AIMC Topic: Ligands

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Computational modelling of olfactory receptors.

Biochimica et biophysica acta. General subjects Jul 1, 2025
Olfactory receptors (ORs), the largest subfamily of G protein-coupled receptors, are essential for detecting and interpreting environmental odorants in animals. Understanding their function is crucial for deciphering olfactory perception and explorin...
Receptors, Odorant Molecular Dynamics Simulation Ligands Humans Animals Molecular Docking Simulation Machine Learning
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On the application of artificial intelligence in virtual screening.

Expert opinion on drug discovery Jul 1, 2025
INTRODUCTION: Artificial intelligence (AI) has emerged as a transformative tool in drug discovery, particularly in virtual screening (VS), a crucial initial step in identifying potential drug candidates. This article highlights the significance of AI...
Humans Artificial Intelligence Molecular Docking Simulation Quantitative Structure-Activity Relationship Drug Evaluation, Preclinical Drug Discovery Ligands Molecular Dynamics Simulation
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When Simulations Meet Machine Learning: Redefining Molecular Docking for Protein-Glycosaminoglycan Systems.

Journal of computational chemistry Jun 30, 2025
Glycosaminoglycans (GAGs) are linear, negatively charged carbohydrates that modulate enzymatic activity in the extracellular matrix. Their high flexibility and specificity in protein-GAG interactions pose challenges for both experimental and computat...
Machine Learning Molecular Docking Simulation Glycosaminoglycans Ligands Proteins Binding Sites Molecular Dynamics Simulation
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Decoding the Structure-Activity Relationship of the Dopamine D3 Receptor-Selective Ligands Using Machine and Deep Learning Approaches.

Journal of chemical information and modeling Jun 9, 2025
Dysfunctions of the dopamine D2 and D3 receptors (D2 and D3) are implicated in neuropsychiatric conditions such as Parkinson's disease, schizophrenia, and substance use disorders (SUDs). Evidence indicates that D3-selective ligands can effectively mo...
Ligands Quantitative Structure-Activity Relationship Receptors, Dopamine D3 Receptors, Dopamine D2 Machine Learning Deep Learning Humans
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Active Learning-Guided Hit Optimization for the Leucine-Rich Repeat Kinase 2 WDR Domain Based on In Silico Ligand-Binding Affinities.

Journal of chemical information and modeling Jun 9, 2025
The leucine-rich repeat kinase 2 (LRRK2) is the most mutated gene in familial Parkinson's disease, and its mutations lead to pathogenic hallmarks of the disease. The LRRK2 WDR domain is an understudied drug target for Parkinson's disease, with no kno...
Ligands Protein Kinase Inhibitors Leucine-Rich Repeat Serine-Threonine Protein Kinase-2 Thermodynamics Protein Domains Molecular Dynamics Simulation Machine Learning Protein Binding Humans
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Predicted and Explained: Transforming drug discovery with AI for high-precision receptor-ligand interaction modeling and binding analysis.

Computers in biology and medicine Jun 1, 2025
The pharmaceutical industry faces persistent challenges in developing effective treatments for complex diseases, creating an urgent need for innovative approaches to accelerate drug discovery. A pivotal factor in this process is the accurate predicti...
Machine Learning Molecular Docking Simulation Protein Binding Computational Biology Drug Discovery Humans Ligands
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Advancements in Ligand-Based Virtual Screening through the Synergistic Integration of Graph Neural Networks and Expert-Crafted Descriptors.

Journal of chemical information and modeling May 26, 2025
The fusion of traditional chemical descriptors with graph neural networks (GNNs) offers a compelling strategy for enhancing ligand-based virtual screening methodologies. A comprehensive evaluation revealed that the benefits derived from this integrat...
Ligands Graph Neural Networks Drug Discovery Drug Evaluation, Preclinical Neural Networks, Computer
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Deep learning-guided design of dynamic proteins.

Science (New York, N.Y.) May 22, 2025
Deep learning has advanced the design of static protein structures, but the controlled conformational changes that are hallmarks of natural signaling proteins have remained inaccessible to de novo design. Here, we describe a general deep learning-gui...
Ligands Deep Learning Mutation Allosteric Regulation Protein Conformation Molecular Dynamics Simulation Proteins Protein Engineering
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CrypTothML: An Integrated Mixed-Solvent Molecular Dynamics Simulation and Machine Learning Approach for Cryptic Site Prediction.

International journal of molecular sciences May 14, 2025
Cryptic sites, which are transient binding sites that emerge through protein conformational changes upon ligand binding, are valuable targets for drug discovery, particularly for allosteric modulators. However, identifying these sites remains challen...
Binding Sites Ligands Protein Binding Solvents Proteins Machine Learning Molecular Dynamics Simulation Drug Discovery
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Efficient Design of Affilin Protein Binders for HER3.

International journal of molecular sciences May 14, 2025
Engineered scaffold-based proteins that bind to concrete targets with high affinity offer significant advantages over traditional antibodies in theranostic applications. Their development often relies on display methods, where large libraries of vari...
Ligands Protein Engineering Protein Binding Peptide Library Receptor, ErbB-3 Cell Surface Display Techniques Humans
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