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This study investigates the integration of quantum mechanical (QM) descriptors with traditional structural descriptors to enhance the prediction of ADMET properties in drug candidates. The results demonstrate that incorporating QM descriptors significantly improves prediction accuracy, particularly for permeability and hERG inhibition, and provides better extrapolation capabilities in diverse chemical spaces. The findings suggest that a hybrid approach combining QM and structural descriptors can lead to mor

Author

Niladri Patra

Language

EN