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Enzyme–enzyme interactions are fundamental to the function of cells. Their atomistic mechanisms remain elusive mainly due to limitations of in-cell measurements. We address this challenge by atomistically modeling, for a total of ≈80 μs, a slice of the human cell cytoplasm that includes three successive enzymes along the glycolytic pathway: glyceraldehyde-3-phosphate dehydrogenase (GAPDH), phosphoglycerate kinase (PGK), and phosphoglycerate mutase (PGM). We tested the model for nonspecific protein stickiness, an artifact of current atomistic force fields in crowded environments. The simulations reveal that the human enzymes co-organize in-cell into transient submetabolon complexes, consistent with previous experimental results. Our data both reiterate known specificity between GAPDH and PGK and reveal extensive direct interactions between GAPDH and PGM. Our simulations further reveal, through force field benchmarking, the critical role of protein solvation in facilitating these enzyme–enzyme interactions. Transient interenzyme interactions with μs lifetime occur repeatedly in our simulations via specific sticky protein surface patches, with interactions often mediated by charged patch residues. Some of the residues that interact frequently with one another lie in or near the active site of the enzymes. We show that some of these patches correspond to a general mode to interact with several partners for promiscuous enzymes like GAPDH. We further show that the non-native yeast PGK is stickier than human PGK in our human cytoplasm model, supporting the idea of evolutionary pressure to reduce sticking. Our cytoplasm modeling paves the way toward capturing the atomistic dynamics of an entire enzymatic pathway in-cell. 

Protein–protein and protein–water hydrogen bonding interactions play essential roles in the way a protein passes through the transition state during folding or unfolding, but the large number of these interactions in molecular dynamics (MD) simulations makes them difficult to analyze. Here, we introduce a state space representation and associated “rarity” measure to identify and quantify transition state passage (transit) events. Applying this representation to a long MD simulation trajectory that captured multiple folding and unfolding events of the GTT WW domain, a small protein often used as a model for the folding process, we identified three transition categories: Highway (faster), Meander (slower), and Ambiguous (intermediate). We developed data sonification and visualization tools to analyze hydrogen bond dynamics before, during, and after these transition events. By means of these tools, we were able to identify characteristic hydrogen bonding patterns associated with “Highway” versus “Meander” versus “Ambiguous” transitions and to design algorithms that can identify these same folding pathways and critical protein–water interactions directly from the data. Highly cooperative hydrogen bonding can either slow down or speed up transit. Furthermore, an analysis of protein–water hydrogen bond dynamics at the surface of WW domain shows an increase in hydrogen bond lifetime from folded to unfolded conformations with Ambiguous transitions as an outlier. In summary, hydrogen bond dynamics provide a direct window into the heterogeneity of transits, which can vary widely in duration (by a factor of 10) due to a complex energy landscape. 

Abstract A high‐resolution ocean model is used to characterize the variability of the shelf circulation and cross‐shelf transport around the South Georgia island (SG). The time‐mean shelf circulation consists of a counterclockwise flow with a net onshelf mass flow in the south and a net offshelf mass flow in the north. In the south, the cross‐shelf exchanges show a two‐layer structure with an offshelf flow below 350 m and onshelf flow above. In the north, the cross‐shelf exchanges show a three‐layer structure with the onshelf flow found only between 350 and 50 m. Correlation analysis shows that winds and the Southern Antarctic Circumpolar Current Front (SACCF) current modulate the variability of the shelf circulation and cross‐shelf transport. Local wind stress is significantly correlated with the coastal currents, mid‐shelf jet, and cross‐shelf transports in the upper layer, while the SACCF modulates the shelf and cross‐shelf transports in the southwestern shelf. Likewise, an Empirical Orthogonal Function analysis indicates that the first mode of shelf circulation variability is highly correlated with the SACCF, while the second mode is explained by the local wind stress and significantly correlated with the Antarctic Oscillation. The El Niño Southern Oscillation does not significantly contribute to the shelf circulation but is significantly correlated with the surface temperature variability. The atmospheric teleconnection drives changes in local heat flux, such that warm El Niño conditions over the equatorial Pacific are associated with a cooling of the SG waters. This superposes local signals onto temperature anomalies advected from upstream in the ACC found in previous studies.