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D S Rykunov

Publications and source records attributed to D S Rykunov.

10 recordsLinked to original sources
PubMed2000

Search for the most stable folds of protein chains: III. Improvement in fold recognition by averaging over homologous sequences and 3D structures.

Three-dimensional (3D) protein fold recognition by query sequence can be improved using information of fold recognition yielded by the sequences homologous to the query one. This idea is now used more and more widely. Our paper presents its consequent development. We suggest incorporating information both on the sequences homologous to the query protein sequence and the 3D structures homologous to the target (already deciphered) protein folds. We show that both these tricks, and especially their combination reduces errors in fold recognition by the threading method. Proteins 2000;40:494-501.

Amino Acids↗
PubMed1998

Optimization of protein structure on lattices using a self-consistent field approach.

Lattice modeling of proteins is commonly used to study the protein folding problem. The reduced number of possible conformations of lattice models enormously facilitates exploration of the conformational space. In this work, we suggest a method to search for the optimal lattice models that reproduced the off-lattice structures with minimal errors in geometry and energetics. The method is based on the self-consistent field optimization of a combined pseudoenergy function that includes two force fields: an "interaction field," that drives the residues to optimize the chain energy, and a "geometrical field," that attracts the residues towards their native positions. By varying the contributions of these force fields in the combined pseudoenergy, one can also test the accuracy of potentials: the better the potentials, i.e., the more accurate the "interaction field," and the smaller the contribution of the "geometrical field" required for building accurate lattice models.

Models, Chemical↗
PubMed1996

Building self-avoiding lattice models of proteins using a self-consistent field optimization.

We present an algorithm to build self-avoiding lattice models of chain molecules with low RMS deviation from their actual 3D structures. To find the optimal coordinates for the lattice chain model, we minimize a function that consists of three terms: (1) the sum of squared deviations of link coordinates on a lattice from their off-lattice values, (2) the sum of "short-range" terms, penalizing violation of chain connectivity, and (3) the sum of "long-range" repulsive terms, penalizing chain self-intersections. We treat this function as a chain molecule "energy" and minimize it using self-consistent field (SCF) theory to represent the pairwise link repulsions as 3D fields acting on the links. The statistical mechanics of chain molecules enables computation of the chain distribution in this field on the lattice. The field is refined by iteration to become self-consistent with the chain distribution, then dynamic programming is used to find the optimal lattice model as the "lowest-energy" chain pathway in this SCF. We have tested the method on one of the coarsest (and most difficult) lattices used for model building on proteins of all structural types and show that the method is adequate for building self-avoiding models of proteins with low RMS deviations from the actual structures.

Algorithms↗
PubMed1995

Accurate general method for lattice approximation of three-dimensional structure of a chain molecule.

An algorithm based on dynamic programming gives the lattice models having the minimal RMS deviations from the actual folds of protein (RNA, etc.) chains for a given lattice and a given orientation of the macromolecule relative to the lattice. The algorithm is applicable for 3-D lattices of any kind. The accuracy of the lattice approximation increases when the distance between neighbor chain links is not rigidly fixed. Special repulsive potentials facilitate generation of self-avoiding lattice chains. The results of model building show the efficiency and precision of this proposed general method when compared with others.

Algorithms↗
PubMed1995

Constructing lattice models of protein chains with side groups.

An algorithm to construct lattice models of polymers with side chains is presented. A search for the global minimum of the error function for a given lattice-to-chain orientation is done by dynamic programming, making the search both fast and complete. Application of the algorithm is illustrated by constructing lattice models for 12 proteins of different sizes and structural types.

Algorithms↗
PubMedDate not supplied

[When and how can homologs overcome errors in the energy estimates and make the 3D structure prediction possible].

One still cannot predict the 3D fold of a protein from its amino acid sequence, mainly because of errors in the energy estimates underlying the prediction. However, a recently developed theory [1] shows that having a set of homologs (i.e., the chains with equal, in despite of numerous mutations, 3D folds) one can average the potential of each interaction over the homologs and thus predict the common 3D fold of protein family even when a correct fold prediction for an individual sequence is impossible because the energies are known only approximately. This theoretical conclusion has been verified by simulation of the energy spectra of simplified models of protein chains [2], and the further investigation of these simplified models shows that their true "native" fold can be found by folding of the chain where each interaction potential is averaged over the homologs. In conclusion, the applicability of the "homolog-averaging" approach is tested by recognition of real protein 3D structures. Both the gapless threading of sequences onto the known protein folds [3] and the more practically important gapped threading (which allows to consider not only the known 3D structures, but the more or less similar to them folds as well) shows a significant increase in selectivity of the native chain fold recognition.

Computer Simulation↗
PubMedDate not supplied

[A rapid and precise method for lattice approximation of the course of a protein chain based on a dynamic programming algorithm].

Application of a dynamic programming method allows one to find the best possible lattice model of a protein chain fold for any lattice and any orientation of the protein relative to the lattice. Special repulsive potentials help to obtain the self-avoiding lattice models of protein folds. The quality of approximation increases when the distance between neighbor chain links is not fixed rigidly. The calculations carried out for the proteins of different structural classes show a high efficiency and precision of this method in comparison with other ones.

Algorithms↗
PubMedDate not supplied

[The brain in stereotaxic coordinates (a textbook for colleges)].

The present textbook is directed forward students of universities and medical colleges, young scientists and practicing doctors dealing with stereotaxic method. The Paxinos and Watson stereotaxic rat brain atlas (1982) is the basis of the textbook. The atlas has been transformed into computer educational program and seven laboratory works: insertion of the electrode into brain, microelectrophoresis, microinjection of drugs into brain, electrolytic destruction in the brain structures, local brain superfusion. The laboratory works are compiled so that they allow not only to study practical use of the stereotaxic method but to model simple problems involving stereotaxic surgery in the deep structures of brain. The textbook is intended for carrying by IBM PC/AT computers. The volume of the textbook is 1.7 Mbytes.

Animals↗
PubMedDate not supplied

[Estimation of quality of approximation of atom-atom contacts of amino acid residues in proteins by the contacts of the residue force centers].

How precisely the atom-atom contacts of amino acid residues in proteins can be approximated by the contacts of amino acid residue "force centers"? To answer this question, we examined the force centers positioned in the C alpha-atom, the C beta-atom, in the optimal point of the C alpha-C beta axis, and in the geometrical center of residues. The maximal coefficient of correlation between the residue force center contacts and the presence of atom-atom contacts of the residues (85%) was obtained for the force centers positioned in geometrical centers of the residues. The correlation is 80% for the optimal position of the centers on the C alpha-C beta axes; a somewhat smaller value (78%) is obtained for the force centers positioned in C beta-atoms, and 71% only for the centers positioned in C alpha-atoms. The obtained results allow one to estimate the limit of precision of calculations which replace the atom-atom interactions by interactions of amino acid residues taken as a whole.

Amino Acids↗