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Molecular modeling

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Cat. No. Product Name
  • HY-L097
    51 compounds

    Animal disease models are used in a variety of settings in basic research, such as studies on mechanisms of disease progression and evaluation new drugs. Animal models can be broadly classified into five categories: 1) experimental, 2) spontaneous, 3) negative, 4) orphan, 5) genetically engineered. Experimental models, which are induced artificially in the laboratory, are most common. Some small molecular compounds are usually used as inducers for animal models, such as Ceruletide for inflammatory model, Azoxymethane for tumor model. These inducers are useful tool in building animal models.

    MCE offers a unique collection of 51 animal model inducers, involving inflammatory model, tumor model, nervous disease model, etc. MCE Animal Disease Model library is a powerful tool for the establishment of animal disease models.

  • HY-L917
    5,000 compounds

    RNA is crucial for the regulation of numerous cellular processes and functions. With the in-depth study of disease mechanisms, processes such as RNA expression, splicing, translation, and stability regulation have become new targets for disease intervention. RNA has provided new therapeutic modalities for metabolic diseases, genetic disorders, and cancer patients, resulting in several innovative drugs.

    MCE R&D team collected small molecules targeting RNA from the PDB, R-BIND, ROBIN, and internal database as the positive dataset, and non-targeting RNA small molecules from ROBIN as the negative dataset. Based on the GeminiMol pre-trained model, we encoded the molecules and calculated over 1700 molecular descriptors using Mordred as inputs for the model. Subsequently, we employed 13 deep learning models to learn from the data. All of which yielded good training results, with AUROCs greater than 0.75. Ultimately, we selected the Finetune model to screen HY-L901P, which exhibited the best classification performance, achieving an AUROC of 0.82 and a prediction accuracy of 0.76. We then applied filtering based on StaR rules (with at least two of the following properties: cLogP ≥ 1.5, Molar Refractivity ≥ 4, Relative Polar Surface Area ≤ 0.3) to obtain a library containing approximately 5,000 small molecule compounds targeting RNA. This library serves as a valuable tool for screening small molecules that interact with RNA.

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