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Similarity based SAR (SIBAR) as tool for early ADME profiling
Christian Klein1, Dominik Kaiser, Stephan Kopp
1Institute of Pharmaceutical Chemistry, University of Vienna, Althanstrasse 14, A-1090 Wien, Austria.
Journal of Computer-Aided Molecular Design
|June 27, 2003
Summary
A novel SIBAR approach using similarity calculations effectively predicts P-glycoprotein (Pgp) inhibitory activity. This method enhances early drug discovery by modeling drug transport and absorption, distribution, metabolism, and excretion (ADME) properties.
Area of Science:
- Drug discovery and development
- Pharmacology
- Computational chemistry
Background:
- Accurate estimation of bioavailability and toxicity is crucial in early drug discovery.
- Drug transport proteins like P-glycoprotein (Pgp) significantly influence ADME properties.
- Traditional QSAR methods struggle with the diverse ligands of Pgp.
Purpose of the Study:
- To develop a predictive model for Pgp-inhibitory activity using a novel approach.
- To assess the utility of SIBAR descriptors for early ADME profiling.
- To overcome limitations of traditional QSAR for diverse Pgp ligands.
Main Methods:
- Utilized a SIBAR (Similarity-Based Approach) based on similarity calculations to reference compounds.
- Generated SIBAR descriptors from similarity values to a diverse reference set.
- Employed Partial Least Squares (PLS) analysis for model building.
- Validated models using cross-validation and an external test set of 31 compounds.
Main Results:
- Achieved models with good predictivity for Pgp-inhibitory activity in a set of 131 propafenone analogues.
- Demonstrated the effectiveness of SIBAR descriptors in predicting activity.
- Validated the predictive power on an independent external test set.
Conclusions:
- The SIBAR approach offers a versatile tool for generating predictive ADME models.
- This method shows promise for early assessment of drug transport and potential drug-drug interactions.
- SIBAR descriptors can aid in overcoming challenges associated with diverse compound libraries in drug discovery.