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N V Dokholyan

Publications and source records attributed to N V Dokholyan.

10 recordsLinked to original sources

Discrete molecular dynamics simulations of peptide aggregation.

We study the aggregation of peptides using the discrete molecular dynamics simulations. Specifically, at temperatures above the alpha-helix melting temperature of a single peptide, the model peptides aggregate into a multilayer parallel beta-sheet structure. This structure has an interstrand distance of 4.8 A and an intersheet distance of 10 A, which agree with experimental observations. Our model explains these results as follows: hydrogen-bond interactions give rise to the interstrand spacing in beta sheets, while Gō interactions between side chains make beta strands parallel to each other and allow beta sheets to pack into layers. An important feature of our results is that the aggregates contain free edges, which may allow for further aggregation of model peptides to form elongated fibrils.

Amyloid beta-Peptides↗

Molecular dynamics simulation of amyloid beta dimer formation.

Recent experiments with amyloid beta (Abeta) peptide indicate that formation of toxic oligomers may be an important contribution to the onset of Alzheimer's disease. The toxicity of Abeta oligomers depends on their structure, which is governed by assembly dynamics. Due to limitations of current experimental techniques, a detailed knowledge of oligomer structure at the atomic level is missing. We introduce a molecular dynamics approach to study Abeta dimer formation. 1), We use discrete molecular dynamics simulations of a coarse-grained model to identify a variety of dimer conformations; and 2), we employ all-atom molecular mechanics simulations to estimate thermodynamic stability of all dimer conformations. Our simulations of a coarse-grained Abeta peptide model predicts 10 different planar beta-strand dimer conformations. We then estimate the free energies of all dimer conformations in all-atom molecular mechanics simulations with explicit water. We compare the free energies of Abeta(1-42) and Abeta(1-40) dimers. We find that 1), dimer conformations have higher free energies compared to their corresponding monomeric states; and 2), the free-energy difference between the Abeta(1-42) and the corresponding Abeta(1-40) dimer conformation is not significant. Our results suggest that Abeta oligomerization is not accompanied by the formation of thermodynamically stable planar beta-strand dimers.

Amyloid beta-Peptides↗

Small-world view of the amino acids that play a key role in protein folding.

We use geometrical considerations to provide a different perspective on the fact that a few selected amino acids, the so-called "key residues," act as nucleation centers for protein folding. By constructing graphs corresponding to protein structures we show that they have the "small-world" feature of having a limited set of vertices with large connectivity. These vertices correspond to the key residues that play the role of "hubs" in the network of interactions that stabilize the structure of the transition state.

Amino Acids↗

Understanding hierarchical protein evolution from first principles.

We propose a model that explains the hierarchical organization of proteins in fold families. The model, which is based on the evolutionary selection of proteins by their native state stability, reproduces patterns of amino acids conserved across protein families. Due to its dynamic nature, the model sheds light on the evolutionary time-scales. By studying the relaxation of the correlation function between consecutive mutations at a given position in proteins, we observe separation of the evolutionary time-scales: at short time intervals families of proteins with similar sequences and structures are formed, while at long time intervals the families of structurally similar proteins that have low sequence similarity are formed. We discuss the evolutionary implications of our model. We provide a "profile" solution to our model and find agreement between predicted patterns of conserved amino acids and those actually observed in nature.

Amino Acid Sequence↗

Thermodynamically important contacts in folding of model proteins.

We introduce a quantity, the entropic susceptibility, that measures the thermodynamic importance-for the folding transition-of the contacts between amino acids in model proteins. Using this quantity, we find that only one equilibrium run of a computer simulation of a model protein is sufficient to select a subset of contacts that give rise to the peak in the specific heat observed at the folding transition. To illustrate the method, we identify thermodynamically important contacts in a model 46-mer. We show that only about 50% of all contacts present in the protein native state are responsible for the sharp peak in the specific heat at the folding transition temperature, while the remaining 50% of contacts do not affect the specific heat.

