Insilico toxicity prediction by using ProTox-II computational tools

Abstract

Background Computational methods transform chemical safety assessment, offering efficient toxicity prediction. Swift and accurate analysis improves safety evaluations, benefiting drug development and regulatory compliance. Methods ProTox-II integrates computational techniques to predict chemical toxicity endpoints, leveraging machine learning, pharmacophores, and diverse experimental data. Models are meticulously validated for accuracy on independent datasets. Results ProTox-II's validated models ensure accurate toxicity prediction. Accessible via the web, it serves toxicologists, agencies, chemists, and stakeholders, providing comprehensive insights including toxicity radar charts, compound similarity, and detailed toxicity profiles with confidence scores. Conclusion ProTox-II is crucial for the pharmaceutical and regulatory sectors, enhancing safety evaluations and regulatory compliance. Leveraging computational techniques, it accelerates drug discovery, serving as an essential tool for mitigating toxicity risks and advancing chemical safety assessment.