Predicting drug metabolism: experiment and/or computation?

By Johannes Kirchmair, Andreas H. Göller, D. Lang, Jens Kunze, Bernard Testa, Ian A. Wilson, Robert C. Glen, Gisbert Schneider. Nature reviews. Drug discovery, 2015

448 citations recorded by the source corpus.

Drug metabolism can produce metabolites with physicochemical and pharmacological properties that differ substantially from those of the parent drug, and consequently has important implications for both drug safety and efficacy. To reduce the risk of costly clinical-stage attrition due to the metabolic characteristics of drug candidates, there is a need for efficient and reliable ways to predict drug metabolism in vitro, in silico and in vivo. In this Perspective, we provide an overview of the state of the art of experimental and computational approaches for investigating drug metabolism. We highlight the scope and limitations of these methods, and indicate strategies to harvest the synergies that result from combining measurement and prediction of drug metabolism.

Subfields: Computational Theory and Mathematics, Molecular Biology, Pharmacology

View Paper: https://www.semanticscholar.org/paper/90d2cdc68da6425ea470e47e6271eb1c42c426be

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Citations in the corpus

Rethinking drug design in the artificial intelligence era (2019, background): “This problem is important, as a reliable toxicology model may be able to reduce the time and cost of drug discovery as well as the need for animal testing 20,21 .”
eDoctor: machine learning and the future of medicine (2018, background): “Drug discovery and pharmacokinetic prediction have been enhanced with ML and deep learning techniques [40], a fact that Gawehn et al. [41] expanded upon in their review of deep learning in drug discovery, claiming that the addition of this tool is ‘game-changing’ and will be useful in toxicity…”
DrugBank 5.0: a major update to the DrugBank database for 2018 (2017, background): “It has also become much more robust and sophisticated (21).”
SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules (2017, unknown): “Inhibition of these isoenzymes is certainly one major cause of pharmacokinetics-related drug-drug interactions 47,48 leading to toxic or other unwanted adverse effects due to the lower clearance and accumulation of the drug or its metabolites 49 .”
Chemistry42: An AI-Driven Platform for Molecular Design and Optimization (2023, methodology): “The Structure Morphing module contains two components: a rule-based Metabolic Stability Enhancer 22 that addresses metabolic instability caused by potential sites of metabolism in the generated structures and the Bioisostere Module that performs bioisosteric/isosteric transformations.”