Quantitative Structure-Activity Relationship (QSAR) modeling is a computational method that predicts the biological activity or properties of chemical compounds based on their molecular structure, establishing mathematical relationships between chemical features and observed effects. Research published in In-vitro I…
Quantitative Structure-Activity Relationship (QSAR) modeling is a computational method that predicts the biological activity or properties of chemical compounds based on their molecular structure, establishing mathematical relationships between chemical features and observed effects. Research published in In-vitro In-vivo In-silico Journal addresses QSAR modeling across drug discovery and toxicological applications. The journal has featured work examining the integration of computational approaches with experimental validation in drug design, exploring how structural modifications influence pharmacological outcomes. Historical perspectives on structure-activity relationships have been documented through analyses of sulfonamide compounds, tracing how early observations of structural variations and their biological consequences informed modern QSAR principles. Additionally, the journal has published research applying QSAR methodologies to environmental health, including the derivation of exposure thresholds for toxic substances like cadmium, where structure-based predictions help establish safe concentration limits for acute and intermediate duration exposures. This topic matters because QSAR modeling reduces the time and cost of identifying promising drug candidates and assessing chemical hazards, enabling researchers to screen large numbers of compounds computationally before committing resources to laboratory testing, thereby accelerating therapeutic development and improving chemical safety assessment.
3 peer-reviewed articles, ranked by relevance. Each links to its DOI.
The 3 articles above have been cited 11 times in the scholarly literature. Citation data via OpenAlex and Crossref, updated Jun 2026.
A sample of recent works citing this journal's research on Quantitative Structure-activity Relationship Modeling, linking to each citing work.