Visualization of large molecular trajectories

The analysis of protein-ligand interactions is a time-intensive task. Researchers have to analyze multiple physico-chemical properties of the protein at once and combine them to derive conclusions about the protein-ligand interplay. Typically, several charts are inspected, and 3D animations can be played side-by-side to obtain a deeper understanding of the data. With the advances in simulation techniques, larger and larger datasets are available, with up to hundreds of thousands of steps. Unfortunately, such large trajectories are very difficult to investigate with traditional approaches. Therefore, the need for special tools that facilitate inspection of these large trajectories becomes substantial. In this paper, we present a novel system for visual exploration of very large trajectories in an interactive and user-friendly way. Several visualization motifs are automatically derived from the data to give the user the information about interactions between protein and ligand. Our system offers specialized widgets to ease and accelerate data inspection and navigation to interesting parts of the simulation. The system is suitable also for simulations where multiple ligands are involved. We have tested the usefulness of our tool on a set of datasets obtained from protein engineers, and we describe the expert feedback.Peer ReviewedPostprint (author's final draft

Adaptive Steered Molecular Dynamics Combined With Protein Structure Networks Revealing the Mechanism of Y68I/G109P Mutations That Enhance the Catalytic Activity of D-psicose 3-Epimerase From Clostridium Bolteae

The scarcity, richness, and other important physiological functions of D-psicose make it crucial to increase the yield of D-psicose. The production of D-psicose can be accomplished by D-psicose 3-epimerase (DPEase) from Clostridium bolteae (CbDPEase) catalyzing the substrate D-fructose. Although the catalytic efficiency of the CbDPEase has been raised via using the site-directed mutagenesis (Y68I/G109P) technique, structure-activity relationship in the wild-type CbDPEase and Y68I/G109P mutant is currently poorly understood. In our study, a battery of molecular modeling methods [homology modeling, adaptive steered molecular dynamics (ASMD) simulations, and Molecular Mechanics/Generalized Born Surface Area (MM-GB/SA)], combined with protein structure networks, were employed to theoretically characterize the reasons for the differences in the abilities of the D-fructose catalyzed by the wild-type CbDPEase and Y68I/G109P mutant. Protein structure networks demonstrated that site-directed mutagenesis enhanced the connectivity between D-fructose and CbDPEase, leading to the increased catalytic efficiency mediated by the functional residues with high betweenness. During the dissociation of the D-fructose from the Y68I/G109P mutant, planes of benzene rings of F248 and W114 could be continuously parallel to the stretching direction of D-fructose. It made the tunnel have an open state and resulted in the stable donor-π interactions between D-fructose and the benzene rings around 18Å. The stronger substrate-protein interactions were detected in the Y68I/G109P mutant, instead of in the wild-type CbDPEase, which were consistent with the binding free energy and Potential Mean of Force (PMF) results. The theoretical results illustrated the reasons that Y68I/G109P mutations increased the catalytic efficiency of CbDPEase and could be provided the new clue for further DPEase engineering