Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Analogue-based approaches in anti-cancer compound modelling: the relevance of QSAR models | Bohari et al. Organic and Medicinal Chemistry Letters 2011 1 3 http content 1 1 3 o Organic and Medicinal Chemistry Letters a SpringerOpen Journal ORIGINAL Open Access Analogue-based approaches in anti-cancer compound modelling the relevance of QSAR models Mohammed Hussaini Bohari Hemant Kumar Srivastava and Garikapati Narahari Sastry Abstract Background QSAR is among the most extensively used computational methodology for analogue-based design. The application of various descriptor classes like quantum chemical molecular mechanics conceptual density functional theory DFT - and docking-based descriptors for predicting anti-cancer activity is well known. Although in vitro assay for anti-cancer activity is available against many different cell lines most of the computational studies are carried out targeting insufficient number of cell lines. Hence statistically robust and extensive QSAR studies against 29 different cancer cell lines and its comparative account has been carried out. Results The predictive models were built for 266 compounds with experimental data against 29 different cancer cell lines employing independent and least number of descriptors. Robust statistical analysis shows a high correlation cross-validation coefficient values and provides a range of QSAR equations. Comparative performance of each class of descriptors was carried out and the effect of number of descriptors 1-10 on statistical parameters was tested. Charge-based descriptors were found in 20 out of 39 models approx. 50 valency-based descriptor in 14 approx. 36 and bond order-based descriptor in 11 approx. 28 in comparison to other descriptors. The use of conceptual DFT descriptors does not improve the statistical quality of the models in most cases. Conclusion Analysis is done with various models where the number of descriptors is increased from 1 to 10 it is interesting to note that in most cases 3 descriptor-based models are adequate. The study reveals that .
