SApredictor

SApredictor identifies and catalogs structural alerts (SAs) to screen and interpret chemical toxicity by detecting substructures associated with toxicological endpoints.


Key Features:

  • Structural Alerts Database: A comprehensive database of structural alerts (SAs) representing chemical substructures associated with toxicological properties.
  • Interpretable, rule-based screening: Uses SA-based screening to provide interpretable assessments and to address limitations of black-box machine learning.
  • Substructure identification and visualization: Identifies and visually highlights key molecular substructures responsible for predicted toxicity.
  • Support for structural optimization: Highlights alerts to guide medicinal chemistry modifications aimed at reducing toxicity while retaining desired properties.
  • Rapid and accurate evaluation: Enables rapid screening and evaluation of compounds against known structural alerts.

Scientific Applications:

  • Toxicity Prediction: Estimating potential toxicity endpoints in new or existing compounds by mapping SAs to known hazards.
  • Drug Design: Informing medicinal chemistry optimization by identifying and mitigating toxic substructures in drug candidates.
  • Chemical Safety Assessment: Supporting safety evaluations and regulatory hazard assessment through interpretable SA-based evidence.

Methodology:

Collecting, storing, and utilizing structural alerts by identifying critical substructures and performing targeted SA-based screenings with integrated visualization of alerts.

Topics

Details

Cost:
Free of charge
Tool Type:
web application
Operating Systems:
Mac, Linux, Windows
Programming Languages:
SAS
Added:
10/9/2022
Last Updated:
11/24/2024

Operations

Publications

Hua Y, Cui X, Liu B, Shi Y, Guo H, Zhang R, Li X. SApredictor: An Expert System for Screening Chemicals Against Structural Alerts. Frontiers in Chemistry. 2022;10. doi:10.3389/fchem.2022.916614. PMID:35910729. PMCID:PMC9326022.

PMID: 35910729
PMCID: PMC9326022
Funding: - National Natural Science Foundation of China: 81803433