Protein Structure Prediction: The Next Generation.
TLDR
It is explored how second generation prediction energy functions can be developed by introducing information from an ensemble of previously simulated structures, based on the assumption of a funneled energy landscape keeping with the principle of minimal frustration.Abstract:
Over the last 10-15 years a general understanding of the chemical reaction of protein folding has emerged from statistical mechanics. The lessons learned from protein folding kinetics based on energy landscape ideas have benefited protein structure prediction, in particular the development of coarse grained models. We survey results from blind structure prediction. We explore how second generation prediction energy functions can be developed by introducing information from an ensemble of previously simulated structures. This procedure relies on the assumption of a funneled energy landscape keeping with the principle of minimal frustration. First generation simulated structures provide an improved input for associative memory energy functions in comparison to the experimental protein structures chosen on the basis of sequence alignment.read more
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Modification and optimization of the united-residue (UNRES) potential energy function for canonical simulations. I. Temperature dependence of the effective energy function and tests of the optimization method with single training proteins.
Adam Liwo,Mey Khalili,Cezary Czaplewski,Sebastian Kalinowski,Stanisław Ołdziej,Katarzyna Wachucik,Harold A. Scheraga +6 more
TL;DR: The modification and parametrization of the united-residue (UNRES) force field is reported for energy-based protein structure prediction and protein folding simulations and introduces temperature dependence to the UNRES force field.
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Prediction, determination and validation of phase diagrams via the global study of energy landscapes
TL;DR: In this paper, the authors present an overview of energy landscapes in the context of phase diagram calculations, an overview over the large variety of methods employed to study energy landscapes and compute free energies on the ab initio level, and a number of typic...
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Basin hopping as a general and versatile optimization framework for the characterization of biological macromolecules
TL;DR: It is shown that the basin hopping framework is general and versatile, allowing to address problems related to the characterization of protein structure, assembly, and motion due to its fundamental ability to sample minima in a high-dimensional variable space.
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Conformational switching upon phosphorylation: a predictive framework based on energy landscape principles.
TL;DR: It is shown that the transferable Hamiltonian correctly captures the nature of the global conformational changes induced by phosphorylation and can sample substantially correct structures for the modified protein with high probability.
References
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Stephen F. Altschul,Thomas L. Madden,Alejandro A. Schäffer,Jinghui Zhang,Zheng Zhang,Webb Miller,David J. Lipman +6 more
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Helen M. Berman,John D. Westbrook,Zukang Feng,Gary L. Gilliland,Talapady N. Bhat,Helge Weissig,Ilya N. Shindyalov,Philip E. Bourne +7 more
TL;DR: The goals of the PDB are described, the systems in place for data deposition and access, how to obtain further information and plans for the future development of the resource are described.
Book
Computer Simulation of Liquids
Michael P. Allen,D. J. Tildesley +1 more
TL;DR: In this paper, the gear predictor -corrector is used to calculate forces and torques in a non-equilibrium molecular dynamics simulation using Monte Carlo methods. But it is not suitable for the gear prediction problem.
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Numerical Integration of the Cartesian Equations of Motion of a System with Constraints: Molecular Dynamics of n-Alkanes
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