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• W32345542 endingPage "77" @default.
• W32345542 startingPage "59" @default.
• W32345542 abstract "Introduction Proteins fold into unique three-dimensional structures predefined by their specific amino acid sequences (Brooks et al. 1998). However, proteins are not static and in their “folded state”; they can interconvert between multiple conformations as a result of thermal energy (Frauenfelder et al. 1988). In fact, protein motions display a hierarchy of timescales, with side-chain fluctuations occurring in the pico- to nanosecond timescale range whereas large-scale domain motions occur in the micro- to millisecond range or slower (Henzler-Wildman et al. 2007). Of these motions, slow-timescale (i.e., ms–μs range), large-amplitude collective motions between a relatively small number of states are of particular interest because they are linked to protein functions such as in enzyme catalysis, drug binding, signal transduction, immune response, protein folding, and protein-protein interactions (Henzler-Wildman and Kern 2007). Large-amplitude conformational changes in biomolecules are often associated with the binding or release of ligands. X-ray crystallography and NMR experiments provide crucial structural information on the conformation of the biomolecule before and after the conformation changes but reveal less about the transition dynamics between two end structures. Moreover, because proteins can sample an ensemble of conformations around the average structure, a complete understanding of protein dynamics requires the knowledge of the multi-dimensional free-energy landscape (functional landscape) that defines the relative probabilities of thermally accessible conformational states and the free-energy barriers between them. This crucial information about the system can be obtained from molecular dynamics (MD) simulations that can pinpoint the precise position and energy of each atom at any instant in time for a single structurally well-resolved protein molecule. Thus molecular dynamics simulations can connect structure and function through a wide range of thermally accessible states, and they have become an important tool for investigating the dynamics of biological molecules (Karplus and McCammon 2002)." @default.
• W32345542 created "2016-06-24" @default.
• W32345542 creator A5003501137 @default.
• W32345542 creator A5060440052 @default.
• W32345542 date "2012-01-06" @default.
• W32345542 modified "2023-09-24" @default.
• W32345542 title "Exploring the Functional Landscape of Biomolecular Machines via Elastic Network Normal Mode Analysis" @default.
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