Pasha, Farhan A. Chung, Hwan W. Kang, Soon B. Cho, Seung J. 2024-01-21T00:00:58Z 2024-01-21T00:00:58Z 2021-09-03 2008-02 0020-7608 https://pubs.kist.re.kr/handle/201004/133787 The computational analyses of pyrido-di-indoles have been performed with various methods such as quantum mechanical studies (AM1, PM3, and DFT) and 3D-QSAR analyses (CoMFA and CoMSIA). The electrophilicity index along with some other properties has been related with biological activities. Electrostatic field has been identified as an important descriptor from the 3D-QSAR analyses. The AM1 geometry and Gasteiger-Marsili charged base CoMFA (r(predictive)(2) = 0.75) and CoMSIA (r(predictive)(2) 0.62) give strong correlation and indicate that a substitution at sites 2 and 3 of Ring A might affect the activity. In addition, a plausible statistical model has been found with DFT-based local philicity and negative Fukui function with a value of r(2) = 0.82 and r(cv)(2) = 0.60. The DFT analysis indicates that electron density of nitrogen atom of Ring B significantly contributes to activity. (C) 2007 Wiley Periodicals, Inc. English WILEY SEMIEMPIRICAL METHODS ATOMIC SOFTNESS 3D QSAR COMFA OPTIMIZATION PARAMETERS BINDING PREDICT MODELS HELP 3D-quantitative structure activity analysis and quantum chemical analysis of pyrido-di-indoles Article 10.1002/qua.21474 1 INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY, v.108, no.2, pp.391 - 400 INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY 108 2 391 400 scie scopus 000251723500022 2-s2.0-37149011343 Chemistry, Physical Mathematics, Interdisciplinary Applications Quantum Science & Technology Physics, Atomic, Molecular & Chemical Chemistry Mathematics Physics Article SEMIEMPIRICAL METHODS ATOMIC SOFTNESS 3D QSAR COMFA OPTIMIZATION PARAMETERS BINDING PREDICT MODELS HELP 3D-QSAR CoMFA DFT pyrido-di-indoles