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D P Dolata

Publications and source records attributed to D P Dolata.

10 recordsLinked to original sources
PubMed1994

MOUSE-III: learning rules of conformational analysis from X-ray data.

MOUSE-III is learning program that finds rules of conformational analysis from raw crystallographic data. The program perceives molecular features, finds conformational classes in the data and then learns rules that link features to classes. The rules that MOUSE learns are capable of correctly assigning conformations to ring systems that were not used for training with greater than 95% accuracy, when MOUSE was presented with sufficient data. The rules also show a compression of as much as 99% when compared to the raw data. This is accomplished through abstraction and generalization. The algorithm is presented along with a carefully worked example. An example of a learned rule is also presented and analyzed. Some conclusions about the scope and limitations of the learning process are presented.

Algorithms↗
PubMed1993

Conformations of large cycloalkanes: cyclooctadecane, cyclononadecane and cycloicosane.

The conformations of cyclooctadecane, cyclononadecane, and cycloicosane were generated by a stochastic program that works in conjunction with MM2. The shapes of the rings are analyzed in terms of previous work by Dale and others, and in terms of distributions of energies, torsion angle distributions, and torsion angle sequences. A new shape element called the 'nick' has been discovered, and it seems to be increasingly important with 18-membered and larger rings. Previously suggested relationships between ring size and energy distribution were observed, and a geometrical explanation is provided for the relative distributions of stable conformations in 16-, 18-, and 20-membered rings.

Algorithms↗
PubMed1993

Short-term learning in conformational analysis.

A method for learning short-term rules of conformational analysis is introduced. The technique works by discovering problems during the building of a conformation in Cartesian coordinate space, and builds an abstract critic suitable for reasoning in abstract symbolic space. The methods not only afford speed increases ranging from 1.0- to 2.3-fold in WIZARD (analysis completed in 100% to 43% of original run time), but can be modified to provide similar increases in other programs that use "template joining" and distance geometry. These methods also provide the basis for a long-term learning project.

Artificial Intelligence↗
PubMed1993

Tylophora compounds as Na+/K(+)-ATPase inhibitors.

1. Acetyltylophoroside (AcT) and tylogenin inhibit Na+/K(+)-ATPase in spite of having structures very different from cardiac glycosides (CGs). 2. Calculation of the lowest energy conformations of AcT and tylogenin and superpositions of these with the X-ray conformations of CGs and chlormadinone acetate led to a model for the interaction of these different types of Na+/K(+)-ATPase inhibitors with the receptor.

4-Butyrolactone↗
PubMed1990

Automated conformational analysis: algorithms for the efficient construction of low-energy conformations.

The method of constructing low-energy conformations using template joining can provide an efficient means of searching the conformational space of molecules. The simplest algorithm to perform this task would construct each potential conformation from scratch. However, new algorithms, some of which use techniques from Artificial Intelligence, have been developed which can greatly improve the efficiency of this approach.

Algorithms↗
PubMed1990

Automated conformational analysis and structure generation: algorithms for molecular perception.

Many methodologies for performing automated conformational analysis require some means of "perceiving" a molecule to determine features of interest. Algorithms for finding rings, bond orders, and stereocenters and detecting the presence of substructural fragments have been developed. These algorithms are described, emphasizing their importance in conformational analysis.

Artificial Intelligence↗
PubMed1987

WIZARD: AI in conformational analysis.

A program which utilizes the techniques of Artificial Intelligence and Expert Systems to solve problems in the area of Conformational Analysis is described. The program searches conformational space in a systematic fashion, based on the technique known as heuristic state-space search. The program proceeds by recognizing conformational units, assigning one or more conformational templates to each unit, and joining them to form conformational suggestions. These suggestions are criticized to discover logical inconsistencies, and any resulting stresses are resolved. The resulting conformational suggestions are sometimes accurate enough for immediate use, or may be further refined by a numerical program. The latter combination is shown to be quite efficient compared to purely numerical conformational search techniques.

Artificial Intelligence↗