Dataset Information

Gonzalez2021 - QSAR Prediction Model for CYP2C9 Inhibitor and Substrate

ABSTRACT: Analysis of metabolic stability, determining the inhibition of CYP2C9 activity and whether the compounds are a substrate for the CYP2C9 enzyme. The data used to build these models has been publicly available at PubChem (AID1645842) by ADME@NCATS. Model type: Predictive machine learning model. Model relevance: The model predicts a chemical compound as an inihibitor and substrate of the CYP2C9 enzymes. Model encoded by: Zakia Yahya (Ersilia) Metadata submitted in BioModels by: Zainab Ashimiyu-Abdusalam Implementation of this model code by Ersilia is available here: https://github.com/ersilia-os/eos5jz9

SUBMITTER: Zainab Ashimiyu-Abdusalam

PROVIDER: MODEL2404160002 | BioModels | 2024-04-16

REPOSITORIES: BioModels

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Publications

Development of Robust Quantitative Structure-Activity Relationship Models for CYP2C9, CYP2D6, and CYP3A4 Catalysis and Inhibition.

Gonzalez Eric E Jain Sankalp S Shah Pranav P Torimoto-Katori Nao N Zakharov Alexey A Nguyễn Ðắc-Trung ÐT Sakamuru Srilatha S Huang Ruili R Xia Menghang M Obach R Scott RS Hop Cornelis E C A CECA Simeonov Anton A Xu Xin X

Drug metabolism and disposition: the biological fate of chemicals 20210628 9

Cytochrome P450 enzymes are responsible for the metabolism of >75% of marketed drugs, making it essential to identify the contributions of individual cytochromes P450 to the total clearance of a new candidate drug. Overreliance on one cytochrome P450 for clearance levies a high risk of drug-drug interactions; and considering that several human cytochrome P450 enzymes are polymorphic, it can also lead to highly variable pharmacokinetics in the clinic. Thus, it would be advantageous to understand ...[more]

PMID: 34183376

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Project description:Treating recurrent GBM is a clinical challenge due to its highly resistant and aggressive nature. In order to develop new therapeutic targets for recurrent GBM a better understanding of its molecular landscape is necessary. Here we used a cellular model, developed in our lab which generates paired primary and recurrent samples from GBM cell lines and primary patient samples hence allowing us to compare the molecular differences between the two populations. Total RNA seq analysis of parent and recurrent population of two cell lines and one patient sample revealed a significant upregulation of Extracellular matrix interaction in recurrent population. Since matrix stiffness plays a pivotal role in cell-ECM interaction and downstream signaling, we developed a system that mimicked the brain like substrate stiffness by using collagen coated polyacrylamide-based substrate whose stiffness can be modified from normal brain (0.5kPa) to tumorigenic (10kPa). Using these substrates, we were able to capture the morphological and physiological differences between parent and recurrent GBM which were not evident on plastic surfaces (~1 GPa). On 0.5kPa, unlike circular parent cells, recurrent GBM cells showed two morphologies (circular and elongated). The recurrent cells growing on 0.5kPa also showed higher proliferation, invasion, migration and in-vivo tumorigenicity in orthotropic GBM mouse model, compared to parent cells. Furthermore, recurrent cells exhibited elevated velocity irrespective of substrate stiffness, which indicated that recurrent cells may possess inherent differential mechanosignalling ability which was reflected by higher expression of ECM proteins like Collagen IVA, MMP2 and MMP9. Moreover, mice brain injected with recurrent cells grown on 0.5kPa substrate showed higher Young’s modulus values suggesting that recurrent cells conditioned on 0.5kPa make the surrounding ECM stiffer. Importantly, inhibition of EGFR signaling, that is amplified with tissue stiffening in GBM resulted in decreased invasion, migration and proliferation in 0.5kPa recurrent cells, but interestingly survival remained unaffected, highlighting the importance of mimicking the physiological stiffness of the brain mimicking clinical scenario. Total RNA seq analysis of parent and recurrent cells grown on plastic and 0.5kPa substrate identified PLEKHA7 as significantly upregulated gene specifically in 0.5kPa recurrent sample. Higher protein expression of PLEKHA7 in recurrent GBM as compared to primary GBM was validated in patient biopsies. Accordingly, PLEKHA7 knockdown reduced invasion and survival of recurrent GBM cells. Together, these data provides a model system that captures the differential mechanosensing signals of primary and recurrent GBM cells and identifies a novel potential target specific for recurrent GBM.

Dataset Information

Gonzalez2021 - QSAR Prediction Model for CYP2C9 Inhibitor and Substrate

Publications

Development of Robust Quantitative Structure-Activity Relationship Models for CYP2C9, CYP2D6, and CYP3A4 Catalysis and Inhibition.

Similar Datasets

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