Yasuhiko Yotsui

A structure-biological activity study based on cluster analysis and the nonlinear mapping method of pattern recognition

Abstract Cluster analysis is used in a study of structure—activity relationships of biologically active compounds. A hierarchal clustering technique was applied to 29 typical antibiotics using 27 antibacterial activities. These antibiotics were of various types; penicillins, cephalosporins, aminoglycosides, macrolides, tetracyclines, and peptides. The result was obtained as a branching tree diagram. The technique allowed the antibiotics to be distributed into 6 clusters, each cluster mostly consisting of compounds with a similar structure. Nonlinear mapping was used to display the 27-dimensional data structure of the antibiotics. The nonlinear map was compared with the clusters obtained by cluster analysis.

Computer-assisted structure—carcinogenicity studies on polycyclic aromatic hydrocarbons by pattern recognition methods

Abstract Pattern recognition methods are applied to the study of structure—carcinogenicity relationships in 25 representative polycyclic aromatic hydrocarbons (PAHs). On the basis of presumed metabolic transformation, a variety of reactivity indices taken from simple Huckel molecular orbital theory for not only parent PAH but also later metabolites are used to investigate the carcinogenic process. In order to display the 12-dimensional molecular descriptor space, a Karhunen—Loeve plot in two-dimensional space is employed, 92.1% of the variance is retained. The data structure shows asymmetric character. Carcinogens are clustered, whereas non-carcinogens are scattered. Linear discriminant functions for carcinogenicity are developed by using multiple linear regression analysis. The most significant equations suggest the importance of metabolic pathways.

Application of pattern recognition to structure-activity problems: Use of minimal spanning tree

Abstract A graph-theoretical algorithm based on the minimal spanning tree (MST) is applied to structure—activity problems. The method is helpful in interpreting the results of cluster analysis, and becomes useful by combining with the mapping method that illustrates approximations of a multidimensional data structure. The antibacterial spectra of cephalosporins are analyzed by the MST approach and a linear mapping method. The main diameter obtained by MST gives the representative data set and clarifies the substituent effect on the antibacterial spectra. Relations between the central nervous system activity of benzodiazepine derivatives and their physicochemical parameters are also analyzed by MST and nonlinear mapping methods. These results for cephalosporins and benzodiazepines prove that MST is very useful in understanding the position of compounds in feature space and their activities.

Development of a new file search system for nuclear magnetic resonance spectra: Production of an Enlarged Data Base and Search Test

Abstract A practical search system for proton n.m.r. spectra is reported. The coding rules and search algorithms are described in detail. Data for 8000 spectra have been converted into a computer-readable file from printed charts. Several search tests are used to evaluate the usefulness of the search system, and various effects of experimental conditions such as different instruments, frequencies and solvents on recall efficiency are described. The results presented indicate that the system should be applicable to routine analytical work.