AIMC Topic: Small Molecule Libraries

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The prediction of RNA-small molecule binding sites in RNA structures based on geometric deep learning.

International journal of biological macromolecules Apr 21, 2025
Biological interactions between RNA and small-molecule ligands play a crucial role in determining the specific functions of RNA, such as catalysis and folding, and are essential for guiding drug design in the medical field. Accurately predicting the ...
Deep Learning Computational Biology Models, Molecular Small Molecule Libraries RNA Ligands Nucleic Acid Conformation Binding Sites
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Prediction of Chromatographic Retention Time of a Small Molecule from SMILES Representation Using a Hybrid Transformer-LSTM Model.

Journal of chemical information and modeling Mar 28, 2025
Accurate retention time (RT) prediction in liquid chromatography remains a significant consideration in molecular analysis. In this study, we explore the use of a transformer-based language model to predict RTs by treating simplified molecular input ...
Neural Networks, Computer Chromatography, Reverse-Phase Time Factors Small Molecule Libraries Chromatography, High Pressure Liquid
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Leveraging Transfer Learning for Predicting Protein-Small-Molecule Interaction Predictions.

Journal of chemical information and modeling Mar 24, 2025
A complex web of intermolecular interactions defines and regulates biological processes. Understanding this web has been particularly challenging because of the sheer number of actors in biological systems: ∼10 proteins in a typical human cell offer ...
Small Molecule Libraries Neural Networks, Computer Machine Learning Proteins Ligands Protein Binding Humans
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Rapid traversal of vast chemical space using machine learning-guided docking screens.

Nature computational science Mar 13, 2025
The accelerating growth of make-on-demand chemical libraries provides unprecedented opportunities to identify starting points for drug discovery with virtual screening. However, these multi-billion-scale libraries are challenging to screen, even for ...
Molecular Docking Simulation Machine Learning Ligands Drug Discovery Algorithms Humans Small Molecule Libraries Receptors, G-Protein-Coupled
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An efficient deep learning-based strategy to screen inhibitors for GluN1/GluN3A receptor.

Acta pharmacologica Sinica Mar 11, 2025
The GluN1/GluN3A receptor, a unique excitatory glycine receptor recently identified in the central nervous system, challenges traditional perspectives of N-methyl-D-aspartate (NMDA) receptor diversity and glycinergic signaling. Its role in emotional ...
Drug Discovery Deep Learning Nerve Tissue Proteins Humans Animals Receptors, N-Methyl-D-Aspartate High-Throughput Screening Assays HEK293 Cells Small Molecule Libraries Patch-Clamp Techniques
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A dataset for machine learning-based QSAR models establishment to screen beta-lactamase inhibitors using the FARM -BIOMOL chemical library.

BMC research notes Mar 3, 2025
OBJECTIVES: Beta-lactamase is a bacterial enzyme that deactivates beta-lactam antibiotics, and it is one of the leading causes of antibiotic resistance problems globally. In current drug discovery research, molecular simulation, like molecular dockin...
beta-Lactamases Databases, Chemical Quantitative Structure-Activity Relationship Machine Learning Molecular Docking Simulation Small Molecule Libraries beta-Lactamase Inhibitors
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Machine Learning in Small-Molecule Mass Spectrometry.

Annual review of analytical chemistry (Palo Alto, Calif.) Feb 27, 2025
Tandem mass spectrometry (MS/MS) is crucial for small-molecule analysis; however, traditional computational methods are limited by incomplete reference libraries and complex data processing. Machine learning (ML) is transforming small-molecule mass s...
Humans Tandem Mass Spectrometry Small Molecule Libraries Machine Learning
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Predicting Antimicrobial Class Specificity of Small Molecules Using Machine Learning.

Journal of chemical information and modeling Feb 23, 2025
While the useful armory of antibiotic drugs is continually depleted due to the emergence of drug-resistant pathogens, the development of novel therapeutics has also slowed down. In the era of advanced computational methods, approaches like machine le...
Microbial Sensitivity Tests Bacteria Anti-Infective Agents Small Molecule Libraries Drug Discovery Machine Learning Anti-Bacterial Agents
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Identifying RNA-small Molecule Binding Sites Using Geometric Deep Learning with Language Models.

Journal of molecular biology Feb 15, 2025
RNAs are emerging as promising therapeutic targets, yet identifying small molecules that bind to them remains a significant challenge in drug discovery. This underscores the crucial role of computational modeling in predicting RNA-small molecule bind...
RNA Nucleic Acid Conformation Drug Discovery Binding Sites Deep Learning Computational Biology Models, Molecular Small Molecule Libraries
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Discovery of TRPV4-Targeting Small Molecules with Anti-Influenza Effects Through Machine Learning and Experimental Validation.

International journal of molecular sciences Feb 6, 2025
Transient receptor potential vanilloid 4 (TRPV4) is a calcium-permeable cation channel critical for maintaining intracellular Ca homeostasis and is essential in regulating immune responses, metabolic processes, and signal transduction. Recent studies...
Mice Influenza, Human Orthomyxoviridae Infections Machine Learning Small Molecule Libraries Humans Animals TRPV Cation Channels Drug Discovery Molecular Docking Simulation Antiviral Agents Influenza A virus
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