article · Scientific Reports
Breast cancer remains a leading cause of cancer-related mortality in women globally, driving the search for effective therapies with fewer side effects. An integrated computational investigation evaluated novel 1,2,4-triazine-3(2H)-one derivatives as targeted inhibitors of tubulin, a key protein involved in cancer cell division. The research combined quantitative structure-activity relationship modelling, ADMET profiling, molecular docking, and 100-nanosecond molecular dynamics simulations. Statistical models achieved an R-squared predictive accuracy of 0.849, revealing that absolute electronegativity and water solubility strongly influence inhibitory activity. Docking analyses identified promising candidates, notably compound Pred28 with a binding score of minus 9.6 kcal/mol. Further simulations confirmed the structural stability of Pred28, showing low root mean square deviation of 0.29 nanometres and fluctuation values reflecting a tightly bound conformation to tubulin, pointing to candidates for future laboratory synthesis.
Tubulin is an essential protein for cancer cell division, making it a critical target for anticancer drugs. By using computational modelling to screen and evaluate molecular structures prior to physical synthesis, researchers can streamline early drug discovery for breast cancer. This targeted approach identifies candidate compounds that are most likely to bind effectively and remain structurally stable.
This work represents very early-stage computational discovery for oncology therapeutics. Medicinal chemists and pharmaceutical developers could use the computational profiles, particularly for candidate Pred28, to guide physical synthesis and in vitro validation. Because the results are entirely computational, the compounds are far from clinical or market application and require rigorous laboratory testing and preclinical trials before commercialisation pathways can open.
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Abstract Breast cancer remains a leading cause of cancer-related deaths among women globally, necessitating the development of more effective therapeutic agents with minimal side effects. This study explores novel 1,2,4-triazine-3(2H)-one derivatives as potential inhibitors of Tubulin, a pivotal protein in cancer cell division, highlighting a targeted approach in cancer therapy. Using an integrated computational approach, we combined quantitative structure–activity relationship (QSAR) modeling, ADMET profiling, molecular docking, and molecular dynamics simulations to evaluate and predict the efficacy and stability of these compounds. Our QSAR models, developed through rigorous statistical analysis, revealed that descriptors such as absolute electronegativity and water solubility significantly influence inhibitory activity, achieving a predictive accuracy (R 2 ) of 0.849. Molecular docking studies identified compounds with high binding affinities, particularly Pred28, which exhibited the best docking score of − 9.6 kcal/mol. Molecular dynamics simulations conducted over 100 ns provided further insights into the stability of these interactions. Pred28 demonstrated notable stability, with the lowest root mean square deviation (RMSD) of 0.29 nm and root mean square fluctuation (RMSF) values indicative of a tightly bound conformation to Tubulin. The novelty of this work lies in its methodological rigor and the integration of multiple advanced computational techniques to pinpoint compounds with promising therapeutic potential. Our findings advance the current understanding of Tubulin inhibitors and open avenues for the synthesis and experimental validation of these compounds, aiming to offer new solutions for breast cancer treatment.
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DOI: 10.1038/s41598-024-66877-2
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