AIMC Topic: Ligands

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LumiCharge: Spherical Harmonic Convolutional Networks for Atomic Charge Prediction in Drug Discovery.

The journal of physical chemistry letters Jun 16, 2025
Atomic charge is crucial in drug design for analyzing reactive sites and interactions between ligands and targets. While quantum mechanical methods offer high accuracy, they are generally computationally costly. Conversely, empirical approaches, whil...
Quantum Theory Ligands Receptors, Androgen Machine Learning Drug Discovery
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Improving Covalent and Noncovalent Molecule Generation via Reinforcement Learning with Functional Fragments.

Journal of chemical information and modeling Jun 5, 2025
Small-molecule drugs play a critical role in cancer therapy by selectively targeting key signaling pathways that drive tumor growth. While deep learning models have advanced drug discovery, there remains a lack of generative frameworks for covalent ...
Protein Kinase Inhibitors Agammaglobulinaemia Tyrosine Kinase Small Molecule Libraries Ligands ErbB Receptors Humans Molecular Docking Simulation Deep Learning Molecular Dynamics Simulation Drug Design
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Multi-omics identifies OSM-OSMR as a key receptor-ligand in the tumor environment of endometrial adenocarcinoma.

International immunopharmacology May 31, 2025
Endometrial adenocarcinoma carries a bleak prognosis, and the molecular markers that evaluate the progression of endometrial adenocarcinoma to advanced stages remain uncertain. Cell-cell communication plays a crucial role in the tumor microenvironmen...
Endometrial Neoplasms Oncostatin M Oncostatin M Receptor beta Subunit Mice, Nude Ligands Multiomics Gene Expression Regulation, Neoplastic Signal Transduction Adenocarcinoma Cell Proliferation Transcriptome Animals Cell Line, Tumor Humans Gene Expression Profiling Female Mice Tumor Microenvironment Prognosis
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Prediction of Ligand-Receptor Interactions Based on CatBoost and Deep Forest and Their Application in Cell-Cell Communication Analysis.

Journal of chemical information and modeling May 30, 2025
Cell-to-cell communication (CCC) is prominent for cell growth and development as well as tissue and organ formation. CCC inference can help us to deeply understand cellular interplay and discover potential therapeutic targets for complex diseases. Ce...
Cell Communication Deep Learning Humans Ligands Computational Biology Boosting Machine Learning Algorithms
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In Silico Screening of Small Molecule Inhibitors for Amyloid-β Aggregation.

Journal of chemical information and modeling May 29, 2025
The self-aggregation of amyloid-β (Aβ) into fibrils is a hallmark of Alzheimer's disease (AD). Inhibition of Aβ aggregation with small molecule compounds represents a promising therapeutic strategy for AD. However, designing effective ligands is chal...
Molecular Dynamics Simulation Machine Learning Drug Evaluation, Preclinical Humans Molecular Docking Simulation Protein Aggregates Ligands Amyloid beta-Peptides Small Molecule Libraries
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Modeling Active-State Conformations of G-Protein-Coupled Receptors Using AlphaFold2 via Template Bias and Explicit Protein Constrains.

Journal of chemical information and modeling May 29, 2025
AlphaFold2 and other deep learning tools represent the state of the art for protein structure prediction; however, they are still limited in their ability to model multiple protein conformations. Since the function of many proteins depends on their a...
Protein Conformation Receptors, G-Protein-Coupled Models, Molecular Ligands Humans Deep Learning
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CrypToth: Cryptic Pocket Detection through Mixed-Solvent Molecular Dynamics Simulations-Based Topological Data Analysis.

Journal of chemical information and modeling May 22, 2025
Some functional proteins undergo conformational changes to expose hidden binding sites when a binding molecule approaches their surface. Such binding sites are called cryptic sites and are important targets for drug discovery. However, it is still di...
Protein Conformation Binding Sites Ligands Solvents Proteins Molecular Dynamics Simulation
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On the Difficulty to Rescore Hits from Ultralarge Docking Screens.

Journal of chemical information and modeling May 22, 2025
Docking-based virtual screening tools customized to mine ultralarge chemical spaces are consistently reported to yield both higher hit rates and more potent ligands than that achieved by conventional docking of smaller million-sized compound librarie...
Machine Learning Ligands Proteins Molecular Docking Simulation Drug Evaluation, Preclinical Protein Binding Quantum Theory
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From Nuclear Receptors to GPCRs: a Deep Transfer Learning Approach for Enhanced Environmental Estrogen Recognition.

Environmental science & technology Apr 30, 2025
Environmental estrogens (EEs), as typical endocrine-disrupting chemicals (EDCs), can bind to classic estrogen receptors (ERs) to induce genomic effects, as well as to G protein-coupled estrogen receptor (GPER) located on the membrane, thereby inducin...
Endocrine Disruptors Receptors, Estrogen Estrogens Humans Receptors, Cytoplasmic and Nuclear Receptors, G-Protein-Coupled Deep Learning Ligands
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AdptDilatedGCN: Protein-ligand binding affinity prediction based on multi-scale interaction fusion mechanism and dilated GCN.

International journal of biological macromolecules Apr 30, 2025
Predicting protein-ligand binding affinity is crucial for drug discovery. However, existing prediction methods often make insufficient use of the features of proteins and ligands, lack interactions between different information, and have difficulty i...
Computational Biology Proteins Ligands Deep Learning Protein Binding
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