BIOLOGICAL ACTIVITIES WITH IN SILICO STUDY OF BTDE COMPOUND AS INHIBITORS OF MYCOBACTERIUM TUBERCULOSIS PROTEIN-TARGETS, ADME AND DFT CALCULATIONS

Tuberculosis caused by Mycobacterium is currently treated with chemotherapeutic antibiotics. A new molecule, β-hydroxytriazole, was evaluated as a Mycobacterium Tuberculosis inhibitor. Our strategy was to evaluate this compound for its optimized properties against Mycobacterium Tuberculosis. In this study, with 6-311++G(d,p) base set under the B3LYP/B3PW91 techniques, the target molecule 1-(1-benzyl-1H-1,2,3-triazol-4-yl)-2-(2,4-dichlorophenyl) ethane-1,2-dione (BTDE) was optimized and its energy parameters were analyzed using density functional calculation (DFT). In addition to the optimized structure of the molecule, many quantum chemical parameters; HOMO-LUMO, MEP, Intramolecular electronic interactions and mullikene atomic charges were calculated and the obtained data were visualized. HOMO-LUMO analysis revealed that the molecule has NLO properties to a significant extent, with energy ranges close to each other in the basis sets used (-7.304/-7.368 eV) and (-1.349/-1.277 eV). The molecular docking analysis and pharmacological potential of BTDE compound were evaluated against the KasA enzymes of Mycobacterium tuberculosis. The results indicated that the compound exhibited strong binding affinities, with docking scores of -6.798 and -6.788 kcal/mol for the respective receptors. These findings suggest that the compound may serve as a promising inhibitor of these critical enzymes, highlighting its potential in tuberculosis treatment.

Authors

Institutions

Publication Details

Journal
Eskişehir Teknik Üniversitesi Bilim ve Teknoloji Dergisi B - Teorik Bilimler
Published
2025-08-25
DOI
https://doi.org/10.20290/estubtdb.1566835
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

BIOLOGICAL ACTIVITIES WITH IN SILICO STUDY OF BTDE COMPOUND AS INHIBITORS OF MYCOBACTERIUM TUBERCULOSIS PROTEIN-TARGETS, ADME AND DFT CALCULATIONS

Ahmet Çağrı Ata, Ümit Yıldıko
Eskişehir Teknik Üniversitesi Bilim ve Teknoloji Dergisi B - Teorik Bilimler
Computational Drug Discovery Methods
article

BIOLOGICAL ACTIVITIES WITH IN SILICO STUDY OF BTDE COMPOUND AS INHIBITORS OF MYCOBACTERIUM TUBERCULOSIS PROTEIN-TARGETS, ADME AND DFT CALCULATIONS

Ahmet Çağrı Ata, Ümit Yıldıko
article en

Abstract

Tuberculosis caused by Mycobacterium is currently treated with chemotherapeutic antibiotics. A new molecule, β-hydroxytriazole, was evaluated as a Mycobacterium Tuberculosis inhibitor. Our strategy was to evaluate this compound for its optimized properties against Mycobacterium Tuberculosis. In this study, with 6-311++G(d,p) base set under the B3LYP/B3PW91 techniques, the target molecule 1-(1-benzyl-1H-1,2,3-triazol-4-yl)-2-(2,4-dichlorophenyl) ethane-1,2-dione (BTDE) was optimized and its energy parameters were analyzed using density functional calculation (DFT). In addition to the optimized structure of the molecule, many quantum chemical parameters; HOMO-LUMO, MEP, Intramolecular electronic interactions and mullikene atomic charges were calculated and the obtained data were visualized. HOMO-LUMO analysis revealed that the molecule has NLO properties to a significant extent, with energy ranges close to each other in the basis sets used (-7.304/-7.368 eV) and (-1.349/-1.277 eV). The molecular docking analysis and pharmacological potential of BTDE compound were evaluated against the KasA enzymes of Mycobacterium tuberculosis. The results indicated that the compound exhibited strong binding affinities, with docking scores of -6.798 and -6.788 kcal/mol for the respective receptors. These findings suggest that the compound may serve as a promising inhibitor of these critical enzymes, highlighting its potential in tuberculosis treatment.

Eskişehir Teknik Üniversitesi Bilim ve Teknoloji Dergisi B - Teorik BilimlerVol. 13(2)
Kafkas University (TR)
Openalex Percentile: Top 77%
Computational Drug Discovery Methods
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.