Investigating the potential anticancer activities of antibiotics as topoisomerase II inhibitors and DNA intercalators: in vitro, molecular docking, molecular dynamics, and SAR studies

Abstract

Topoisomerase II (TOP-2) is a promising molecular target for cancer therapy. Numerous antibiotics could interact with biologically relevant macromolecules and provoke antitumor potential. Herein, molecular docking studies were used to investigate the binding interactions of 138 antibiotics against the human topoisomerase II-DNA complex. Followed by the MD simulations for 200 ns and MM-GBSA calculations. On the other hand, the antitumor activities of the most promising candidates were investigated against three cancer cell lines using doxorubicin (DOX) as a reference drug. Notably, spiramycin (SP) and clarithromycin (CL) showed promising anticancer potentials on the MCF-7 cell line. Moreover, azithromycin (AZ) and CL exhibited good anticancer potentials against the HCT-116 cell line. Finally, the TOP-2 enzyme inhibition assay was carried out to confirm the proposed rationale. Briefly, potent TOP-2 inhibitory potentials were recorded for erythromycin (ER) and roxithromycin (RO). Additionally, a SAR study opened eyes to promising anticancer pharmacophores encountered by these antibiotics.

Highlights

• Molecular docking studies of 139 antibiotics against the topoisomerase II-DNA complex.

• SP, RO, AZ, CL, and ER were the most promising and commercially available candidates.

• Molecular dynamics simulations for 200 ns for the most promising five complexes.

• MM-GBSA calculations for the frontier five complexes.

• SP and CL showed promising anticancer potentials on the MCF-7 cell line, besides, AZ and CL exhibited good anticancer potentials against the HCT-116 cell line.

• Potent TOP-2 inhibitory potentials were recorded for ER and RO.

Graphical Abstract

Keywords:

• Antibiotics
• cytotoxicity
• topoisomerase II
• molecular docking and dynamics
• MM-GBSA

Acknowledgements

The authors would like to thank the Deanship of scientific research at Umm Al-Qura University for supporting this work by grant code (23UQU4290565DSR022), [email protected]. Also, the authors acknowledge the HPC, the University of Cape Town, for using supercomputing facilities.

Author contributions

Conceptualisation: Ahmed A. Al-Karmalawy; Data curation and formal analysis: Faten Farouk, Ayman Abo Elmaaty, Radwan Alnajjar, and Ahmed A. Al‐Karmalawy; Methodology: Faten Farouk, Ayman Abo Elmaaty, Haytham O. Tawfik, Radwan Alnajjar, Mohamed A. Saleh, and Ahmed A. Al‐Karmalawy; Project administration and supervision: Ahmed A. Al-Karmalawy; Resources, software, and validation: Faten Farouk, Ayman Abo Elmaaty, and Radwan Alnajjar; Writing – review & editing: Faten Farouk, Ayman Abo Elmaaty, Ahmed Elkamhawy, Haytham O. Tawfik, Radwan Alnajjar, Mohammed A. S. Abourehab, Wagdy M. Eldehna, and Ahmed A. Al‐Karmalawy. All authors approved the final version of the manuscript.

Disclosure statement

The authors report no conflicts of interest.

Additional information

Funding

This work was funded by the Deanship of Scientific Research at Umm Al-Qura University by grant code (23UQU4290565DSR022), [email protected].