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Comparison of various methods for validity evaluation of QSAR models
Shadi Shayanfar1, Ali Shayanfar2,3
1Student Research Committee, Faculty of Pharmacy, Tabriz University of Medical Sciences, Tabriz, Iran.
BMC Chemistry
|August 23, 2022
Summary
External validation of quantitative structure-activity relationship (QSAR) models is crucial for drug discovery. Relying solely on metrics like r-squared is insufficient for determining QSAR model reliability.
Area of Science:
- Computational chemistry
- Medicinal chemistry
- Drug discovery
Background:
- Quantitative structure-activity relationship (QSAR) modeling is vital in drug discovery.
- External validation assesses QSAR model reliability for predicting new compound activity.
- Various external validation criteria exist in scientific literature.
Purpose of the Study:
- To evaluate the sufficiency of current external validation criteria for QSAR models.
- To analyze the reliability of QSAR models based on statistical parameters.
- To identify limitations in QSAR model validation methodologies.
Main Methods:
- Collected 44 reported QSAR models from scientific publications.
- Calculated various statistical parameters for external validation.
- Discussed the implications of the calculated parameters.
Main Results:
- The coefficient of determination (r²) alone is inadequate for validating QSAR models.
- Established external validation criteria present both advantages and disadvantages.
- A comprehensive approach is needed for QSAR model assessment.
Conclusions:
- Current external validation methods are not sufficient on their own to determine QSAR model validity.
- Consideration of multiple criteria and their limitations is essential for robust QSAR studies.
- Further refinement of validation strategies is necessary for reliable drug discovery predictions.
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