‐ or ATP‐bound states, respectively. “Mutual” class motions generally describe “in‐plane” and/or “out‐of‐plane” (scissor‐like) rotation of the subdomains within the NBD. This result is consistent with experimental nuclear magnetic resonance data on the NBD. The “unique” class motions target specific regions on the NBD, usually surface loops or sites involved in nucleotide binding and are, therefore, expected to be involved in allostery and signal transmission. For all classes, and especially for those of the “unique” type, regions of enhanced mobility can be identified; these are termed “hot spots,” and their locations generally parallel those found by NMR spectroscopy. The presence of magnesium and potassium cations in the nucleotide‐binding pocket was also found to influence the dynamics of the NBD significantly. Proteins 2015; 83:282–299. © 2014 Wiley Periodicals, Inc.