第17回研究談話会(Mircea V. Diudea 氏)開催

テーマ
Title
「Similarity by Cluj topological descriptors」
講演者
Speaker
Prof. Mircea V. Diudea (Faculty of Chemistry and Chemical Engineering, “Babes-Bolyai” University, Rumania; 知的コミュニティ基盤研究センター外国人研究員)
日時
Date
2004年3月26日(金) 15時~16時
場所
Location
筑波大学春日キャンパス 情報メディアユニオン3階共同研究会議室I
概要
Abstract
Twenty years ago there were a dozen of topological indices ? numerical descriptors encoding topological attributes of a molecular graph. They were used both in graph discriminating analysis and correlating studies for modeling a variety physico-chemical properties and biological activities. Nowadays, their number becomes uncountable, as a consequence of the explosive development of computational technology. However, only few software packages are available for calculating topological indices: CODESSA, MOLCONN Z, DRAGON, TOSS MODE or POLLY. They incorporate correlating analysis statistics, as well. The TOPOCLUJ software package is deviced to calculate topological descriptors from topological matrices and/or polynomials. Several weighting schemes including group electronegativity, group mass and partial charges are proposed. Topological indices derived from the matrices: adjacency, connectivity, distance, detour, distance-path, detour-path, Cluj, their reciprocal matrices, walk-matrices, walk-operated matrices, layer- and shell-matrices were successfully used in correlating studies and graph discriminating analysis during the last decade. Several novel topological matrices, like distance-path, Cluj (with its variants), layer-matrices, walk matrix, walk (triple matrix) operator, characteristic and "property" polynomials, and the corresponding topological descriptors are calculable by the TOPOCLUJ software package. Another program developed by the TOPO GROUP CLUJ is CLUJ_SIMIL. It calculates similarity indices and performs correlational analysis in clusters defined by similarity criteria. The antiinflamatory activity of a set of 100 molecules, derivatives of the anthranilic acid, have been investigated by this last program. The activity estimation and prediction of our program is discussed in the light of the literature data.
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