Abstract B119: Chemo-informatics and cytotoxicity characterization of novel rhenium complexes for potential triple-negative breast cancer management

Abstract Chemotherapy has been the mainstay treatment modality for managing metastatic breast cancer, including the triple-negative subtype. However, the recent development of resistance in these malignant tumors to conventional cytotoxic drugs has made it necessary to search for new pharmacological agents to combat this deadly disease. We screened for the cytotoxic potentials of two novel rhenium complexes, PR6 and PR7, on MCF 7 cells and triple-negative MDA-MB-468 breast cancer subtypes and later characterized their chemo-informatics properties, including their possible interactions with apoptosis regulatory proteins. MCF7 and MDA-MB-468 cells were given 2.5 µM of PR6 or 1.5 µM of PR7 for 72 hours, and then we checked how many cells were still alive using an MTS-based cell viability test. The molecular interactions of the novel rhenium ligands with BAX, BCL-2, and MCL-1 apoptosis-regulatory proteins alongside the standard carboplatin drug and the target protein inhibitors were investigated using Maestro and GROMAC software-based molecular docking and molecular dynamics simulation in silico analyses. The ligands’ pharmacodynamic and pharmacokinetic properties were predicted using the Deep PK Web server. Our results established that PR6 and PR7 exert cytotoxic effects on the selected breast cancer cells. Furthermore, the novel rhenium ligands demonstrated acceptable pharmacodynamic and pharmacokinetic properties, predicting them as promising drug-like candidates. PR6, PR7, and the carboplatin drug were observed to interact with all the target proteins, with the highest binding interaction and strongest affinity with the BCL-2 protein recorded for the rhenium ligands. In conclusion, PR6 and PR7 rhenium complexes demonstrate promising potential as therapeutic agents for breast cancer management, and direct interaction with apoptosis regulatory proteins is hereby predicted to be the mechanism underlying their anticancer activities. Citation Format: John Abiodun. Obadipe, Santosh Mandal, Taiwo Ooreoluwa. Ojo, Olawale Quadri. Bolaji, Abdeen Tunde. Ogunlana, Bor-Jang Hwang, Yusuf Mansur. Liadi, Alexis Green, Valerie Odero-Marah. Chemo-informatics and cytotoxicity characterization of novel rhenium complexes for potential triple-negative breast cancer management [abstract]. In: Proceedings of the 18th AACR Conference on the Science of Cancer Health Disparities; 2025 Sep 18-21; Baltimore, MD. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2025;34(9 Suppl):Abstract nr B119.

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Journal
Cancer Epidemiology Biomarkers & Prevention
Published
2025-09-18
DOI
https://doi.org/10.1158/1538-7755.disp25-b119
Primary Topic
Computational Drug Discovery Methods
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article
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article

Abstract B119: Chemo-informatics and cytotoxicity characterization of novel rhenium complexes for potential triple-negative breast cancer management

Yusuf Liadi, Taiwo Ooreoluwa Ojo, Alexis Green, Abdeen Tunde Ogunlana et al.
Cancer Epidemiology Biomarkers & Prevention
Computational Drug Discovery Methods
article

Abstract B119: Chemo-informatics and cytotoxicity characterization of novel rhenium complexes for potential triple-negative breast cancer management

Yusuf Liadi, Taiwo Ooreoluwa Ojo, Alexis Green, Abdeen Tunde Ogunlana, John Abiodun Obadipe, Bor-Jang Hwang, Valerie Odero‐Marah, Santosh Kumar Mandal, Olawale Quadri Bolaji
article en

Abstract

Abstract Chemotherapy has been the mainstay treatment modality for managing metastatic breast cancer, including the triple-negative subtype. However, the recent development of resistance in these malignant tumors to conventional cytotoxic drugs has made it necessary to search for new pharmacological agents to combat this deadly disease. We screened for the cytotoxic potentials of two novel rhenium complexes, PR6 and PR7, on MCF 7 cells and triple-negative MDA-MB-468 breast cancer subtypes and later characterized their chemo-informatics properties, including their possible interactions with apoptosis regulatory proteins. MCF7 and MDA-MB-468 cells were given 2.5 µM of PR6 or 1.5 µM of PR7 for 72 hours, and then we checked how many cells were still alive using an MTS-based cell viability test. The molecular interactions of the novel rhenium ligands with BAX, BCL-2, and MCL-1 apoptosis-regulatory proteins alongside the standard carboplatin drug and the target protein inhibitors were investigated using Maestro and GROMAC software-based molecular docking and molecular dynamics simulation in silico analyses. The ligands’ pharmacodynamic and pharmacokinetic properties were predicted using the Deep PK Web server. Our results established that PR6 and PR7 exert cytotoxic effects on the selected breast cancer cells. Furthermore, the novel rhenium ligands demonstrated acceptable pharmacodynamic and pharmacokinetic properties, predicting them as promising drug-like candidates. PR6, PR7, and the carboplatin drug were observed to interact with all the target proteins, with the highest binding interaction and strongest affinity with the BCL-2 protein recorded for the rhenium ligands. In conclusion, PR6 and PR7 rhenium complexes demonstrate promising potential as therapeutic agents for breast cancer management, and direct interaction with apoptosis regulatory proteins is hereby predicted to be the mechanism underlying their anticancer activities. Citation Format: John Abiodun. Obadipe, Santosh Mandal, Taiwo Ooreoluwa. Ojo, Olawale Quadri. Bolaji, Abdeen Tunde. Ogunlana, Bor-Jang Hwang, Yusuf Mansur. Liadi, Alexis Green, Valerie Odero-Marah. Chemo-informatics and cytotoxicity characterization of novel rhenium complexes for potential triple-negative breast cancer management [abstract]. In: Proceedings of the 18th AACR Conference on the Science of Cancer Health Disparities; 2025 Sep 18-21; Baltimore, MD. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2025;34(9 Suppl):Abstract nr B119.

Cancer Epidemiology Biomarkers & PreventionVol. 34(9_Supplement)
University of Ibadan (NG), Morgan State University (US)
Openalex Percentile: Top 73%
Computational Drug Discovery Methods
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