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Benzimidazoles

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Preparation of a chemiluminescence sensor for multi-detection of benzimidazoles in meat based on molecularly imprinted polymer.

Food chemistry
In this study, a molecularly imprinted polymer capable of recognizing 8 benzimidazoles was first synthesized. The computation simulation showed that the shape and size of used template were the main factors influencing its recognition ability. Then t...

Prediction of Farnesoid X Receptor Disruptors with Machine Learning Methods.

Chemical research in toxicology
The farnesoid X receptor (FXR) emerges as a promising drug target involved in regulating various metabolic pathways, yet some xenobiotic compounds binding to FXR would be an important determinant to induce the receptor dysfunctions that lead to undes...

Molecular docking and machine learning analysis of Abemaciclib in colon cancer.

BMC molecular and cell biology
BACKGROUND: The main challenge in cancer research is the identification of different omic variables that present a prognostic value and personalised diagnosis for each tumour. The fact that the diagnosis is personalised opens the doors to the design ...

Trace Identification and Visualization of Multiple Benzimidazole Pesticide Residues on Leaves Using Terahertz Imaging Combined with Deep Learning.

International journal of molecular sciences
Molecular spectroscopy has been widely used to identify pesticides. The main limitation of this approach is the difficulty of identifying pesticides with similar molecular structures. When these pesticide residues are in trace and mixed states in pla...

Inter-laboratory automation of the in vitro micronucleus assay using imaging flow cytometry and deep learning.

Archives of toxicology
The in vitro micronucleus assay is a globally significant method for DNA damage quantification used for regulatory compound safety testing in addition to inter-individual monitoring of environmental, lifestyle and occupational factors. However, it re...

In silico formulation prediction of drug/cyclodextrin/polymer ternary complexes by machine learning and molecular modeling techniques.

Carbohydrate polymers
Ternary cyclodextrin (CD) complexes (drug/CD/polymer) can effectively improve the solubility of water-insoluble drugs with large size than binary CD formulations. However, ternary formulations are screened by a trial-and-error approach, which is labo...

Deep learning-based design and screening of benzimidazole-pyrazine derivatives as adenosine A receptor antagonists.

Journal of biomolecular structure & dynamics
The Adenosine A receptor (AAR) is considered a novel potential target for the immunotherapy of cancer, and AAR antagonists have an inhibitory effect on tumor growth, proliferation, and metastasis. In our previous studies, we identified a class of ben...