Computational Approaches to Protein Dynamics: From Quantum - download pdf or read online

By Monika Fuxreiter

ISBN-10: 1466561572

ISBN-13: 9781466561571

This groundbreaking paintings addresses a vital paradigm shift in structural molecular biology, illustrating how protein dynamics performs a valuable function in a variety of features, together with enzymatic catalysis, protein–protein interactions, and the association of complicated assemblies. The publication provides sleek computational thoughts for the characterization of proteins and their dynamic homes. The computational equipment in particular handle the dynamical points of protein functionalities, with distinct emphasis at the research of complicated assemblies and intrinsically disordered proteins.

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Additional resources for Computational Approaches to Protein Dynamics: From Quantum to Coarse-Grained Methods

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Förster resonance energy transfer [FRET]) could benefit from computational prediction of low-energy conformers. Ensemble Description of Protein Structures The discovery of proteins with multiple native states is a new challenge for molecular dynamics simulations. These group of proteins, termed as intrinsically disordered (ID), are devoid of a single, well-defined structure [163]. Instead, ID proteins interconvert between many conformations and exist as an ensemble of structures [164]. Protein segments with similar properties could also be functionally relevant [165].

A new direction is to partition the configurational space into smaller regions along the slow degrees of freedom and these regions are sampled independently [131]. The results, which are produced by the parallel calculations are subsequently merged. If there are several slow degrees of freedom, many dimensional PMFs have to be used, which on the other hand are difficult to cope with. This problem was discussed in connection with metadynamics [37,132]. Finding slow degrees of freedom is also challenging.

Advanced Methods Parametrization of CG techniques is carried out using all-atom MD results, equilibrium geometries, or thermodynamic data as a reference [65]. The obvious benefit of the CG method is enabling the use of longer time steps, which exceed at least one order of magnitude than that of classical MD. Hence CG simulations increase simulation length, which enables the study of large-scale conformational changes. The drawback is obviously losing some of the details, which could be avoided if multiscale or hybrid approaches are applied (see “Multiscale Techniques” section).

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Computational Approaches to Protein Dynamics: From Quantum to Coarse-Grained Methods by Monika Fuxreiter


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