Pharmacophore identification and bioactivity prediction for triaminotriazine derivatives by electron conformational-genetic algorithm QSAR method

• Published in: European journal of medicinal chemistry Vol. 45; no. 9; pp. 4157 - 4168
• Main Authors: Sarıpınar, Emin, Geçen, Nazmiye, Şahin, Kader, Yanmaz, Ersin
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Masson SAS 01.09.2010; Elsevier
• Subjects: Algorithms; Antineoplastic agents; Antineoplastic Agents - chemistry; Antineoplastic Agents - pharmacology; Biological and medical sciences; Drug design; Electron conformational method; Electrons; General aspects; Genetic algorithm; Genetics; HT29 Cells; Humans; Medical sciences; Models, Molecular; Molecular Conformation; Pharmacology. Drug treatments; Pharmacophore; QSAR; Quantitative Structure-Activity Relationship; Triaminotriazine; Triazines - chemistry; Triazines - pharmacology; Electron conformational method; Triaminotriazine; Drug design; QSAR; Genetic algorithm; Pharmacophore; Antineoplastic agent; Drug; Prediction; Morpholine derivatives; Electronic structure; Structure activity relation; Triazine derivatives; Molecular model; QSA; Conformation
• ISSN: 0223-5234; 1768-3254
• DOI: 10.1016/j.ejmech.2010.06.007

The electron conformational–genetic algorithm (EC–GA) method has been employed as a 4D-QSAR approach to reveal the pharmacophore (Pha) and to predict anticancer activity in the N-morpholino triaminotriazine derivatives. The electron conformational matrices of congruity (ECMCs) identified by electronic and structural parameters are constructed from data of conformational analysis and electronic structure calculation of molecules. Comparing the matrices, electron conformational submatrix of activity (ECSA, Pha) are revealed that are common for these compounds within a minimum tolerance. To predict the theoretical activity of training and test set and to select important variables for describing the activities, genetic algorithm and non-linear least square regression methods were applied. Regression coefficients were found 0.9708 for training and 0.9520 for test set. The electron–conformational genetic algorithm (EC–GA) method has been employed to reveal the pharmacophore (Pha) and to predict anticancer activity, studying in the class of triaminotriazine derivatives. [Display omitted]