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Results for "

learning performance

" in MedChemExpress (MCE) Product Catalog:

By Targets:	EGFR (1) Endogenous Metabolite (1) GABA Receptor (1) iGluR (2) nAChR (1)
By Research Areas:	Neurological Disease (6)

Inhibitors & Agonists

Screening Libraries

Inhibitory Antibodies

Cat. No.	Product Name	Target	Research Areas	Chemical Structure

HY-P99216

Ponezumab 1 Publications Verification PF-04360365; RN 1219	EGFR	Neurological Disease
Ponezumab (PF-04360365) is a humanised anti-amyloid IgG2 monoclonal antibody. Ponezumab reduces Aβ levels in the central nervous system and improves performance in mice in various models of learning and memory. Ponezumab can be used in study of Alzheimer's disease .

HY-19490

VQW-765 AQW-051	nAChR	Neurological Disease
VQW-765 (AQW-051) is a selective and orally active alpha-7 nicotinic acetylcholine receptor (α7-nAChR) agonist with a pK_D value of 7.56 to recombinantly expressed human α7-nAChR. VQW-765 shows anxiolytic-like effect in vivo. VQW-765 can be used for the research of anxiety disorder and acute performance anxiety .

HY-100782

DL-AP7 2-APH; 2-Amino-7-phosphonoheptanoic acid	iGluR	Neurological Disease
DL-AP7 is a competitive NMDA antagonist and an anticonvulsant. DL-AP7 blocks the NMDA-induced convulsions and impairs learning performance in a passive avoidance task in mice .

HY-120192

CGP 62349	GABA Receptor	Neurological Disease
CGP 62349 is a selective and orally active GABA_B receptor antagonist that improves cognitive performance in multiple learning paradigms .

HY-123904

UoS12258	iGluR	Neurological Disease
UoS12258 is a selective positive allosteric modulator of AMPA receptor. UoS12258 enhances AMPA receptor‐mediated synaptic transmission. UoS12258 improves performance in cognition rat models, including Scopolamine (HY-N0296)‐impaired rats and water maze learning and retention in aged rats .

HY-129245

Razobazam Hoe 175	Endogenous Metabolite	Neurological Disease
Razobazam (Hoe 175) is a benzodiazepine derivative with cognitive activity. Razobazam has been shown to improve learning performance in socially deprived rats. Razobazam increased avoidance scores by 18% after training. Razobazam caused significant changes in the optical density of certain areas of the rat brain, including a 22% decrease in the lateral habenula and a 25% increase in the ventral tegmental area. Razobazam also caused a 13% increase in optical density in the prefrontal cortex of rats .

Cat. No.	Product Name

HY-L917

RNA Binding Library	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.

RNA Binding Library

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.

Cat. No.	Product Name	Target	Research Area

HY-P99216

Ponezumab 1 Publications Verification PF-04360365; RN 1219	EGFR	Neurological Disease
Ponezumab (PF-04360365) is a humanised anti-amyloid IgG2 monoclonal antibody. Ponezumab reduces Aβ levels in the central nervous system and improves performance in mice in various models of learning and memory. Ponezumab can be used in study of Alzheimer's disease .

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