AIMC Topic: Ligands

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Edge-enhanced interaction graph network for protein-ligand binding affinity prediction.

PloS one Apr 8, 2025
Protein-ligand interactions are crucial in drug discovery. Accurately predicting protein-ligand binding affinity is essential for screening potential drugs. Graph neural networks have proven highly effective in modeling spatial relationships and thre...
Ligands Drug Discovery Protein Binding Proteins Neural Networks, Computer Algorithms
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Virtual reality in drug design: Benefits, applications and industrial perspectives.

Current opinion in structural biology Apr 7, 2025
Virtual reality (VR) is a tool which has transformative potential in domains which involve the visualization of complex 3D data such as structure-based drug design (SBDD), where it offers new ways to visualize and manipulate complex molecular structu...
Drug Industry Ligands COVID-19 Drug Design Humans COVID-19 Drug Treatment Virtual Reality Drug Discovery SARS-CoV-2 Molecular Docking Simulation
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Persistent Directed Flag Laplacian (PDFL)-Based Machine Learning for Protein-Ligand Binding Affinity Prediction.

Journal of chemical theory and computation Apr 5, 2025
Directionality in molecular and biomolecular networks plays an important role in the accurate representation of the complex, dynamic, and asymmetrical nature of interactions present in protein-ligand binding, signal transduction, and biological pathw...
Ligands Protein Binding Proteins Machine Learning
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Can Deep Learning Blind Docking Methods be Used to Predict Allosteric Compounds?

Journal of chemical information and modeling Apr 1, 2025
Allosteric compounds offer an alternative mode of inhibition to orthosteric compounds with opportunities for selectivity and noncompetition. Structure-based drug design (SBDD) of allosteric compounds introduces complications compared to their orthost...
Molecular Docking Simulation Drug Design Protein Conformation Protein Kinase Inhibitors Cyclin-Dependent Kinase 2 Deep Learning Ligands Allosteric Regulation
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Atomic context-conditioned protein sequence design using LigandMPNN.

Nature methods Mar 28, 2025
Protein sequence design in the context of small molecules, nucleotides and metals is critical to enzyme and small-molecule binder and sensor design, but current state-of-the-art deep-learning-based sequence design methods are unable to model nonprote...
Protein Conformation Ligands Proteins Models, Molecular Crystallography, X-Ray Deep Learning Amino Acid Sequence Protein Binding
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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 ...
Proteins Ligands Protein Binding Small Molecule Libraries Humans Neural Networks, Computer Machine Learning
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Developing predictive models for µ opioid receptor binding using machine learning and deep learning techniques.

Experimental biology and medicine (Maywood, N.J.) Mar 19, 2025
Opioids exert their analgesic effect by binding to the µ opioid receptor (MOR), which initiates a downstream signaling pathway, eventually inhibiting pain transmission in the spinal cord. However, current opioids are addictive, often leading to overd...
Analgesics, Opioid Support Vector Machine Ligands Humans Deep Learning Receptors, Opioid, mu Machine Learning Structure-Activity Relationship Protein Binding
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Probing the dark chemical matter against PDE4 for the management of psoriasis using in silico, in vitro and in vivo approach.

Molecular diversity Mar 17, 2025
The potential downsides for the present treatment for psoriasis are drug resistance, reduced efficacy, risk of mental episodes, and drug interactions. Hence, this study aims to discover a new drug for psoriasis by considering global research efforts ...
Animals Molecular Docking Simulation Drug Discovery Humans Ligands Phosphodiesterase 4 Inhibitors Cyclic Nucleotide Phosphodiesterases, Type 4 Psoriasis Molecular Dynamics Simulation Mice
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Artificial Intelligence: A New Tool for Structure-Based G Protein-Coupled Receptor Drug Discovery.

Biomolecules Mar 17, 2025
Understanding protein structures can facilitate the development of therapeutic drugs. Traditionally, protein structures have been determined through experimental approaches such as X-ray crystallography, NMR spectroscopy, and cryo-electron microscopy...
Algorithms Molecular Docking Simulation Computational Biology Receptors, G-Protein-Coupled Drug Discovery Humans Artificial Intelligence Ligands Protein Conformation
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Computational discovery of novel PI3KC2α inhibitors using structure-based pharmacophore modeling, machine learning and molecular dynamic simulation.

Journal of molecular graphics & modelling Mar 15, 2025
PI3KC2α is a lipid kinase associated with cancer metastasis and thrombosis. In this study, we present a novel computational workflow integrating structure-based pharmacophore modeling, machine learning (ML), and molecular dynamics (MD) simulations to...
Ligands Protein Kinase Inhibitors Pharmacophore Phosphoinositide-3 Kinase Inhibitors Protein Binding Phosphatidylinositol 3-Kinases Molecular Dynamics Simulation Molecular Docking Simulation Drug Discovery Humans Machine Learning
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