AIMC Topic: Drug Discovery

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A Machine Learning Algorithm Suggests Repurposing Opportunities for Targeting Selected GPCRs.

International journal of molecular sciences Sep 23, 2024
Repurposing utilizes existing drugs with known safety profiles and discovers new uses by combining experimental and computational approaches. The integration of computational methods has greatly advanced drug repurposing, offering a rational approach...
Receptors, G-Protein-Coupled Drug Repositioning Algorithms Humans Ligands Drug Discovery Machine Learning
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Research Progresses and Applications of Knowledge Graph Embedding Technique in Chemistry.

Journal of chemical information and modeling Sep 20, 2024
A knowledge graph (KG) is a technique for modeling entities and their interrelations. Knowledge graph embedding (KGE) translates these entities and relationships into a continuous vector space to facilitate dense and efficient representations. In the...
Humans Databases, Chemical Cheminformatics Neural Networks, Computer Drug Discovery
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Deep-Learning-Driven Discovery of SN3-1, a Potent NLRP3 Inhibitor with Therapeutic Potential for Inflammatory Diseases.

Journal of medicinal chemistry Sep 20, 2024
The NLRP3 inflammasome plays a central role in the pathogenesis of various intractable human diseases, making it an urgent target for therapeutic intervention. Here, we report the development of SN3-1, a novel orally potent NLRP3 inhibitor, designed ...
Mice Humans Inflammation Drug Discovery Animals Structure-Activity Relationship Mice, Inbred C57BL Inflammasomes NLR Family, Pyrin Domain-Containing 3 Protein Deep Learning Crystallography, X-Ray Male
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SSR-DTA: Substructure-aware multi-layer graph neural networks for drug-target binding affinity prediction.

Artificial intelligence in medicine Sep 17, 2024
Accurate prediction of drug-target binding affinity (DTA) is essential in the field of drug discovery. Recently, scientists have been attempting to utilize artificial intelligence prediction to screen out a significant number of ineffective compounds...
Proteins Humans Drug Discovery Neural Networks, Computer Protein Binding
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In Silico Insights: QSAR Modeling of TBK1 Kinase Inhibitors for Enhanced Drug Discovery.

Journal of chemical information and modeling Sep 17, 2024
TBK1, or TANK-binding kinase 1, is an enzyme that functions as a serine/threonine protein kinase. It plays a crucial role in various cellular processes, including the innate immune response to viruses, cell proliferation, apoptosis, autophagy, and an...
Drug Discovery Protein Serine-Threonine Kinases Quantitative Structure-Activity Relationship Protein Kinase Inhibitors Humans Models, Molecular Machine Learning Computer Simulation
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GPCRSPACE: A New GPCR Real Expanded Library Based on Large Language Models Architecture and Positive Sample Machine Learning Strategies.

Journal of medicinal chemistry Sep 17, 2024
The quest for novel therapeutics targeting G protein-coupled receptors (GPCRs), essential in numerous physiological processes, is crucial in drug discovery. Despite the abundance of GPCR-targeting drugs, many receptors lack selective modulators, indi...
Small Molecule Libraries Drug Discovery Receptors, G-Protein-Coupled Humans Machine Learning
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Combined Physics- and Machine-Learning-Based Method to Identify Druggable Binding Sites Using SILCS-Hotspots.

Journal of chemical information and modeling Sep 16, 2024
Identifying druggable binding sites on proteins is an important and challenging problem, particularly for cryptic, allosteric binding sites that may not be obvious from X-ray, cryo-EM, or predicted structures. The Site-Identification by Ligand Compet...
Protein Conformation Binding Sites Molecular Dynamics Simulation Ligands Machine Learning Protein Binding Proteins Drug Discovery
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Automated design of multi-target ligands by generative deep learning.

Nature communications Sep 11, 2024
Generative deep learning models enable data-driven de novo design of molecules with tailored features. Chemical language models (CLM) trained on string representations of molecules such as SMILES have been successfully employed to design new chemical...
Humans Deep Learning Proteins Models, Chemical Drug Design Drug Discovery Ligands Polypharmacology
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Kinase Drug Discovery: Impact of Open Science and Artificial Intelligence.

Molecular pharmaceutics Sep 6, 2024
Given their central role in signal transduction, protein kinases (PKs) were first implicated in cancer development, caused by aberrant intracellular signaling events. Since then, PKs have become major targets in different therapeutic areas. The prefe...
Drug Discovery Humans Protein Kinases Protein Kinase Inhibitors Signal Transduction Artificial Intelligence
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An artificial intelligence accelerated virtual screening platform for drug discovery.

Nature communications Sep 5, 2024
Structure-based virtual screening is a key tool in early drug discovery, with growing interest in the screening of multi-billion chemical compound libraries. However, the success of virtual screening crucially depends on the accuracy of the binding p...
Drug Discovery Protein Binding Drug Evaluation, Preclinical Artificial Intelligence Molecular Docking Simulation Humans Ubiquitin-Protein Ligases Small Molecule Libraries Ligands Crystallography, X-Ray NAV1.7 Voltage-Gated Sodium Channel
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