11,020 research outputs found
Exploiting Homology Information in Nontemplate Based Prediction of Protein Structures
In this paper we describe a novel strategy for exploring the conformational space of proteins and show that this leads to better models for proteins the structure of which is not amenable to template based methods. Our strategy is based on the assumption that the energy global minimum of homologous proteins must correspond to similar conformations, while the precise profiles of their energy landscape, and consequently the positions of the local minima, are likely to be different. In line with this hypothesis, we apply a replica exchange Monte Carlo simulation protocol that, rather than using different parameters for each parallel simulation, uses the sequences of homologous proteins. We show that our results are competitive with respect to alternative methods, including those producing the best model for each of the analyzed targets in the CASP10 (10th Critical Assessment of techniques for protein Structure Prediction) experiment free modeling category
Extending fragment-based free energy calculations with library Monte Carlo simulation: Annealing in interaction space
Pre-calculated libraries of molecular fragment configurations have previously
been used as a basis for both equilibrium sampling (via "library-based Monte
Carlo") and for obtaining absolute free energies using a polymer-growth
formalism. Here, we combine the two approaches to extend the size of systems
for which free energies can be calculated. We study a series of all-atom
poly-alanine systems in a simple dielectric "solvent" and find that precise
free energies can be obtained rapidly. For instance, for 12 residues, less than
an hour of single-processor is required. The combined approach is formally
equivalent to the "annealed importance sampling" algorithm; instead of
annealing by decreasing temperature, however, interactions among fragments are
gradually added as the molecule is "grown." We discuss implications for future
binding affinity calculations in which a ligand is grown into a binding site
Combining Coarse-Grained Protein Models with Replica-Exchange All-Atom Molecular Dynamics
We describe a combination of all-atom simulations with CABS, a
well-established coarse-grained protein modeling tool, into a single multiscale
protocol. The simulation method has been tested on the C-terminal beta hairpin
of protein G, a model system of protein folding. After reconstructing atomistic
details, conformations derived from the CABS simulation were subjected to
replica-exchange molecular dynamics simulations with OPLS-AA and AMBER99sb
force fields in explicit solvent. Such a combination accelerates system
convergence several times in comparison with all-atom simulations starting from
the extended chain conformation, demonstrated by the analysis of melting
curves, the number of native-like conformations as a function of time and
secondary structure propagation. The results strongly suggest that the proposed
multiscale method could be an efficient and accurate tool for high-resolution
studies of protein folding dynamics in larger systems.Comment: 12 pages, 4 figure
Computers and Liquid State Statistical Mechanics
The advent of electronic computers has revolutionised the application of
statistical mechanics to the liquid state. Computers have permitted, for
example, the calculation of the phase diagram of water and ice and the folding
of proteins. The behaviour of alkanes adsorbed in zeolites, the formation of
liquid crystal phases and the process of nucleation. Computer simulations
provide, on one hand, new insights into the physical processes in action, and
on the other, quantitative results of greater and greater precision. Insights
into physical processes facilitate the reductionist agenda of physics, whilst
large scale simulations bring out emergent features that are inherent (although
far from obvious) in complex systems consisting of many bodies. It is safe to
say that computer simulations are now an indispensable tool for both the
theorist and the experimentalist, and in the future their usefulness will only
increase.
This chapter presents a selective review of some of the incredible advances
in condensed matter physics that could only have been achieved with the use of
computers.Comment: 22 pages, 2 figures. Chapter for a boo
Gene regulatory networks: a coarse-grained, equation-free approach to multiscale computation
We present computer-assisted methods for analyzing stochastic models of gene
regulatory networks. The main idea that underlies this equation-free analysis
is the design and execution of appropriately-initialized short bursts of
stochastic simulations; the results of these are processed to estimate
coarse-grained quantities of interest, such as mesoscopic transport
coefficients. In particular, using a simple model of a genetic toggle switch,
we illustrate the computation of an effective free energy and of a
state-dependent effective diffusion coefficient that characterize an
unavailable effective Fokker-Planck equation. Additionally we illustrate the
linking of equation-free techniques with continuation methods for performing a
form of stochastic "bifurcation analysis"; estimation of mean switching times
in the case of a bistable switch is also implemented in this equation-free
context. The accuracy of our methods is tested by direct comparison with
long-time stochastic simulations. This type of equation-free analysis appears
to be a promising approach to computing features of the long-time,
coarse-grained behavior of certain classes of complex stochastic models of gene
regulatory networks, circumventing the need for long Monte Carlo simulations.Comment: 33 pages, submitted to The Journal of Chemical Physic
Parallel Tempering: Theory, Applications, and New Perspectives
We review the history of the parallel tempering simulation method. From its
origins in data analysis, the parallel tempering method has become a standard
workhorse of physiochemical simulations. We discuss the theory behind the
method and its various generalizations. We mention a selected set of the many
applications that have become possible with the introduction of parallel
tempering and we suggest several promising avenues for future research.Comment: 21 pages, 4 figure
Parallel Tempering Simulation of the three-dimensional Edwards-Anderson Model with Compact Asynchronous Multispin Coding on GPU
Monte Carlo simulations of the Ising model play an important role in the
field of computational statistical physics, and they have revealed many
properties of the model over the past few decades. However, the effect of
frustration due to random disorder, in particular the possible spin glass
phase, remains a crucial but poorly understood problem. One of the obstacles in
the Monte Carlo simulation of random frustrated systems is their long
relaxation time making an efficient parallel implementation on state-of-the-art
computation platforms highly desirable. The Graphics Processing Unit (GPU) is
such a platform that provides an opportunity to significantly enhance the
computational performance and thus gain new insight into this problem. In this
paper, we present optimization and tuning approaches for the CUDA
implementation of the spin glass simulation on GPUs. We discuss the integration
of various design alternatives, such as GPU kernel construction with minimal
communication, memory tiling, and look-up tables. We present a binary data
format, Compact Asynchronous Multispin Coding (CAMSC), which provides an
additional speedup compared with the traditionally used Asynchronous
Multispin Coding (AMSC). Our overall design sustains a performance of 33.5
picoseconds per spin flip attempt for simulating the three-dimensional
Edwards-Anderson model with parallel tempering, which significantly improves
the performance over existing GPU implementations.Comment: 15 pages, 18 figure
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