Back

Breaking barriers: A new phytomedicine based treatment approach for targeted unrevealed non-canonical DNA structures in tuberculosis bacteria.

Bhowmik, S.; Shroff, T.; Bag, S.; Kadam, P.; Mistry, N.

2025-04-10 biophysics
10.1101/2025.04.08.647720 bioRxiv
Show abstract

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), remains a critical global health issue, complicated by the emergence of multi-drug-resistant (MDR) and extensively drug-resistant (XDR) strains. Current treatments involve prolonged use of first- and second-line drugs, which are associated with severe side effects and poor patient adherence. Non-canonical DNA structures, such as G-quadruplexes (GQ) and i-Motifs (iM), play a vital role in regulating Mtbs virulence, stress responses, and drug resistance mechanisms, making them attractive targets for therapy. Flavonoids, naturally occurring polyphenolic compounds found in various fruits and vegetables have demonstrated the ability to enhance the effectiveness of traditional TB drugs while minimizing cytotoxicity. By employing biophysical techniques including UV-Vis absorption spectroscopy, binding constant determination, and thermal melting experiments, this study investigates the interaction between two flavonoids, quercetin and kaempferol and non-canonical DNA structures (GQ and iM) within the Mtb genome. Key GQ/iM sequences from Mtb genes associated with drug resistance were identified and evaluated for their binding with flavonoids. Results revealed that quercetin and kaempferol preferentially interact with specific cyp51 GQ, dnaB GQ, espB GQ, espE GQ, SigA iM, fabH iM, psk5 iM DNA sequences, as indicated by significant changes in absorption spectra. The calculated binding constants showed strong affinities for these specific DNA structures. Thermal melting experiments further indicated that flavonoids increased the thermal stability of these particular GQ and iM DNA, suggesting stabilization via strong stacking interactions. These findings highlight the potential of flavonoids as promising agents to target GQ/iM DNA structures, offering a new strategy for addressing Mtb drug resistance and virulence.

Matching journals

The top 9 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.