On searching in, sampling of, and dynamically moving through conformational space of biomolecular systems: A review.
TLDR
Methods to search for low‐energy conformations, to generate a Boltzmann‐weighted ensemble of configurations, or to generate classical‐dynamical trajectories for molecular systems in the condensed liquid phase are briefly reviewed with an eye to application to biomolecular systems.Abstract:
Methods to search for low-energy conformations, to generate a Boltzmann-weighted ensemble of configurations, or to generate classical-dynamical trajectories for molecular systems in the condensed liquid phase are briefly reviewed with an eye to application to biomolecular systems. After having chosen the degrees of freedom and method to generate molecular configurations, the efficiency of the search or sampling can be enhanced in various ways: (i) efficient calculation of the energy function and forces, (ii) application of a plethora of search enhancement techniques, (iii) use of a biasing potential energy term, and (iv) guiding the sampling using a reaction or transition pathway. The overview of the available methods should help the reader to choose the combination that is most suitable for the biomolecular system, degrees of freedom, interaction function, and molecular or thermodynamic properties of interest.read more
Citations
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Computational Prediction of 1H and 13C Chemical Shifts: A Useful Tool for Natural Product, Mechanistic, and Synthetic Organic Chemistry
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Perspective: Coarse-grained models for biomolecular systems.
TL;DR: This review seeks to provide a balanced, coherent, and unified presentation of several distinct approaches for developing CG models, including top-down, network- based, native-centric, knowledge-based, and bottom-up modeling strategies.
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Coarse-Grained Protein Models and Their Applications
Sebastian Kmiecik,Dominik Gront,Michal Kolinski,Lukasz Wieteska,Lukasz Wieteska,Aleksandra Elzbieta Dawid,Andrzej Kolinski +6 more
TL;DR: An overview of coarse-grained models focusing on their design, including choices of representation, models of energy functions, sampling of conformational space, and applications in the modeling of protein structure, dynamics, and interactions are provided.
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Combining an Elastic Network With a Coarse-Grained Molecular Force Field: Structure, Dynamics, and Intermolecular Recognition
TL;DR: The results for this series of tests indicate that ELNEDIN models allow microsecond time-scale molecular dynamics simulations to be carried out readily, that large biological entities such as the viral capsid of the cowpea mosaic virus can be stably modeled as assemblies of independent ELNedIN models, and that ELnEDin models show significant promise for modeling protein-protein association processes.
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Computations of standard binding free energies with molecular dynamics simulations.
Yuqing Deng,Benoît Roux +1 more
TL;DR: An increasing number of studies have reported computations of the standard (absolute) binding free energy of small ligands to proteins using molecular dynamics simulations and explicit solvent molecules that are in good agreement with experiments, suggesting that physics-based approaches hold the promise of making important contributions to the process of drug discovery and optimization in the near future.
References
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Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Journal ArticleDOI
Optimization by Simulated Annealing
TL;DR: There is a deep and useful connection between statistical mechanics and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters), and a detailed analogy with annealing in solids provides a framework for optimization of very large and complex systems.
Genetic algorithms in search, optimization and machine learning
TL;DR: This book brings together the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields.
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Molecular dynamics with coupling to an external bath.
TL;DR: In this paper, a method is described to realize coupling to an external bath with constant temperature or pressure with adjustable time constants for the coupling, which can be easily extendable to other variables and to gradients, and can be applied also to polyatomic molecules involving internal constraints.
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Numerical Integration of the Cartesian Equations of Motion of a System with Constraints: Molecular Dynamics of n-Alkanes
TL;DR: In this paper, a numerical algorithm integrating the 3N Cartesian equations of motion of a system of N points subject to holonomic constraints is formulated, and the relations of constraint remain perfectly fulfilled at each step of the trajectory despite the approximate character of numerical integration.
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