QSAR studies about cytotoxicity of benzophenazines with dual inhibition toward both topoisomerases I and II: 3D-MoRSE descriptors and statistical considerations about variable selection

• Published in: Bioorganic & medicinal chemistry Vol. 14; no. 21; pp. 7347 - 7358
• Main Authors: Saíz-Urra, Liane, González, Maykel Pérez, Teijeira, Marta
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01-11-2006; Elsevier Science
• Subjects: 3D-MoRSE descriptors; Antineoplastic agents; Benzophenazines; Biological and medical sciences; Cell Line, Tumor; Drug Screening Assays, Antitumor; Enzyme Inhibitors - chemistry; Enzyme Inhibitors - pharmacology; General aspects; Humans; Hydrogen Bonding; Medical sciences; Models, Molecular; Pharmacology. Drug treatments; Phenazines - chemistry; Phenazines - pharmacology; QSAR; Quantitative Structure-Activity Relationship; Topoisomerase I Inhibitors; Topoisomerase II Inhibitors; Topoisomerase inhibitors; Topoisomerase inhibitors; 3D-MoRSE descriptors; QSAR; Benzophenazines; Carcinoma; Lung; Cytotoxicity; Modeling; Isomerases; Structure activity relation; Multiple resistance; Molecular model; Mathematical model; Tumor cell; Human; DNA topoisomerase (ATP-hydrolysing); Enzyme; DNA topoisomerase; Prediction; Enzyme inhibitor; Malignant tumor; Regression analysis; In vitro; Multiple regression; Cell line; Topological index; Genetic algorithm; Tertiary amine; Carboxamide; Autocorrelation
• ISSN: 0968-0896; 1464-3391
• DOI: 10.1016/j.bmc.2006.05.081

A QSAR study was developed employing the 3D-MoRSE descriptors and a set of benzophenazines in order to model, the inhibition of the topoisomerases I and II, expressed by the cytotoxicity of these compounds (IC
50) against drug resistant human small cell lung carcinoma line cell H69/LX4. A comparison with other approaches such as the Topological, BCUT, Galvez topological charge indexes, 2D autocorrelations, Randic molecular profile, Geometrical, RDF and WHIM descriptors, was carried out.
Deoxyribonucleic acid (DNA) topoisomerases are involved in diverse cellular processes, such as replication, transcription, recombination, and chromosome segregation. Searching new compounds that inhibit both topoisomerases I and II is very important due to the deficiency of the specific inhibitors to overcome multidrug resistance (MDR). A QSAR study was developed, employing the 3D-MoRSE descriptors and a set of 64 benzophenazines in order to model the inhibition of the topoisomerases I and II, expressed by the cytotoxicity of these compounds (IC
50) versus drug-resistant human small cell lung carcinoma line cell H69/LX4. A comparison with other approaches such as the Topological, BCUT, Galvez topological charge indexes, 2D autocorrelations, Randić molecular profile, Geometrical, RDF, and WHIM descriptors was carried out. The mathematical models were obtained by means of the multiple regression analysis (MRA) and the variables were selected using the genetic algorithm. The model relative to the 3D-MoRSE descriptors was considered as the best, taking into account its statistical parameters. It was able to describe more than 82.2% of the variance in the experimental activity once the outliers were extracted.