Amino Acids↗

Identifying the protein folding nucleus using molecular dynamics.

Molecular dynamics simulations of folding in an off-lattice protein model reveal a nucleation scenario, in which a few well-defined contacts are formed with high probability in the transition state ensemble of conformations. Their appearance determines folding cooperativity and drives the model protein into its folded conformation. Amino acid residues participating in those contacts may serve as "accelerator pedals" used by molecular evolution to control protein folding rate.

Binding Sites↗

Distributions of dimeric tandem repeats in non-coding and coding DNA sequences.

We study the length distribution functions for the 16 possible distinct dimeric tandem repeats in DNA sequences of diverse taxonomic partitions of GenBank (known human and mouse genomes, and complete genomes of Caenorhabditis elegans and yeast). For coding DNA, we find that all 16 distribution functions are exponential. For non-coding DNA, the distribution functions for most of the dimeric repeats have surprisingly long tails, that fit a power-law function. We hypothesize that: (i) the exponential distributions of dimeric repeats in protein coding sequences indicate strong evolutionary pressure against tandem repeat expansion in coding DNA sequences; and (ii) long tails in the distributions of dimers in non-coding DNA may be a result of various mutational mechanisms. These long, non-exponential tails in the distribution of dimeric repeats in non-coding DNA are hypothesized to be due to the higher tolerance of non-coding DNA to mutations. By comparing genomes of various phylogenetic types of organisms, we find that the shapes of the distributions are not universal, but rather depend on the specific class of species and the type of a dimer.

Animals↗

Clustering of identical oligomers in coding and noncoding DNA sequences.

We develop a quantitative method for analyzing repetitions of identical short oligomers in coding and noncoding DNA sequences. We analyze sequences presently available in the GenBank separately for primate, mammal, vertebrate, rodent, invertebrate and plant taxonomic partitions. We find that some oligomers "cluster" more than they would if randomly distributed, while other oligomers "repel" each other. To quantify this degree of clustering, we define clustering measures. We find that (i) clustering significantly differs in coding and noncoding DNA; (ii) in most cases, monomers, dimers and tetramers cluster in noncoding DNA but appear to repel each other in coding DNA. (iii) The degree of clustering for different sources (primates, invertebrates, and plants) is more conserved among these sources in the case of coding DNA than in the case of noncoding DNA. (iv) In contrast to other oligomers, we find that trimers always prefer to cluster. (v) Clustering of each particular oligomer is conserved within the same organism.

Animals↗

Traveling time and traveling length in critical percolation clusters.

We study traveling time and traveling length for tracer dispersion in two-dimensional bond percolation, modeling flow by tracer particles driven by a pressure difference between two points separated by Euclidean distance r. We find that the minimal traveling time t(min) scales as t(min) approximately r(1.33), which is different from the scaling of the most probable traveling time, t* approximately r(1.64). We also calculate the length of the path corresponding to the minimal traveling time and find l(min) approximately r(1.13) and that the most probable traveling length scales as l* approximately r(1.21). We present the relevant distribution functions and scaling relations.

Journal Article↗

Discrete molecular dynamics studies of the folding of a protein-like model.

BACKGROUND: Many attempts have been made to resolve in time the folding of model proteins in computer simulations. Different computational approaches have emerged. Some of these approaches suffer from insensitivity to the geometrical properties of the proteins (lattice models), whereas others are computationally heavy (traditional molecular dynamics). RESULTS: We used the recently proposed approach of Zhou and Karplus to study the folding of a protein model based on the discrete time molecular dynamics algorithm. We show that this algorithm resolves with respect to time the folding <--> unfolding transition. In addition, we demonstrate the ability to study the core of the model protein. CONCLUSIONS: The algorithm along with the model of interresidue interactions can serve as a tool for studying the thermodynamics and kinetics of protein models.

Algorithms↗