AIMC Topic: Ligands

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MultiModRLBP: A Deep Learning Approach for Multi-Modal RNA-Small Molecule Ligand Binding Sites Prediction.

IEEE journal of biomedical and health informatics Aug 6, 2024
This study aims to tackle the intricate challenge of predicting RNA-small molecule binding sites to explore the potential value in the field of RNA drug targets. To address this challenge, we propose the MultiModRLBP method, which integrates multi-mo...
Algorithms Deep Learning Nucleic Acid Conformation Binding Sites Small Molecule Libraries RNA Ligands Computational Biology
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Protein ligand binding site prediction using graph transformer neural network.

PloS one Aug 6, 2024
Ligand binding site prediction is a crucial initial step in structure-based drug discovery. Although several methods have been proposed previously, including those using geometry based and machine learning techniques, their accuracy is considered to ...
Algorithms Neural Networks, Computer Proteins Machine Learning Drug Discovery Binding Sites Databases, Protein Protein Binding Ligands
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Biomimetic fusion: Platyper's dual vision for predicting protein-surface interactions.

Materials horizons Jul 29, 2024
Predicting protein binding with the material surface still remains a challenge. Here, a novel approach, platypus dual perception neural network (Platyper), was developed to describe the interactions in protein-surface systems involving bioceramics wi...
Surface Properties Biomimetics Ligands Neural Networks, Computer Proteins Molecular Dynamics Simulation Protein Binding
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From mundane to surprising nonadditivity: drivers and impact on ML models.

Journal of computer-aided molecular design Jul 25, 2024
Nonadditivity (NA) in Structure-Activity and Structure-Property Relationship (SAR) data is a rare but very information rich phenomenon. It can indicate conformational flexibility, structural rearrangements, and errors in assay results and structural ...
Structure-Activity Relationship Ligands Molecular Conformation Humans Machine Learning Drug Discovery
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Transcriptionally Conditional Recurrent Neural Network for De Novo Drug Design.

Journal of chemical information and modeling Jul 24, 2024
Computational molecular generation methods that generate chemical structures from gene expression profiles have been actively developed for de novo drug design. However, most omics-based methods involve complex models consisting of multiple neural ne...
Transcription, Genetic Drug Design Gene Expression Profiling Humans Ligands Neural Networks, Computer
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HydraScreen: A Generalizable Structure-Based Deep Learning Approach to Drug Discovery.

Journal of chemical information and modeling Jul 22, 2024
We propose HydraScreen, a deep-learning framework for safe and robust accelerated drug discovery. HydraScreen utilizes a state-of-the-art 3D convolutional neural network designed for the effective representation of molecular structures and interactio...
Protein Binding Drug Design Ligands Proteins Drug Discovery Neural Networks, Computer Deep Learning
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Binding and sensing diverse small molecules using shape-complementary pseudocycles.

Science (New York, N.Y.) Jul 18, 2024
We describe an approach for designing high-affinity small molecule-binding proteins poised for downstream sensing. We use deep learning-generated pseudocycles with repeating structural units surrounding central binding pockets with widely varying sha...
Molecular Docking Simulation Deep Learning Binding Sites Small Molecule Libraries Protein Multimerization Methotrexate Protein Binding Thyroxine Nanopores Ligands Proteins
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MDFit: automated molecular simulations workflow enables high throughput assessment of ligands-protein dynamics.

Journal of computer-aided molecular design Jul 17, 2024
Molecular dynamics (MD) simulation is a powerful tool for characterizing ligand-protein conformational dynamics and offers significant advantages over docking and other rigid structure-based computational methods. However, setting up, running, and an...
Binding Sites Proteins Workflow Ligands Protein Conformation Molecular Dynamics Simulation Molecular Docking Simulation Humans Drug Design Protein Binding Machine Learning Software
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Future Perspectives of Artificial Intelligence in Bone Marrow Dosimetry and Individualized Radioligand Therapy.

Seminars in nuclear medicine Jul 15, 2024
Radioligand therapy is an emerging and effective treatment option for various types of malignancies, but may be intricately linked to hematological side effects such as anemia, lymphopenia or thrombocytopenia. The safety and efficacy of novel therano...
Artificial Intelligence Precision Medicine Bone Marrow Humans Ligands Radiometry
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Machine Learned Classification of Ligand Intrinsic Activities at Human μ-Opioid Receptor.

ACS chemical neuroscience Jul 11, 2024
Opioids are small-molecule agonists of μ-opioid receptor (μOR), while reversal agents such as naloxone are antagonists of μOR. Here, we developed machine learning (ML) models to classify the intrinsic activities of ligands at the human μOR based on t...
Humans Neural Networks, Computer Machine Learning Receptors, Opioid, mu Animals Rats Mice Analgesics, Opioid Ligands
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