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• W2519117888 startingPage "73" @default.
• W2519117888 abstract "There is extensive interest in hydrogenases based on their ability to rapidly and efficiently interconvert H2 with protons and electrons, and their (typically) superior function relative to molecular mimics. Understanding the function of enzymes is one approach to implementing design features to make better catalysts and is an approach we have implemented in our work. In this review, we will discuss our efforts to develop design principles from enzymes, with specific focus on proton transport. We will also present computational studies of the mimics we have investigated with similar methodologies. We will discuss the mechanisms used by small scaffolds on molecular mimics which in many cases are surprisingly similar to those used by nature, while in other cases, computational analysis allowed us to reveal an unexpected role. Computational methods provide one of the best ways, and in some cases, the only way, to gain insight into the mechanistic details of enzymes. In this review, we illustrate the general computational strategy we used to study the proton pathway of [FeFe]-hydrogenase, and the similar strategy to investigate small molecules. We present the main results we obtained and how our computational work stimulated or worked in concert with experimental investigations. We also focus on estimation of errors and convergence of properties in the simulations. These studies demonstrate the powerful results that can be obtained by the close pairing of experimental and theoretical approaches." @default.
• W2519117888 created "2016-09-23" @default.
• W2519117888 creator A5034580690 @default.
• W2519117888 creator A5062213912 @default.
• W2519117888 creator A5078039482 @default.
• W2519117888 date "2016-01-01" @default.
• W2519117888 modified "2023-09-27" @default.
• W2519117888 title "Molecular Dynamics Studies of Proton Transport in Hydrogenase and Hydrogenase Mimics" @default.
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• W2519117888 doi "https://doi.org/10.1016/bs.mie.2016.05.044" @default.
• W2519117888 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/27497163" @default.
• W2519117888 hasPublicationYear "2016" @default.
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