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Identification of DprE1 inhibitors for tuberculosis through integrated in-silico approaches.
Dash, Swagatika; Rathi, Ekta; Kumar, Avinash; Chawla, Kiran; Kini, Suvarna G.
Afiliación
  • Dash S; Department of Pharmaceutical Chemistry, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, India, 576104.
  • Rathi E; Department of Pharmaceutical Chemistry, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, India, 576104.
  • Kumar A; Department of Medical Affairs, Curie Sciences Private Limited, Samastipur, Bihar, India, 848125.
  • Chawla K; Department of Microbiology, Kasturba Medical College, Manipal Academy of Higher Education, Manipal, Karnataka, India, 576104.
  • Kini SG; Department of Pharmaceutical Chemistry, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, India, 576104. suvarna.gk@manipal.edu.
Sci Rep ; 14(1): 11315, 2024 05 17.
Article en En | MEDLINE | ID: mdl-38760437
ABSTRACT
Decaprenylphosphoryl-ß-D-ribose-2'-epimerase (DprE1), a crucial enzyme in the process of arabinogalactan and lipoarabinomannan biosynthesis, has become the target of choice for anti-TB drug discovery in the recent past. The current study aims to find the potential DprE1 inhibitors through in-silico approaches. Here, we built the pharmacophore and 3D-QSAR model using the reported 40 azaindole derivatives of DprE1 inhibitors. The best pharmacophore hypothesis (ADRRR_1) was employed for the virtual screening of the chEMBL database. To identify prospective hits, molecules with good phase scores (> 2.000) were further evaluated by molecular docking studies for their ability to bind to the DprE1 enzyme (PDB 4KW5). Based on their binding affinities (< - 9.0 kcal/mole), the best hits were subjected to the calculation of free-binding energies (Prime/MM-GBSA), pharmacokinetic, and druglikeness evaluations. The top 10 hits retrieved from these results were selected to predict their inhibitory activities via the developed 3D-QSAR model with a regression coefficient (R2) value of 0.9608 and predictive coefficient (Q2) value of 0.7313. The induced fit docking (IFD) studies and in-silico prediction of anti-TB sensitivity for these top 10 hits were also implemented. Molecular dynamics simulations (MDS) were performed for the top 5 hit molecules for 200 ns to check the stability of the hits with DprE1. Based on their conformational stability throughout the 200 ns simulation, hit 2 (chEMBL_SDF357100) was identified as the best hit against DprE1 with an accepted safety profile. The MD results were also in accordance with the docking score, MM-GBSA value, and 3D-QSAR predicted activity. The hit 2 molecule, (N-(3-((2-(((1r,4r)-4-(dimethylamino)cyclohexyl)amino)-9-isopropyl-9H-purin-6-yl)amino)phenyl)acrylamide) could serve as a lead for the discovery of a novel DprE1 inhibiting anti-TB drug.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Relación Estructura-Actividad Cuantitativa / Simulación del Acoplamiento Molecular / Antituberculosos Idioma: En Revista: Sci Rep Año: 2024 Tipo del documento: Article Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Relación Estructura-Actividad Cuantitativa / Simulación del Acoplamiento Molecular / Antituberculosos Idioma: En Revista: Sci Rep Año: 2024 Tipo del documento: Article Pais de publicación: Reino Unido