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Cytochrome P-450 CYP3A

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Excipient knowledgebase: Development of a comprehensive tool for understanding the disposition and interaction potential of common excipients.

CPT: pharmacometrics & systems pharmacology
Although the use of excipients is widespread, a thorough understanding of the drug interaction potential of these compounds remains a frequent topic of current research. Not only can excipients alter the disposition of coformulated drugs, but it is l...

Application of Deep Neural Network Models in Drug Discovery Programs.

ChemMedChem
In silico driven optimization of compound properties related to pharmacokinetics, pharmacodynamics, and safety is a key requirement in modern drug discovery. Nowadays, large and harmonized datasets allow to implement deep neural networks (DNNs) as a ...

Dietary Inhibitors of CYP3A4 Are Revealed Using Virtual Screening by Using a New Deep-Learning Classifier.

Journal of agricultural and food chemistry
CYP3A4 is the main human enzyme responsible for phase I metabolism of dietary compounds, prescribed drugs and xenobiotics, steroid hormones, and bile acids. The inhibition of CYP3A4 activity might impair physiological mechanisms, including the endocr...

Prediction of Cytochrome P450 Inhibition Using a Deep Learning Approach and Substructure Pattern Recognition.

Journal of chemical information and modeling
Cytochrome P450 (CYP) is a family of enzymes that are responsible for about 75% of all metabolic reactions. Among them, CYP1A2, CYP2C9, CYP2C19, CYP2D6, and CYP3A4 participate in the metabolism of most drugs and mediate many adverse drug reactions. T...

An Uncertainty-Guided Deep Learning Method Facilitates Rapid Screening of CYP3A4 Inhibitors.

Journal of chemical information and modeling
Cytochrome P450 3A4 (CYP3A4), a prominent member of the P450 enzyme superfamily, plays a crucial role in metabolizing various xenobiotics, including over 50% of clinically significant drugs. Evaluating CYP3A4 inhibition before drug approval is essent...

Evaluation of machine learning models for cytochrome P450 3A4, 2D6, and 2C9 inhibition.

Journal of applied toxicology : JAT
Cytochrome P450 (CYP) enzymes are involved in the metabolism of approximately 75% of marketed drugs. Inhibition of the major drug-metabolizing P450s could alter drug metabolism and lead to undesirable drug-drug interactions. Therefore, it is of great...

Deep Learning Models Compared to Experimental Variability for the Prediction of CYP3A4 Time-Dependent Inhibition.

Chemical research in toxicology
Most drugs are mainly metabolized by cytochrome P450 (CYP450), which can lead to drug-drug interactions (DDI). Specifically, time-dependent inhibition (TDI) of CYP3A4 isoenzyme has been associated with clinically relevant DDI. To overcome potential D...

Application of machine learning models for property prediction to targeted protein degraders.

Nature communications
Machine learning (ML) systems can model quantitative structure-property relationships (QSPR) using existing experimental data and make property predictions for new molecules. With the advent of modalities such as targeted protein degraders (TPD), the...

Advanced Mass-Spectra-Based Machine Learning for Predicting the Toxicity of Traditional Chinese Medicines.

Analytical chemistry
Traditional Chinese medicine (TCM) has been a cornerstone of health care for centuries, valued for its preventive and therapeutic properties. However, recent decades have revealed significant toxicological concerns associated with TCMs due to their c...

Functional Imaging of CYP3A4 at Multiple Dimensions Using an AI-Driven High Performance Fluorogenic Substrate.

Small (Weinheim an der Bergstrasse, Germany)
Cytochrome P450 3A4 (CYP3A4) is a key mediator in xenobiotic metabolism and drug-drug interactions (DDI), developing orally active fluorogenic substrates for sensing and imaging of a target enzyme in biological systems remains challenging. Here, an a...