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Noncovalent Interaction Analysis in Fluctuating Environments.

ABSTRACT: Noncovalent interactions play a central role in many chemical and biological systems. In a previous study, Johnson et al developed a NonCovalent Interaction (NCI) index to characterize and visualize different types of weak interactions. To apply the NCI analysis to fluctuating environments as in solution phase, we here develop a new Averaged NonCovalent Interaction (i.e., aNCI) index along with a fluctuation index to characterize magnitude of interactions and fluctuations. We applied aNCI for various systems including solute-solvent and ligand-protein noncovalent interactions. For water and benzene molecules in aqueous solution, solvation structures and the specific hydrogen bond patterns were visualized clearly. For the Cl(-)+CH3Cl SN2 reaction in aqueous solution, charge reorganization influences over solvation structure along SN2 reaction were revealed. For ligand-protein systems, aNCI can recover several key fluctuating hydrogen bond patterns that have potential applications for drug design. Therefore, aNCI, as a complementary approach to the original NCI method, can extract and visualize noncovalent interactions from thermal noise in fluctuating environments.

SUBMITTER: Wu P

PROVIDER: S-EPMC3720145 | biostudies-literature | 2013 May

REPOSITORIES: biostudies-literature

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Noncovalent Interaction Analysis in Fluctuating Environments.

Wu Pan P Chaudret Robin R Hu Xiangqian X Yang Weitao W

Journal of chemical theory and computation 20130501 5

Noncovalent interactions play a central role in many chemical and biological systems. In a previous study, Johnson <i>et al</i> developed a NonCovalent Interaction (NCI) index to characterize and visualize different types of weak interactions. To apply the NCI analysis to fluctuating environments as in solution phase, we here develop a new Averaged NonCovalent Interaction (i.e., aNCI) index along with a fluctuation index to characterize magnitude of interactions and fluctuations. We applied aNCI ...[more]

PMID: 23894230

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Project description:Coastal marine systems are affected by seasonal variations in biogeochemical and physical processes, sometimes leading to alternating periods of reproductive growth limitation within an annual cycle. Transitions between these periods can be sudden or gradual. Human activities, such as reservoir construction and interbasin water transfers, influence these processes and can affect the type of transition between resource loading conditions. How such human activities might influence phytoplankton succession is largely unknown. Here, we employ a multispecies, multi-nutrient model to explore how nutrient loading switching mode might affect phytoplankton succession. The model is based on the Monod-relationship, predicting an instantaneous reproductive growth rate from ambient inorganic nutrient concentrations whereas the limiting nutrient at any given time was determined by Liebig's Law of the Minimum. When these relationships are combined with population loss factors, such as hydraulic displacement of cells associated with inflows, a characterization of a species' niche can be achieved through application of the R* conceptual model, thus enabling an ecological interpretation of modeling results. We found that the mode of reversal in resource supply concentrations had a profound effect. When resource supply reversals were sudden, as expected in systems influenced by pulsed inflows or wind-driven mixing events, phytoplankton were characterized by alternating succession dynamics, a phenomenon documented in inland water bodies of temperate latitudes. When resource supply reversals were gradual, as expected in systems influenced by seasonally developing wet and dry seasons, or annually occurring periods of upwelling, phytoplankton dynamics were characterized by mirror-image succession patterns. This phenomenon has not been reported previously in plankton systems but has been observed in some terrestrial plant systems. These findings suggest that a transition from alternating to "mirror-image" succession patterns might arise with continued coastal zone development, with crucial implications for ecosystems dependent on time-sensitive processes, e.g., spawning events and migration patterns.

Project description:Annual variations in biogeochemical and physical processes can lead to nutrient variability and seasonal patterns in phytoplankton productivity and assemblage structure. In many coastal systems river inflow and water exchange with the ocean varies seasonally, and alternating periods can arise where the nutrient most limiting to phytoplankton growth switches. Transitions between these alternating periods can be sudden or gradual and this depends on human activities, such as reservoir construction and interbasin water transfers. How such activities might influence phytoplankton assemblages is largely unknown. Here, we employed a multispecies, multi-nutrient model to explore how nutrient loading switching mode might affect characteristics of phytoplankton assemblages. The model is based on the Monod-relationship, predicting an instantaneous growth rate from ambient inorganic nutrient concentrations whereas the limiting nutrient at any given time was determined by Liebig's Law of the Minimum. Our simulated phytoplankton assemblages self-organized from species rich pools over a 15-year period, and only the surviving species were considered as assemblage members. Using the model, we explored the interactive effects of complementarity level in trait trade-offs within phytoplankton assemblages and the amount of noise in the resource supply concentrations. We found that the effect of shift from a sudden resource supply transition to a gradual one, as observed in systems impacted by watershed development, was dependent on the level of complementarity. In the extremes, phytoplankton species richness and relative overyielding increased when complementarity was lowest, and phytoplankton biomass increased greatly when complementarity was highest. For low-complementarity simulations, the persistence of poorer-performing phytoplankton species of intermediate R*s led to higher richness and relative overyielding. For high-complementarity simulations, the formation of phytoplankton species clusters and niche compression enabled higher biomass accumulation. Our findings suggest that an understanding of factors influencing the emergence of life history traits important to complementarity is necessary to predict the impact of watershed development on phytoplankton productivity and assemblage structure.

Dataset Information

Noncovalent Interaction Analysis in Fluctuating Environments.

Publications

Noncovalent Interaction Analysis in Fluctuating Environments.

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