AIMC Topic: Ligands

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Prospective de novo drug design with deep interactome learning.

Nature communications Apr 22, 2024
De novo drug design aims to generate molecules from scratch that possess specific chemical and pharmacological properties. We present a computational approach utilizing interactome-based deep learning for ligand- and structure-based generation of dru...
Protein Binding Drug Design Ligands Deep Learning PPAR gamma Humans Binding Sites
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Molecular Docking Improved with Human Spatial Perception Using Virtual Reality.

IEEE transactions on visualization and computer graphics Apr 19, 2024
Adaptive steered molecular dynamics (ASMD) is a computational biophysics method in which an external force is applied to a selected set of atoms or a specific reaction coordinate to induce a particular molecular motion. Virtual reality (VR) based met...
Perception Computer Graphics Molecular Docking Simulation Humans Proteins Artificial Intelligence Virtual Reality Ligands
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PT-Finder: A multi-modal neural network approach to target identification.

Computers in biology and medicine Apr 15, 2024
Efficient target identification for bioactive compounds, including novel synthetic analogs, is crucial for accelerating the drug discovery pipeline. However, the process of target identification presents significant challenges and is often expensive,...
Software Drug Discovery Proteins Ligands Neural Networks, Computer Machine Learning Humans
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Machine learning approaches to predict TAS2R receptors for bitterants.

Biotechnology and bioengineering Apr 8, 2024
Bitter taste involves the detection of diverse chemical compounds by a family of G protein-coupled receptors, known as taste receptor type 2 (TAS2R). It is often linked to toxins and harmful compounds and in particular bitter taste receptors particip...
Receptors, G-Protein-Coupled Ligands Humans Machine Learning Taste Taste Receptors, Type 2
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Inferring molecular inhibition potency with AlphaFold predicted structures.

Scientific reports Apr 8, 2024
Even though in silico drug ligand-based methods have been successful in predicting interactions with known target proteins, they struggle with new, unassessed targets. To address this challenge, we propose an approach that integrates structural data ...
Receptors, G-Protein-Coupled Ligands Humans Machine Learning
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Advancing Ligand Docking through Deep Learning: Challenges and Prospects in Virtual Screening.

Accounts of chemical research Apr 5, 2024
Molecular docking, also termed ligand docking (LD), is a pivotal element of structure-based virtual screening (SBVS) used to predict the binding conformations and affinities of protein-ligand complexes. Traditional LD methodologies rely on a search a...
Drug Discovery Deep Learning Proteins Ligands Algorithms Molecular Docking Simulation
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Machine learning-aided search for ligands of P2Y and other P2Y receptors.

Purinergic signalling Mar 25, 2024
The P2Y receptor, activated by uridine diphosphate (UDP), is a target for antagonists in inflammatory, neurodegenerative, and metabolic disorders, yet few potent and selective antagonists are known to date. This prompted us to use machine learning as...
Ligands Machine Learning Humans Receptors, Purinergic P2 Drug Discovery
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Directional Δ Neural Network (DrΔ-Net): A Modular Neural Network Approach to Binding Free Energy Prediction.

Journal of chemical information and modeling Mar 12, 2024
The protein-ligand binding free energy is a central quantity in structure-based computational drug discovery efforts. Although popular alchemical methods provide sound statistical means of computing the binding free energy of a large breadth of syste...
Entropy Neural Networks, Computer Proteins Protein Binding Ligands
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Investigating the Aryl Hydrocarbon Receptor Agonist/Antagonist Conformational Switch Using Well-Tempered Metadynamics Simulations.

Journal of chemical information and modeling Mar 8, 2024
The aryl hydrocarbon receptor (AhR) is a ligand-dependent transcription factor that mediates biological signals to control various complicated cellular functions. It plays a crucial role in environmental sensing and xenobiotic metabolism. Dysregulati...
Humans Ligands Aryl Hydrocarbon Receptor Nuclear Translocator Artificial Intelligence Receptors, Aryl Hydrocarbon
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Ligand-based pharmacophore modeling and machine learning for the discovery of potent aurora A kinase inhibitory leads of novel chemotypes.

Molecular diversity Mar 6, 2024
Aurora-A (AURKA) is serine/threonine protein kinase involved in the regulation of numerous processes of cell division. Numerous studies have demonstrated strong association between AURKA and cancer. AURKA is overexpressed in many cancers, such as col...
Ligands Quantitative Structure-Activity Relationship Protein Kinase Inhibitors Pharmacophore Drug Discovery Aurora Kinase A Humans Models, Molecular Machine Learning
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