913 research outputs found
Gap misrepair mutagenesis: efficient site-directed induction of transition, transversion, and frameshift mutations in vitro.
The SISO CSPI PDG standard for commercial off-the-shelf simulation package interoperability reference models
For many years discrete-event simulation has been used to analyze production and logistics problems in manufactur-ing and defense. Commercial-off-the-shelf Simulation Packages (CSPs), visual interactive modelling environ-ments such as Arena, Anylogic, Flexsim, Simul8, Witness, etc., support the development, experimentation and visua-lization of simulation models. There have been various attempts to create distributed simulations with these CSPs and their tools, some with the High Level Architecture (HLA). These are complex and it is quite difficult to assess how a set of models/CSP are actually interoperating. As the first in a series of standards aimed at standardizing how the HLA is used to support CSP distributed simula-tions, the Simulation Interoperability Standards Organiza-tion’s (SISO) CSP Interoperability Product Development Group (CSPI PDG) has developed and standardized a set of Interoperability Reference Models (IRM) that are in-tended to clearly identify the interoperability capabilities of CSP distributed simulations
Thermodynamics of protein folding: a random matrix formulation
The process of protein folding from an unfolded state to a biologically
active, folded conformation is governed by many parameters e.g the sequence of
amino acids, intermolecular interactions, the solvent, temperature and chaperon
molecules. Our study, based on random matrix modeling of the interactions,
shows however that the evolution of the statistical measures e.g Gibbs free
energy, heat capacity, entropy is single parametric. The information can
explain the selection of specific folding pathways from an infinite number of
possible ways as well as other folding characteristics observed in computer
simulation studies.Comment: 21 Pages, no figure
Universality and diversity of folding mechanics for three-helix bundle proteins
In this study we evaluate, at full atomic detail, the folding processes of
two small helical proteins, the B domain of protein A and the Villin headpiece.
Folding kinetics are studied by performing a large number of ab initio Monte
Carlo folding simulations using a single transferable all-atom potential. Using
these trajectories, we examine the relaxation behavior, secondary structure
formation, and transition-state ensembles (TSEs) of the two proteins and
compare our results with experimental data and previous computational studies.
To obtain a detailed structural information on the folding dynamics viewed as
an ensemble process, we perform a clustering analysis procedure based on graph
theory. Moreover, rigorous pfold analysis is used to obtain representative
samples of the TSEs and a good quantitative agreement between experimental and
simulated Fi-values is obtained for protein A. Fi-values for Villin are also
obtained and left as predictions to be tested by future experiments. Our
analysis shows that two-helix hairpin is a common partially stable structural
motif that gets formed prior to entering the TSE in the studied proteins. These
results together with our earlier study of Engrailed Homeodomain and recent
experimental studies provide a comprehensive, atomic-level picture of folding
mechanics of three-helix bundle proteins.Comment: PNAS, in press, revised versio
In the light of directed evolution: Pathways of adaptive protein evolution
Directed evolution is a widely-used engineering strategy for improving the stabilities or biochemical functions of proteins by repeated rounds of mutation and selection. These experiments offer empirical lessons about how proteins evolve in the face of clearly-defined laboratory selection pressures. Directed evolution has revealed that single amino acid mutations can enhance properties such as catalytic activity or stability and that adaptation can often occur through pathways consisting of sequential beneficial mutations. When there are no single mutations that improve a particular protein property experiments always find a wealth of mutations that are neutral with respect to the laboratory-defined measure of fitness. These neutral mutations can open new adaptive pathways by at least 2 different mechanisms. Functionally-neutral mutations can enhance a protein's stability, thereby increasing its tolerance for subsequent functionally beneficial but destabilizing mutations. They can also lead to changes in “promiscuous” functions that are not currently under selective pressure, but can subsequently become the starting points for the adaptive evolution of new functions. These lessons about the coupling between adaptive and neutral protein evolution in the laboratory offer insight into the evolution of proteins in nature
High throughput mutagenesis for identification of residues regulating human prostacyclin (hIP) receptor
