SerotoninAI

SerotoninAI predicts pKi values and pharmacokinetic properties from molecular SMILES to evaluate compound affinity for serotonin receptors and transporters.

Key Features:

• Affinity Prediction: Predicts pKi values for major serotonergic targets, including serotonin receptors and transporters.
• SMILES Input: Accepts molecular structures encoded as SMILES for compound-level predictions.
• Pharmacokinetic Property Prediction: Estimates blood-brain barrier penetration and human intestinal absorption.

Scientific Applications:

• Drug Discovery Prioritization: Use predicted pKi values to rank and prioritize candidate ligands targeting the serotonergic system.
• CNS Pharmacokinetics Assessment: Use blood-brain barrier penetration predictions to assess potential central nervous system exposure.
• Absorption Evaluation: Use human intestinal absorption predictions to inform assessments of oral uptake potential.

Methodology:

Predictions of pKi and pharmacokinetic properties are computed from molecular structures provided as SMILES.