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High coordination lattice models of protein structure, dynamics and thermodynamics

100%

Kolinski A. , Skolnick J.

Acta Biochimica Polonica

1997

tom 44

nr 3

A high coordination lattice discretization of protein conformational space is described. The model allows discrete representation of polypeptide chains of globular proteins and small macromolecular assemblies with an accuracy comparable to the accuracy of crystallographic structures. Knowledge based force Held, that consists of sequence specific short range interactions, cooperative model of hydrogen bond network and tertiary one body, two body and multibody interactions, is outlined and discussed. A model of stochastic dynamics for these protein models is also described. The proposed method enables moderate resolution tertiary structure prediction of simple and small globular proteins. Its applicability in structure prediction increases significantly when evolutionary information is exploited or/and when sparse experimental data are available. The model responds correctly to sequence mutations and could be used at early stages of a computer aided protein design and protein redesign. Computational speed, associated with the discrete structure of the model, enables studies of the long time dynamics of polypeptides and proteins and quite detailed theoretical studies of thermodynamics of nontrivial protein models.

Structure of Proteins : New Approach to Molecular Modeling

80%

Koliński A. , Rotkiewicz P. , Skolnick J.

2001

tom Vol. 75, nr 4

587-599

The force field and Monte Carlo sampling method of our recently developed reduced model of proteins is described. Recent applications of the models include ab initio structure prediction for small globular proteins, modeling of protein structure based on distantly homologous (or analogous) structural templates, assembly of protein structure from sparse experimental data, and computational studies of protein folding dynamics and thermodynamics. The newest application, described in this paper, enables the prediction of low-to-moderate resolution coordinates of the parts of protein structure that are missed in incomplete PDB files.

Prediction of protein secondary structure by neural networks: encoding short and long range patterns of amino acid packing

80%

Vieth M. , Kolinski A. , Skolnick J. , Sikorski A.

Acta Biochimica Polonica

1992

tom 39

nr 4

À complex, cascaded neural network designed to predict the secondary structure of globular proteins has been developed. Information about the local buried-unburied pattern and the average tendency of the particular types of amino acids to be buried inside the globule were used. Nonspecific information about long distance contact maps was also employed. These modifications result in a noticeable improvement (3 - 9%) of prediction accuracy. The best result for the average success ratio for the testing set of nonhomologous proteins was 68.3% (with corresponding Matthews' coefficients, C

Computer simulations of protein folding with a small number of distance restraints

80%

Sikorski A. , Kolinski A. , Skolnick J.

nr 3

A high coordination lattice model was used to represent the protein chain. Lattice points correspond to amino-acid side groups. A complicated force field was designed in order to reproduce a protein-like behavior of the chain. Long-distance tertiary restraints were also introduced into the model. The Replica Exchange Monte Carlo method was applied to find the lowest energy states of the folded chain and to solve the problem of multiple minima. In this method, a set of replicas of the model chain was simulated independently in different temperatures with the exchanges of replicas allowed. The model chains, which consisted of up to 100 residues, were folded to structures whose root-mean-square deviation (RMSD) from their native state was between 2.5 and 5 A. Introduction of restrain based on the positions of the backbone hydrogen atoms led to an improvement in the number of successful simulation runs. A small improvement (about 0.5 A) was also achieved in the RMSD of the folds. The proposed method can be used for the refinement of structures determined experimentally from NMR data.