The human prostacyclin receptor (hIP receptor) is a seven-transmembrane G protein-coupled receptor (GPCR) that plays a critical role in vascular smooth muscle relaxation and platelet aggregation. hIP receptor dysfunction has been implicated in numerous cardiovascular abnormalities, including myocardial infarction, hypertension, thrombosis and atherosclerosis. Genomic sequencing has discovered several genetic variations in the PTGIR gene coding for hIP receptor, however, its structure-function relationship has not been sufficiently explored. Here we set out to investigate the applicability of high throughput random mutagenesis to study the structure-function relationship of hIP receptor. While chemical mutagenesis was not suitable to generate a mutagenesis library with sufficient coverage, our data demonstrate error-prone PCR (epPCR) mediated mutagenesis as a valuable method for the unbiased screening of residues regulating hIP receptor function and expression. Here we describe the generation and functional characterization of an epPCR derived mutagenesis library compromising >4000 mutants of the hIP receptor. We introduce next generation sequencing as a useful tool to validate the quality of mutagenesis libraries by providing information about the coverage, mutation rate and mutational bias. We identified 18 mutants of the hIP receptor that were expressed at the cell surface, but demonstrated impaired receptor function. A total of 38 non-synonymous mutations were identified within the coding region of the hIP receptor, mapping to 36 distinct residues, including several mutations previously reported to affect the signaling of the hIP receptor. Thus, our data demonstrates epPCR mediated random mutagenesis as a valuable and practical method to study the structurefunction relationship of GPCRs. © 2014 Bill et al
A New Monte Carlo Algorithm for Protein Folding
We demonstrate that the recently proposed pruned-enriched Rosenbluth method
(P. Grassberger, Phys. Rev. E 56 (1997) 3682) leads to extremely efficient
algorithms for the folding of simple model proteins. We test them on several
models for lattice heteropolymers, and compare to published Monte Carlo
studies. In all cases our algorithms are faster than all previous ones, and in
several cases we find new minimal energy states. In addition to ground states,
our algorithms give estimates for the partition sum at finite temperatures.Comment: 4 pages, Latex incl. 3 eps-figs., submitted to Phys. Rev. Lett.,
revised version with changes in the tex
Protein structures and optimal folding emerging from a geometrical variational principle
Novel numerical techniques, validated by an analysis of barnase and
chymotrypsin inhibitor, are used to elucidate the paramount role played by the
geometry of the protein backbone in steering the folding to the correct native
state. It is found that, irrespective of the sequence, the native state of a
protein has exceedingly large number of conformations with a given amount of
structural overlap compared to other compact artificial backbones; moreover the
conformational entropies of unrelated proteins of the same length are nearly
equal at any given stage of folding. These results are suggestive of an
extremality principle underlying protein evolution, which, in turn, is shown to
be associated with the emergence of secondary structures.Comment: Revtex, 5 pages, 5 postscript figure
Potentials of Mean Force for Protein Structure Prediction Vindicated, Formalized and Generalized
Understanding protein structure is of crucial importance in science, medicine
and biotechnology. For about two decades, knowledge based potentials based on
pairwise distances -- so-called "potentials of mean force" (PMFs) -- have been
center stage in the prediction and design of protein structure and the
simulation of protein folding. However, the validity, scope and limitations of
these potentials are still vigorously debated and disputed, and the optimal
choice of the reference state -- a necessary component of these potentials --
is an unsolved problem. PMFs are loosely justified by analogy to the reversible
work theorem in statistical physics, or by a statistical argument based on a
likelihood function. Both justifications are insightful but leave many
questions unanswered. Here, we show for the first time that PMFs can be seen as
approximations to quantities that do have a rigorous probabilistic
justification: they naturally arise when probability distributions over
different features of proteins need to be combined. We call these quantities
reference ratio distributions deriving from the application of the reference
ratio method. This new view is not only of theoretical relevance, but leads to
many insights that are of direct practical use: the reference state is uniquely
defined and does not require external physical insights; the approach can be
generalized beyond pairwise distances to arbitrary features of protein
structure; and it becomes clear for which purposes the use of these quantities
is justified. We illustrate these insights with two applications, involving the
radius of gyration and hydrogen bonding. In the latter case, we also show how
the reference ratio method can be iteratively applied to sculpt an energy
funnel. Our results considerably increase the understanding and scope of energy
functions derived from known biomolecular structures
High resolution protein folding with a transferable potential
A generalized computational method for folding proteins with a fully
transferable potential and geometrically realistic all-atom model is presented
and tested on seven different helix bundle proteins. The protocol, which
includes graph-theoretical analysis of the ensemble of resulting folded
conformations, was systematically applied and consistently produced structure
predictions of approximately 3 Angstroms without any knowledge of the native
state. To measure and understand the significance of the results, extensive
control simulations were conducted. Graph theoretic analysis provides a means
for systematically identifying the native fold and provides physical insight,
conceptually linking the results to modern theoretical views of protein
folding. In addition to presenting a method for prediction of structure and
folding mechanism, our model suggests that a accurate all-atom amino acid
representation coupled with a physically reasonable atomic interaction
potential (that does not require optimization to the test set) and hydrogen
bonding are essential features for a realistic protein model.Comment: submitted to PNAS 2005-03-1
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