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Hierarchical organization of eglin c native state dynamics is shaped by competing direct and water-mediated interactions.

ABSTRACT: The native state dynamics of the small globular serine protease inhibitor eglin c has been studied in a long 336 ns computer simulation in explicit solvent. We have elucidated the energy landscape explored during the course of the simulation by using Principal Component Analysis. We observe several basins in the energy landscape in which the system lingers for extended periods. Through an iterative process we have generated a tree-like hierarchy of states describing the observed dynamics. We observe a range of divergent contact types including salt bridges, hydrogen bonds, hydrophilic interactions, and hydrophobic interactions, pointing to the frustration between competing interactions. Additionally, we find evidence of competing water-mediated interactions. Divergence in water-mediated interactions may be found to supplement existing direct contacts, but they are also found to be independent of such changes. Water-mediated contacts facilitate interactions between residues of like charge as observed in the simulation. Our results provide insight into the complexity of the dynamic native state of a globular protein and directly probe the residual frustration in the native state.

SUBMITTER: Materese CK

PROVIDER: S-EPMC2504818 | biostudies-literature | 2008 Aug

REPOSITORIES: biostudies-literature

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Hierarchical organization of eglin c native state dynamics is shaped by competing direct and water-mediated interactions.

Materese Christopher Kroboth CK Goldmon Christa Charisse CC Papoian Garegin A GA

Proceedings of the National Academy of Sciences of the United States of America 20080729 31

The native state dynamics of the small globular serine protease inhibitor eglin c has been studied in a long 336 ns computer simulation in explicit solvent. We have elucidated the energy landscape explored during the course of the simulation by using Principal Component Analysis. We observe several basins in the energy landscape in which the system lingers for extended periods. Through an iterative process we have generated a tree-like hierarchy of states describing the observed dynamics. We obs ...[more]

PMID: 18664578

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Project description:We propose a new computational method for exploring chromatin structural organization based on Markov State Modelling of Hi-C data represented as an interaction network between genomic loci. A Markov process describes the random walk of a traveling probe in the corresponding energy landscape, mimicking the motion of a biomolecule involved in chromatin function. By studying the metastability of the associated Markov State Model upon annealing, the hierarchical structure of individual chromosomes is observed, and corresponding set of structural partitions is identified at each level of hierarchy. Then, the notion of effective interaction between partitions is derived, delineating the overall topology and architecture of chromosomes. Mapping epigenetic data on the graphs of intra-chromosomal effective interactions helps in understanding how chromosome organization facilitates its function. A sketch of whole-genome interactions obtained from the analysis of 539 partitions from all 23 chromosomes, complemented by distributions of gene expression regulators and epigenetic factors, sheds light on the structure-function relationships in chromatin, delineating chromosomal territories, as well as structural partitions analogous to topologically associating domains and active / passive epigenomic compartments. In addition to the overall genome architecture shown by effective interactions, the affinity between partitions of different chromosomes was analyzed as an indicator of the degree of association between partitions in functionally relevant genomic interactions. The overall static picture of whole-genome interactions obtained with the method presented in this work provides a foundation for chromatin structural reconstruction, for the modelling of chromatin dynamics, and for exploring the regulation of genome function. The algorithms used in this study are implemented in a freely available Python package ChromaWalker (https://bitbucket.org/ZhenWahTan/chromawalker).

Project description:The design of stable formulations remains a major challenge for protein therapeutics, particularly the need to minimize aggregation. Experimental formulation screens are typically based on thermal transition midpoints (Tm), and forced degradation studies at elevated temperatures. Both approaches give limited predictions of long-term storage stability, particularly at low temperatures. Better understanding of the mechanisms of action for formulation of excipients and buffers could lead to improved strategies for formulation design. Here, we identified a complex impact of glycine concentration on the experimentally determined stability of an antibody Fab fragment and then used molecular dynamics simulations to reveal mechanisms that underpin these complex behaviors. Tm values increased monotonically with glycine concentration, but associated ΔSvh measurements revealed more complex changes in the native ensemble dynamics, which reached a maximum at 30 mg/mL. The aggregation kinetics at 65 °C were similar at 0 and 20 mg/mL glycine, but then significantly slower at 50 mg/mL. These complex behaviors indicated changes in the dominant stabilizing mechanisms as the glycine concentration was increased. MD revealed a complex balance of glycine self-interaction, and differentially preferred interactions of glycine with the Fab as it displaced hydration-shell water, and surface-bound water and citrate buffer molecules. As a result, glycine binding to the Fab surface had different effects at different concentrations, and led from preferential interactions at low concentrations to preferential exclusion at higher concentrations. During preferential interaction, glycine displaced water from the Fab hydration shell, and a small number of water and citrate molecules from the Fab surface, which reduced the protein dynamics as measured by root-mean-square fluctuation (RMSF) on the short time scales of MD. By contrast, the native ensemble dynamics increased according to ΔSvh, suggesting increased conformational changes on longer time scales. The aggregation kinetics did not change at low glycine concentrations, and so the opposing dynamics effects either canceled out or were not directly relevant to aggregation. During preferential exclusion at higher glycine concentrations, glycine could only bind to the Fab surface through the displacement of citrate buffer molecules already favorably bound on the Fab surface. Displacement of citrate increased the flexibility (RMSF) of the Fab, as glycine formed fewer bridging hydrogen bonds to the Fab surface. Overall, the slowing of aggregation kinetics coincided with reduced flexibility in the Fab ensemble at the very highest glycine concentrations, as determined by both RMSF and ΔSvh, and occurred at a point where glycine binding displaced neither water nor citrate. These final interactions with the Fab surface were driven by mass action and were the least favorable, leading to a macromolecular crowding effect under the regime of preferential exclusion that stabilized the dynamics of Fab.

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Hierarchical organization of eglin c native state dynamics is shaped by competing direct and water-mediated interactions.

Publications

Hierarchical organization of eglin c native state dynamics is shaped by competing direct and water-mediated interactions.

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