LogD7.4 prediction enhanced by transferring knowledge from chromatographic retention time, microscopic pKa and logP.

ABSTRACT: Lipophilicity is a fundamental physical property that significantly affects various aspects of drug behavior, including solubility, permeability, metabolism, distribution, protein binding, and toxicity. Accurate prediction of lipophilicity, measured by the logD7.4 value (the distribution coefficient between n-octanol and buffer at physiological pH 7.4), is crucial for successful drug discovery and design. However, the limited availability of data for logD modeling poses a significant challenge to achieving satisfactory generalization capability. To address this challenge, we have developed a novel logD7.4 prediction model called RTlogD, which leverages knowledge from multiple sources. RTlogD combines pre-training on a chromatographic retention time (RT) dataset since the RT is influenced b

SUBMITTER: Wang Y 

PROVIDER: S-EPMC10478446 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature