QUANTUM MODELING OF SOME POTENT NON-TOXIC ANTI-TUBERCULOSIS COMPOUNDS
QUANTUM MODELING OF SOME POTENT NON-TOXIC ANTI-TUBERCULOSIS COMPOUNDS
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Date
2016-09
Authors
ERIC, GOWAL MUDIMA
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Abstract
A series of quinolone derivatives mainly 8-mehtylquinolones and Nitroquinolone were subjected to QSAR studies to correlate and predict their in-vitro biological activity- Minimal Inhibitory Concentration (MIC) - against Mycobacterium tuberculosis H37Rv (MTB) and Mycobacterium Smegmatis ATCC 14468 (MC2) as well as to predict their cytotoxicity in a mammalian vero cell reported as (IC50). The molecular geometries of all the structures were subjected to energy minimization using molecular mechanics (MM2) and then re-optimized by the density functional theory (DFT) with Becke‟s three-parameter hybrid functional using LYP correlation functional and the standard Pople‟s 6-311G* basis set. In Addition to PADEL descriptors, the parameters from quantum-chemical calculations were used. The genetic algorithm (GA) and multiple linear regression analysis (MLRA) were used to select the descriptors and to generate the correlation models that relate the structural features to the biological activities respectively. The final models were tested internally using the Leave-One-Out cross-validation and validated against the test set. Result of the QSAR study of 8-methylquinolone Carboxylic acids against Mycobacterium tuberculosis H37Rv shows that the best model has R2 = 0.90323; R2adjs = 0.88123; F = 41.0676; S = 0.2301 Q2LOO = 0.8311; R2Pred = 0.78708. Result of the QSAR study of 8-Methylquinolone carboxylic acid against Mycobacterium Smegmatis ATCC 14468 (MC2) shows the best model to have R2 = 0.9184; R2Adjs = 0.8990; F = 47.28523; s = 0.18902. The model has Q2LOO = 0.84987. It was externally validated by testing it on the test set and performed well with R2Pred = 0.79343. Results of the QSAR study of combination of 8-Methylquinolone Carboxylic acids and Nitroquinolones against Mycobacterium tuberculosis H37Rv (MTB) shows the best model have the following statistical parameters n = 35; R2 =0.90178; s = 0.22292; F = 42.84356; p < 0.0001; SPress = 2.46008;SDEP = 0.26512. The Q2LOO = 0.82634 shows that this model is internally stable. The model was externally validated and found to have good predictive ability with R2pred of 0.77462. The result of QSAR study of the in-vivo cytotoxicity (IC50) study of 8-Methylquinolones carboxylic acids shows the best model to have R2 = 0.97684; F =147.63356; S = 0.00716 SPress= . 0.00132 The internal validation shows the model to be internally stable with Q2LOO = 0.91459. The external validation shows this model to have an excellent predictive ability with R2Pred = 0.97829. The Y-randomization shows the model to have R2p = 0.868807. Analysis of the descriptors in the final models led to the conclusion that the factors that influence the development of the activity of the active compounds analyzed against Mycobacterium tuberculosis H37Rv and Mycobacterium smegmatis ATCC 14468 (MC2) are principally steric and electronic in nature. The most important descriptor for modeling the cytotoxicity of this group of compounds was AATS6p Average Broto-Moreau autocorrelation - lag 6 / weighted by polarizabilities. SpDiam_Dzv (Spectral diameter from Barysz matrix / weighted by van der Waals volumes. This is a weighted distance matrix accounting for the presence of heteroatoms and multiple bonds)
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A DISSERTATION SUBMITTED TO THE SCHOOL OF POSTGRADUATE STUDIES, AHMADU BELLO UNIVERSITY, ZARIA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE AWARD OF MASTER DEGREE IN PHYSICAL CHEMISTRY DEPARTMENT OF CHEMISTRY, FACULTY OF SCIENCE, AHMADU BELLO UNIVERSITY, ZARIA, NIGERIA
Keywords
QUANTUM MODELING,, NON-TOXIC,, ANTI-TUBERCULOSIS,, COMPOUNDS,