Preprint
Something for Nothing: Improved Solvation Free Energy Prediction with Δ-Learning
Abstract
Molecular solubility is among the key properties that determine the clinical performance of a drug candidate because poor molecular solubility often indicates inadequate bioavailability. Using the CombiSolv-Exp database, we test several models (Gaussian process regression, decision trees, k-nearest neighbors) for hydration free energies by integrating Δ-Learning and a universal quantum-chemistry continuum solvation model, SMD. The optimal model …
Authors
Meng F; Zhang H; Collins-Ramirez JS; Ayers PW
DOI
10.21203/rs.3.rs-2604981/v1
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