40 research outputs found
Sequence-based study of two related proteins with different folding behaviors
ZSPA-1 is an engineered protein that binds to its parent, the
three-helix-bundle Z domain of staphylococcal protein A. Uncomplexed ZSPA-1
shows a reduced helix content and a melting behavior that is less cooperative,
compared with the wild-type Z domain. Here we show that the difference in
folding behavior between these two sequences can be partly understood in terms
of an off-lattice model with 5-6 atoms per amino acid and a minimalistic
potential, in which folding is driven by backbone hydrogen bonding and
effective hydrophobic attraction.Comment: 12 pages, 5 figure
Monte Carlo Update for Chain Molecules: Biased Gaussian Steps in Torsional Space
We develop a new elementary move for simulations of polymer chains in torsion
angle space. The method is flexible and easy to implement. Tentative updates
are drawn from a (conformation-dependent) Gaussian distribution that favors
approximately local deformations of the chain. The degree of bias is controlled
by a parameter b. The method is tested on a reduced model protein with 54 amino
acids and the Ramachandran torsion angles as its only degrees of freedom, for
different b. Without excessive fine tuning, we find that the effective step
size can be increased by a factor of three compared to the unbiased b=0 case.
The method may be useful for kinetic studies, too.Comment: 14 pages, 4 figure
esyN: network building, sharing and publishing.
The construction and analysis of networks is increasingly widespread in biological research. We have developed esyN ("easy networks") as a free and open source tool to facilitate the exchange of biological network models between researchers. esyN acts as a searchable database of user-created networks from any field. We have developed a simple companion web tool that enables users to view and edit networks using data from publicly available databases. Both normal interaction networks (graphs) and Petri nets can be created. In addition to its basic tools, esyN contains a number of logical templates that can be used to create models more easily. The ability to use previously published models as building blocks makes esyN a powerful tool for the construction of models and network graphs. Users are able to save their own projects online and share them either publicly or with a list of collaborators. The latter can be given the ability to edit the network themselves, allowing online collaboration on network construction. esyN is designed to facilitate unrestricted exchange of this increasingly important type of biological information. Ultimately, the aim of esyN is to bring the advantages of Open Source software development to the construction of biological networks.This is the final published version of the paper. It's also available from PLOS at http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0106035
Oligomerization of amyloid Abeta peptides using hydrogen bonds and hydrophobicity forces
The 16-22 amino acid fragment of the beta-amyloid peptide associated with the
Alzheimer's disease, Abeta, is capable of forming amyloid fibrils. Here we
study the aggregation mechanism of Abeta(16-22) peptides by unbiased
thermodynamic simulations at the atomic level for systems of one, three and six
Abeta(16-22) peptides. We find that the isolated Abeta(16-22) peptide is mainly
a random coil in the sense that both the alpha-helix and beta-strand contents
are low, whereas the three- and six-chain systems form aggregated structures
with a high beta-sheet content. Furthermore, in agreement with experiments on
Abeta(16-22) fibrils, we find that large parallel beta-sheets are unlikely to
form. For the six-chain system, the aggregated structures can have many
different shapes, but certain particularly stable shapes can be identified.Comment: 19 pages, 7 figures (to appear in Biophys. J.
The TRiC/CCT chaperone is implicated in Alzheimer's disease based on patient GWAS and an RNAi screen in Aβ-expressing Caenorhabditis elegans.
