AIMC Topic: Receptors, Adrenergic, alpha-2

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DeepADRA2A: predicting adrenergic α2a inhibitors using deep learning.

Journal of biomolecular structure & dynamics Oct 14, 2023
Adrenergic α2a (ADRA2A) receptors play a crucial role in modulating various physiological actions, thereby influencing the proper functioning of different systems in the body. ADRA2A regulation is associated with a wide range of effects, including al...
Humans Machine Learning Algorithms Drug Discovery Deep Learning Receptors, Adrenergic, alpha-2 Adrenergic alpha-2 Receptor Antagonists
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Ligand- and Structure-Based Analysis of Deep Learning-Generated Potential α2a Adrenoceptor Agonists.

Journal of chemical information and modeling Jan 6, 2021
The α2a adrenoceptor is a medically relevant subtype of the G protein-coupled receptor family. Unfortunately, high-throughput techniques aimed at producing novel drug leads for this receptor have been largely unsuccessful because of the complex pharm...
Deep Learning Ligands Receptors, Adrenergic, alpha-2 Medetomidine
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Predicting Methylphenidate Response in ADHD Using Machine Learning Approaches.

The international journal of neuropsychopharmacology May 10, 2015
BACKGROUND: There are no objective, biological markers that can robustly predict methylphenidate response in attention deficit hyperactivity disorder. This study aimed to examine whether applying machine learning approaches to pretreatment demographi...
Humans Brain Prognosis Female Male Child Treatment Outcome Support Vector Machine Age Factors Magnetic Resonance Imaging Lead Cotinine Body Weight Rest Polymorphism, Genetic Central Nervous System Stimulants Attention Deficit Disorder with Hyperactivity Methylphenidate Drug Therapy, Computer-Assisted Norepinephrine Plasma Membrane Transport Proteins Receptors, Adrenergic, alpha-2 Stroop Test
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