Background
Time consumed and expenses in discovering and synthesizing new hypothetical drugs with improved biological activity have been a major challenge toward the treatment of multi-drug-resistant strain Mycobacterium tuberculosis (TB). To solve the above problem, quantitative structure activity relationship (QSAR) is a recent approach developed to discover novel agents with better biological activity against M. tuberculosis.
Results
A validated QSAR model was developed in this study to predict the biological activities of some anti-tubercular compounds and to design new hypothetical drugs is influenced with the molecular descriptors, AATS7s, VR1_Dzi, VR1_Dzs, SpMin7_Bhe, and TDB8e, which has been validated through internal and external validation test. Prior to high anti-tubercular activity of the lead compound, compound 17 served as a template structure to design compounds with improved activity. Among the compounds designed, compounds 17i, 17j, and 17n were observed with improved anti-tubercular activities which ranges from 8.8981 to 9.0377 pBA.
Conclusion
The outcome of this research is recommended for pharmaceutical and medicinal chemists to synthesis and carry out an in vivo and in vitro screening for the proposed designed compounds in order to substantiate the computational findings.
Background: The reoccurrence of the resistant strains of Mycobacterium tuberculosis to available drugs/medications has mandated for the development of more effective anti-tubercular agents with efficient activities. Therefore, this work utilized the application of modeling technique to predict the inhibition activities of some prominent compounds which been reported to be efficient against M. tuberculosis. To accomplish the purpose of this work, multiple regression and genetic function approximation were adopted to create the model. Results: The established model was swayed with topological descriptors: MATS7s, SM1_DzZ, TDB3v, and RDF70v. More also, interactions between the compounds and the target "DNA gyrase" were evaluated via docking approach utilizing the PyRx and Discovery Studio simulated software. Meanwhile, compound 19 has the most perceptible binding affinity of − 16.5 kcal/mol. Consequently, compound 19 served as a reference structural template and insight to design twelve novel hypothetical agents with more competent activities. Meanwhile, compound 19h was observed with high activity among the designed compounds with more prominent binding affinities of − 21.6 kcal/ mol. Conclusion: Therefore, this research recommends in vivo, in vitro screening and pharmacokinetic properties to be carried out in order to determine the toxicity of the designed compounds.
Emergence of multi-drug resistant strains of Mycobacterium tuberculosis to the available drugs has demanded for the development of more potent anti-tubercular agents with efficient pharmacological activities. Time consumed and expenses in discovering and synthesizing new drug targets with improved biological activity have been a major challenge toward the treatment of multi-drug resistance strain M. tuberculosis. To solve the above problem, Quantitative Structure Activity Relationship (QSAR) is a recent approach developed to discover a novel drug with a better biological against M. Tuberculosis. A validated QSAR model developed in this study to predict the biological activities of some anti-tubercular compounds and to design new hypothetical drugs is influenced with the molecular descriptors; AATS7s, VR1-Dzi, VR1-Dzs, SpMin7-Bhe and RDF110i. The internal validation test for the derived model was found to have correlation coefficient (R2) of 0.8875, adjusted correlation coefficient (R2adj) value of 0.8234 and leave one out cross validation coefficient (Qcv2) value of 0.8012 while the external validation test was found to have (R2test) of 0.7961 and Y-randomization Coefficient (cRp2) of 0.6832. Molecular docking shows that ligand 13 of 2,4-disubstituted quinoline derivatives have promising higher binding score of -18.8 kcal/mol compared to the recommended drugs; isoniazid -14.6 kcal/mol. The proposed QSAR model and molecular docking studies will provides valuable approach for the modification of the lead compound, designing and synthesis more potent anti-tubercular agents.
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