Analysis of Pharmacological Activity for Antituberculosis Drugs by Electronic-Structure Data Mining

Abstract

We aim at developing an analytical method for data mining which would be useful for molecular design and discovery in Chemistry and Pharmaceutical Sciences. We have developed a program for electronic-structure data mining to automatically discover a mathematical correlation function between an electronic descriptor and a chemical property. This program uses the electronic factors obtained by electronic-structure calculation, by performing a simple linear regression analysis and multivariate analysis is to explore the regularity of chemistry. Electronic factors to be used for analysis are orbital energy, excitation energy, oscillator strength, transition dipole moment, dipole moment, ionization energy, and the electron affinity. Using this electronic-structure data mining, an analysis was carried out for pyrazinamide derivatives that are anti-tuberculosis drugs. A large number of function fittings, it has been shown that the best fitting is obtained when the orbital energy of the molecular orbital localized on the benzene moiety is chosen as a descriptor.