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Updated: Sep 17, 2025

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
Published on: June 20, 2025
Computational approaches to DMPK: A realistic assessment of current methods and their practical impact. Part I:
Koichi Handa1, Mariko Hirano1, Michiharu Kageyama1
1Axcelead Tokyo West Partners, Inc., Translational Science Group, 4-3-2 Asahigaoka, Hino-shi, Tokyo 191-0065, Japan.
Abstract:
Artificial intelligence and computational approaches have received considerable interest in recent years, and here we assess their real-world utility in drug discovery projects. We review recent in silico models in the area of drug metabolism and pharmacokinetics (DMPK), especially for physicochemical properties (pKa and logD) and in vitro assays [solubility (DMSO, Dried-DMSO, Powder), permeability (PAMPA, Caco-2, MDCK), metabolic stability (liver microsome, hepatocyte), and protein binding (plasma, microsome, brain)]. We discuss which are currently fit for purpose (and which are not), bridging both computational and experimental aspects in the early drug discovery stages. The review includes diverse aspects of obtaining data and model generation, as well as modeler/experimentalist interplay.
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