Abstract

BackgroundThe 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.ResultsThe 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.ConclusionTherefore, 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.

Highlights

  • 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

  • Anti-tubercular drugs recommended for treating tuberculosis include the following: rifampicin, pyrazinamide, para-aminosalicylic acid, and isoniazide (Adeniji et al 2020a)

  • Reports have shown that patients do not respond positively to the administered drugs due to the resistance strain of Mycobacterium tuberculosis toward the current drugs

Read more

Summary

Introduction

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. 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. Anti-tubercular drugs recommended for treating tuberculosis include the following: rifampicin, pyrazinamide, para-aminosalicylic acid, and isoniazide (Adeniji et al 2020a). Reports have shown that patients do not respond positively to the administered drugs due to the resistance strain of Mycobacterium tuberculosis toward the current drugs. Most of these drugs have been reported with adverse side effect (Adeniji et al 2020a). The pursuit of novel anti-tubercular agents with enhanced and efficient properties/activities with minimum side effects against

Methods
Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call