Virtual screening and free energy estimation for identifying Mycobacterium tuberculosis flavoenzyme DprE1 inhibitors.
J Mol Graph Model
; 102: 107770, 2021 01.
Article
de En
| MEDLINE
| ID: mdl-33065513
ABSTRACT
In Mycobacterium tuberculosis (MTB), the cell wall synthesis flavoenzyme decaprenylphosphoryl-ß-d-ribose 2'-epimerase (DprE1) plays a crucial role in host pathogenesis, virulence, lethality and survival under stress. The emergence of different variants of drug resistant MTB are a major threat worldwide which essentially requires more effective new drug molecules with no major side effects. Here, we used structure based virtual screening of bioactive molecules from the ChEMBL database targeting DprE1, having bioactive 78,713 molecules known for anti-tuberculosis activity. An extensive molecular docking, binding affinity and pharmacokinetics profile filtering results in the selection four compounds, C5 (ChEMBL2441313), C6 (ChEMBL2338605), C8 (ChEMBL441373) and C10 (ChEMBL1607606) which may explore as potential drug candidates. The obtained results were validated with thirteen known DprE1 inhibitors. We further estimated the free-binding energy, solvation and entropy terms underlying the binding properties of DprE1-ligand interactions with the implication of MD simulation, MM/GBSA, MM/PBSA and MM/3D-RISM. Interestingly, we find that C6 shows the highest ΔG scores (-41.28 ± 3.51, -22.36 ± 3.17, -10.33 ± 5.70 kcal mol-1) in MM/GBSA, MM/PBSA and MM/3D-RISM assay, respectively. Whereas, the lowest ΔG scores (-35.31 ± 3.44, -13.67 ± 2.65, -3.40 ± 4.06 kcal mol-1) observed for CT319, the inhibitor co-crystallized with DprE1. Collectively, the results demonstrated that hit-molecules C5, C6, C8 and C10 having better binding free energy and molecular affinity as compared to CT319. Thus, we proposed that selected compounds may be explored as lead molecules in MTB therapy.
Mots clés
Texte intégral:
1
Collection:
01-internacional
Base de données:
MEDLINE
Sujet principal:
Tuberculose
/
Mycobacterium tuberculosis
Type d'étude:
Diagnostic_studies
/
Prognostic_studies
/
Screening_studies
Limites:
Humans
Langue:
En
Journal:
J Mol Graph Model
Sujet du journal:
BIOLOGIA MOLECULAR
Année:
2021
Type de document:
Article
Pays d'affiliation:
Inde