In-silico studies of anti-tuberculosis drugs using advanced computational technique: A DFT, molecular docking, and QSAR analysis

Cancer remains the number one health care challenge worldwide with an estimation of 1 in 9 people developing cancer in their lifetime. The aim of the study was to investigate the anticancer and antimetastatic effects of Leptospermum petersonii’s active compounds against pancreatic and prostate cancer cells. The following techniques were employed: thin-layer chromatography, column and nuclear magnetic resonance chromatography, AlamarBlue assay, ATP assay, wound healing assay, Hoechst Staining, caspase assay, Agarose gel (DNA fragmentation analysis), and RT-PCR. Through cell viability assay and IC??, approximately 100 μg/ml for the methanolic crude extract was identified with a greater cytotoxic effect on MIA PaCa-2 than PC3 cells. The ethyl acetate extract showed cytotoxicity indices IC?? > 100 μg/ml signifying that 60% of the cells were viable even at a dose of 100 μg/ml and thus led to the termination of additional testing because of its ineffective potency. Caspase 3/7 assay and DNA fragmentation had shown some positive results in support of apoptosis. Wound healing demonstrated untreated cells healed the gap in 24 hours, whereas treated cells took longer to do so. Gene expression showed upregulation of RB1 and checkpoint 1 which are necessary for DNA damage and apoptosis induction. In conclusion, the results suggest that there might be compounds within L. petersonii extracts that can be exploited for anticancer agents.

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Publication Details

Journal
Journal of Applied Pharmaceutical Science
Published
2025-01-01
DOI
https://doi.org/10.7324/japs.2025.v15.i12.13
Primary Topic
Computational Drug Discovery Methods
Type
article
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article

In-silico studies of anti-tuberculosis drugs using advanced computational technique: A DFT, molecular docking, and QSAR analysis

Bhavana Panthi, Indra Sen Ram, Anwesh Pandey, Samiyara Begum et al.
Journal of Applied Pharmaceutical Science
Computational Drug Discovery Methods
article

In-silico studies of anti-tuberculosis drugs using advanced computational technique: A DFT, molecular docking, and QSAR analysis

Bhavana Panthi, Indra Sen Ram, Anwesh Pandey, Samiyara Begum, Suresh Kumar
article en

Abstract

Cancer remains the number one health care challenge worldwide with an estimation of 1 in 9 people developing cancer in their lifetime. The aim of the study was to investigate the anticancer and antimetastatic effects of Leptospermum petersonii’s active compounds against pancreatic and prostate cancer cells. The following techniques were employed: thin-layer chromatography, column and nuclear magnetic resonance chromatography, AlamarBlue assay, ATP assay, wound healing assay, Hoechst Staining, caspase assay, Agarose gel (DNA fragmentation analysis), and RT-PCR. Through cell viability assay and IC??, approximately 100 μg/ml for the methanolic crude extract was identified with a greater cytotoxic effect on MIA PaCa-2 than PC3 cells. The ethyl acetate extract showed cytotoxicity indices IC?? > 100 μg/ml signifying that 60% of the cells were viable even at a dose of 100 μg/ml and thus led to the termination of additional testing because of its ineffective potency. Caspase 3/7 assay and DNA fragmentation had shown some positive results in support of apoptosis. Wound healing demonstrated untreated cells healed the gap in 24 hours, whereas treated cells took longer to do so. Gene expression showed upregulation of RB1 and checkpoint 1 which are necessary for DNA damage and apoptosis induction. In conclusion, the results suggest that there might be compounds within L. petersonii extracts that can be exploited for anticancer agents.

Journal of Applied Pharmaceutical Science
Openalex Percentile: Top 71%
Computational Drug Discovery Methods
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In-silico studies of anti-tuberculosis drugs using advanced computational technique: A DFT, molecular docking, and QSAR analysis — Bhavana Panthi, Indra Sen Ram, et al. · Journal of Applied Pharmaceutical Science (2025) | TGRS Research Map | TGRS