Advances and Applications in Bioinformatics and Chemistry (Apr 2023)
Facing Antitubercular Resistance: Identification of Potential Direct Inhibitors Targeting InhA Enzyme and Generation of 3D-pharmacophore Model by in silico Approach
Abstract
Ghyzlane EL Haddoumi,1,2 Mariam Mansouri,1,2 Houda Bendani,1,2 El Mehdi Bouricha,1,2 Ilham Kandoussi,1,2 Lahcen Belyamani,2– 4 Azeddine Ibrahimi1– 3 1Biotechnology Lab (MedBiotech), Rabat Medical and Pharmacy School, University Mohammed V, Rabat, Morocco; 2Centre Mohammed VI for Research & Innovation (CM6), Rabat, Morocco; 3Mohammed VI University of Health Sciences (UM6SS), Casablanca, Morocco; 4Emergency Department, Military Hospital Mohammed V, Rabat, MoroccoCorrespondence: Azeddine Ibrahimi, Mohammed VI University of Health Sciences (UM6SS), Casablanca, Morocco, Tel +212660240131, Email [email protected]: The enoyl-acyl carrier protein reductase (InhA) is one of the important key enzymes employed in mycolic acids biosynthesis pathway and an important component of mycobacterial cell walls. This enzyme has also been identified as major target of isoniazid drug, except that isoniazid needs to be activated first by the catalase peroxidase (KatG) protein to form the isonicotinoyl-NAD (INH-NAD) adduct that inhibits the action of InhA enzyme. However, this activation becomes more difficult and unreachable with the problem of mutation-related resistance caused mainly by acquired mutations in KatG and InhA protein. Our main interest in this study is to identify direct InhA inhibitors using computer-aided drug design.Methods: Computer-aided drug design was used to solve this problem by applying three different approaches including mutation impact modelling, virtual screening and 3D-pharmacophore search.Results: A total of 15 mutations were collected from the literature, then a 3D model was generated for each of them and their impact was predicted. Of the 15 mutations, 10 were found to be deleterious and have a direct effect on flexibility, stability and SASA of the protein. In virtual screening, from 1,000 similar INH-NAD analogues obtained by the similarity search method, 823 compounds passed toxicity filter and drug likeness rules, which were then docked to the wild-type of InhA protein. Subsequently, 34 compounds with binding energy score better than that of INH-NAD were selected and docked against the 10 generated mutated models of InhA. Only three leads showed a lower binding affinity better than the reference. The 3D-pharmacophore model approach was used to identify the common features between those three compounds by generating a pharmacophoric map.Conclusion: The result of this study may pave the way to develop more potent mutant-specific inhibitors to overcome this resistance.Keywords: molecular docking, CADD, Mycobacterium tuberculosis, InhA, mutational profile
