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Shah2020 - Predicting liver cytosol stability of small molecules.

ABSTRACT: The human liver cytosol stability model is used for predicting the stability of a drug in the cytosol of human liver cells, which is beneficial for identifying potential drug candidates early during the drug discovery process. If a drug compound is quickly absorbed, it may not reach the intended target in the body or become toxic. On the other hand, if a drug compound is too stable, it could accumulate and cause detrimental effects. The authors use an NCATS dataset of 1450 compounds screened in vitro in mouse and human cytosol fractions. Compounds were classified as stable (half-life > 30min) or unstable (half-life ≤ 30 min). Note that authors report the dataset was biased towards stable compounds. Model Type: Machine learning model. Model Relevance: Predicts probability of a compound stability due to liver cells metabolism. Model Encoded by: Pauline (Ersilia) Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam Implementation of this model code by Ersilia is available here: https://github.com/ersilia-os/eos9yy1

SUBMITTER: Zainab Ashimiyu-Abdusalam  

PROVIDER: MODEL2404220005 | BioModels | 2024-04-22

REPOSITORIES: BioModels

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Predicting liver cytosol stability of small molecules.

Shah Pranav P   Siramshetty Vishal B VB   Zakharov Alexey V AV   Southall Noel T NT   Xu Xin X   Nguyen Dac-Trung DT  

Journal of cheminformatics 20200407 1

Over the last few decades, chemists have become skilled at designing compounds that avoid cytochrome P (CYP) 450 mediated metabolism. Typical screening assays are performed in liver microsomal fractions and it is possible to overlook the contribution of cytosolic enzymes until much later in the drug discovery process. Few data exist on cytosolic enzyme-mediated metabolism and no reliable tools are available to chemists to help design away from such liabilities. In this study, we screened 1450 co  ...[more]

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