Monte Carlo update for chain molecules: Biased Gaussian steps in torsional space

Favrin, Giorgio; Irbäck, Anders; Sjunnesson, Fredrik

doi:10.1063/1.1364637

Cited by 109 publications

(114 citation statements)

References 27 publications

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“…a single torsion angle is turned, and the semi-local biased Gaussian step proposed in Ref. [31]. The latter method works with the Ramachandran angles of four adjacent amino acids.…”

Section: Methodsmentioning

confidence: 99%

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Folding of a small helical protein using hydrogen bonds and hydrophobicity forces

2002

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Abstract:A reduced protein model with five to six atoms per amino acid and five amino acid types is developed and tested on a three-helix-bundle protein, a 46-amino acid fragment from staphylococcal protein A. The model does not rely on the widely used Gō approximation where non-native interactions are ignored. We find that the collapse transition is considerably more abrupt for the protein A sequence than for random sequences with the same composition. The chain collapse is found to be at least as fast as helix formation. Energy minimization restricted to the thermodynamically favored topology gives a structure that has a root-mean-square deviation of 1.8Å from the native structure. The sequence-dependent part of our potential is pairwise additive. Our calculations suggest that fine-tuning this potential by parameter optimization is of limited use. *

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“…a single torsion angle is turned, and the semi-local biased Gaussian step proposed in Ref. [31]. The latter method works with the Ramachandran angles of four adjacent amino acids.…”

Section: Methodsmentioning

confidence: 99%

“…The degree of bias is governed by a parameter b. In our thermodynamic simulations, we take b = 10 (rad/Å) 2 , which gives a strong bias toward deformations that are approximately local [31]. Figure 3 shows the evolution of the energy in a simulated-tempering run that took about two weeks on an 800 MHz processor.…”

Section: Methodsmentioning

confidence: 99%

Folding of a small helical protein using hydrogen bonds and hydrophobicity forces

2002

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“…To sample the conformations of the protein chains anchored on the trans ring, we use two basic Monte-Carlo moves: branch rotation and an improved version of the biased Gaussian step [25], while for the translocating alpha helix we allow only translation moves and rotation around the center of mass. Figure S5 Plot of translocation free energy F (Q,Q s ) as a function of the number of Helix-chains contacts Q and of the number of translocated residues Q s .…”

Section: Foldingmentioning

confidence: 99%

Multi-Scale Simulations Provide Supporting Evidence for the Hypothesis of Intramolecular Protein Translocation in GroEL/GroES Complexes

Coluzza¹,

Simone²,

Fraternali³

et al. 2005

PLoS Comput Biol

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The biological function of chaperone complexes is to assist the folding of non-native proteins. The widely studied GroEL chaperonin is a double-barreled complex that can trap non-native proteins in one of its two barrels. The ATP-driven binding of a GroES cap then results in a major structural change of the chamber where the substrate is trapped and initiates a refolding attempt. The two barrels operate anti-synchronously. The central region between the two barrels contains a high concentration of disordered protein chains, the role of which was thus far unclear. In this work we report a combination of atomistic and coarse-grained simulations that probe the structure and dynamics of the equatorial region of the GroEL/GroES chaperonin complex. Surprisingly, our simulations show that the equatorial region provides a translocation channel that will block the passage of folded proteins but allows the passage of secondary units with the diameter of an alpha-helix. We compute the free-energy barrier that has to be overcome during translocation and find that it can easily be crossed under the influence of thermal fluctuations. Hence, strongly non-native proteins can be squeezed like toothpaste from one barrel to the next where they will refold. Proteins that are already fairly close to the native state will not translocate but can refold in the chamber where they were trapped. Several experimental results are compatible with this scenario, and in the case of the experiments of Martin and Hartl, intra chaperonin translocation could explain why under physiological crowding conditions the chaperonin does not release the substrate protein.

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“…If one does not propose y new uniformly anymore, the name Biased Metropolis Algorithm (BMA) is often used. Some biased Metropolis simulations can be found in the literature where the bias is introduced to match special situations [60,61,62,63,64]. In the following we discuss a general biased Metropolis scheme [15,65], which aims at approximating heatbath probabilities.…”

Section: Biased Markov Chain Monte Carlomentioning

confidence: 99%

“…Cross-fertilization may go in both directions. For instance, generalized ensemble techniques propagated from lattice gauge theory [7] over statistical physics [42] into biophysics [13], while it appears that biased Metropolis techniques [60,61,62,63,15] propagate in the opposite direction [65].…”

Section: Outlook and Conclusionmentioning

confidence: 99%

Markov Chain Monte Carlo Methods for Simulations of Biomolecules

Berg

Lecture Notes in Physics

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The computer revolution has been driven by a sustained increase of computational speed of approximately one order of magnitude (a factor of ten) every five years since about 1950. In natural sciences this has led to a continuous increase of the importance of computer simulations. Major enabling techniques are Markov Chain Monte Carlo (MCMC) and Molecular Dynamics (MD) simulations.This article deals with the MCMC approach. First basic simulation techniques, as well as methods for their statistical analysis are reviewed. Afterwards the focus is on generalized ensembles and biased updating, two advanced techniques, which are of relevance for simulations of biomolecules, or are expected to become relevant with that respect. In particular we consider the multicanonical ensemble and the replica exchange method (also known as parallel tempering or method of multiple Markov chains).

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Monte Carlo update for chain molecules: Biased Gaussian steps in torsional space

Cited by 109 publications

References 27 publications

Folding of a small helical protein using hydrogen bonds and hydrophobicity forces

Folding of a small helical protein using hydrogen bonds and hydrophobicity forces

Multi-Scale Simulations Provide Supporting Evidence for the Hypothesis of Intramolecular Protein Translocation in GroEL/GroES Complexes

Markov Chain Monte Carlo Methods for Simulations of Biomolecules

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