In Silico Assessment of Potential Geroprotectors: From Separate Endpoints to Complex Pharmacotherapeutic Effects
Leonid Stolbov1, Anastasia Rudik1, Alexey Lagunin1,2
1Institute of Biomedical Chemistry, 10 Bldg. 8, Pogodinskaya Str., 119121 Moscow, Russia.
Abstract:
This study presents an approach for the in silico assessment of potential geroprotectors that target the multifaceted mechanisms of aging, implemented in the PASS GERO web application. This work is timely given the societal impact of aging-the primary risk factor for major chronic diseases. The urgent need to extend healthspan-the period of life spent in good health-motivates the search for compounds that modulate fundamental aging mechanisms. The model estimates the probabilities of 117 aging-related biological activities with high predictive accuracy, achieving an average Invariant Accuracy of Prediction (IAP) of 0.967 under cross-validation. Validation using known geroprotectors (rapamycin, metformin, and resveratrol) demonstrated strong concordance between predicted activities and documented molecular mechanisms of action. For instance, the model correctly predicted rapamycin's inhibition of mTOR and metformin's activation of AMPK. The PASS GERO web application provides a systematic strategy to prioritize novel compound candidates for experimental evaluation in anti-aging research. We discuss challenges including the chemical diversity of the training data, the need for validated biomarkers, and the limitations of translating computational predictions into clinical outcomes, positioning the tool as robust application for activity profiling in discovery workflows.
Insights
This study introduces PASS GERO, a web tool for predicting anti-aging compounds by assessing 117 biological activities. It aids researchers in identifying potential geroprotectors to extend healthspan and combat age-related diseases.
Area of Science:
- Computational chemistry
- Gerontology
- Drug discovery
Background:
- Aging is the primary risk factor for chronic diseases, necessitating interventions to extend healthspan.
- Identifying compounds that modulate fundamental aging mechanisms is crucial for developing effective anti-aging strategies.
Purpose of the Study:
- To develop and validate an in silico approach for assessing potential geroprotectors.
- To implement this approach in the PASS GERO web application for prioritizing novel compound candidates.
Main Methods:
- Development of a predictive model for 117 aging-related biological activities.
- Utilizing the PASS GERO web application for in silico assessment.
- Cross-validation achieving an average Invariant Accuracy of Prediction (IAP) of 0.967.
Main Results:
- The model demonstrated high predictive accuracy for biological activities related to aging.
- Validation with known geroprotectors (rapamycin, metformin) showed accurate prediction of their molecular mechanisms (e.g., mTOR inhibition, AMPK activation).
Conclusions:
- The PASS GERO web application offers a systematic strategy for prioritizing compounds in anti-aging research.
- The tool serves as a robust application for activity profiling within drug discovery workflows, despite challenges in data diversity and clinical translation.
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