Cardiovascular diseases (CVDs) remain a leading cause of mortality in modern society, with factors such as sedentary lifestyles, unhealthy diets, and obesity contributing to their increasing prevalence. The widespread use of Statins for lipid-lowering therapy in both primary and secondary cardiovascular prevention is anticipated to rise in response to this trend. Given the rapid escalation in the prevalence of Statin usage, it is imperative to understand their toxicological effects on public health. While previous studies have explored various pharmacological effects of statins, comprehensive investigations into their genotoxic and Mutagenic potential are lacking. In this study, we conducted a comprehensive In silico evaluation of Statins using four different toxicological assessment programs, focusing on various genotoxicity, carcinogenicity, Mutagenicity, and Micronucleus formation endpoints. By comparing program outputs with experimental data, we assessed the reliability of In silico Toxicity predictions and discussed the consistency among different platforms. Our findings suggest discrepancies among the predictions of different programs, highlighting the importance of integrating multiple sources of data and methodologies in Toxicity evaluations. Despite inconsistencies, integrating in silico predictions with future in vitro and in vivo studies can contribute to a better understanding of the toxicological properties of statins and ensure their safe usage. This study underscores the necessity of careful evaluation and utilization of multiple data sources in decision-making regarding the toxicological profile of statins. Ultimately, leveraging in silico methods to guide future comprehensive toxicological studies will enhance our understanding of Statins' safety profiles and contribute to public health research.
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Primary Language | English |
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Subjects | Biochemistry and Cell Biology (Other) |
Journal Section | Research Articles |
Authors | |
Project Number | - |
Early Pub Date | November 21, 2024 |
Publication Date | |
Submission Date | May 2, 2024 |
Acceptance Date | November 11, 2024 |
Published in Issue | Year 2024 Volume: 28 Issue: 6 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.