The human Aβ peptide causes progressive paralysis when expressed in the muscles of the nematode worm, C. elegans. We have exploited this model of Aβ toxicity by carrying out an RNAi screen to identify genes whose reduced expression modifies the severity of this locomotor phenotype. Our initial finding was that none of the human orthologues of these worm genes is identical with the genome-wide significant GWAS genes reported to date (the "white zone"); moreover there was no identity between worm screen hits and the longer list of GWAS genes which included those with borderline levels of significance (the "grey zone"). This indicates that Aβ toxicity should not be considered as equivalent to sporadic AD. To increase the sensitivity of our analysis, we then considered the physical interactors (+1 interactome) of the products of the genes in both the worm and the white+grey zone lists. When we consider these worm and GWAS gene lists we find that 4 of the 60 worm genes have a +1 interactome overlap that is larger than expected by chance. Two of these genes form a chaperonin complex, the third is closely associated with this complex and the fourth gene codes for actin, the major substrate of the same chaperonin
Finite Size Effects in Simulations of Protein Aggregation
It is becoming increasingly clear that the soluble protofibrillar species that proceed amyloid fibril formation are associated with a range of neurodegenerative disorders such as Alzheimer's and Parkinson diseases. Computer simulations of the processes that lead to the formation of these oligomeric species are starting to make significant contributions to our understanding of the determinants of protein aggregation. We simulate different systems at constant concentration but with a different number of peptides and we study the how the finite number of proteins affects the underlying free energy of the system and therefore the relative stability of the species involved in the process. If not taken into account, this finite size effect can undermine the validity of theoretical predictions regarding the relative stability of the species involved and the rates of conversion from one to the other. We discuss the reasons that give rise to this finite size effect form both a probabilistic and energy fluctuations point of view and also how this problem can be dealt by a finite size scaling analysis
ALS/FTD Mutation-Induced Phase Transition of FUS Liquid Droplets and Reversible Hydrogels into Irreversible Hydrogels Impairs RNP Granule Function.
The mechanisms by which mutations in FUS and other RNA binding proteins cause ALS and FTD remain controversial. We propose a model in which low-complexity (LC) domains of FUS drive its physiologically reversible assembly into membrane-free, liquid droplet and hydrogel-like structures. ALS/FTD mutations in LC or non-LC domains induce further phase transition into poorly soluble fibrillar hydrogels distinct from conventional amyloids. These assemblies are necessary and sufficient for neurotoxicity in a C. elegans model of FUS-dependent neurodegeneration. They trap other ribonucleoprotein (RNP) granule components and disrupt RNP granule function. One consequence is impairment of new protein synthesis by cytoplasmic RNP granules in axon terminals, where RNP granules regulate local RNA metabolism and translation. Nuclear FUS granules may be similarly affected. Inhibiting formation of these fibrillar hydrogel assemblies mitigates neurotoxicity and suggests a potential therapeutic strategy that may also be applicable to ALS/FTD associated with mutations in other RNA binding proteins.Supported by Canadian Institutes of Health Research (PEF, PStGH), Alzheimer Society of Ontario (PEF, PStGH), Wellcome Trust (PStGH, MEV, CFK, GSK, DR, CEH), Medical Research Council (PStGH, MEV, CFK, GSK), National Institutes of Health Research, Alzheimer Research UK (CFK, GSK), Gates Cambridge Scholarship (JQL), Engineering and Physical Sciences Research Council (CFK, GSK), European Research Council Starting Grant RIBOMYLOME_309545 (GGT), European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement no. 322817 (CEH), and National Institute of Neurological Disorders and Stroke R01 NS07377 (NAS). The authors thank Tom Cech and Roy Parker for helpful discussions.This is the final version of the article. It was first available from Elsevier via http://dx.doi.org/10.1016/j.neuron.2015.10.03
Statistical Physics of Protein Folding and Aggregation
The mechanisms of protein folding and aggregation are investigated by computer simulations of all-atom and reduced models with sequence-based potentials. A quasi local Monte Carlo update is developed in order to efficiently sample proteins in the folded phase. A small helical protein, the B-domain of staphylococcal protein A, is studied using a reduced model. In the thermodynamically favoured topology, energy minimisation leads to a conformation whose root mean square deviation form the experimental structure is 1.8Ã…. We also study the thermodynamics and kinetics of small fast folding proteins without a clear free-energy barrier between the folded and unfolded states. Analytical calculations using a square well-potential enable us to predict the relaxation time within a factor of two. Finally using an all atom model, we study the aggregation properties of a 7-amino acid fragment of Alzheimer's amyloid beta peptide. We find that the system of three and six such fragments form aggregated structures with a high content of antiparallel beta-sheet structure, which is in line with experimental data