AIMC Topic: Models, Molecular

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Protein ligand structure prediction: From empirical to deep learning approaches.

Current opinion in structural biology Feb 5, 2025
Protein-ligand structure prediction methods, aiming to predict the three-dimensional complex structure and binding energy of a compound and target protein, are essential in many structure-based drug discovery pipelines, including virtual screening an...
Deep Learning Protein Binding Drug Discovery Models, Molecular Ligands Protein Conformation Computational Biology Proteins
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Transformer Decoder Learns from a Pretrained Protein Language Model to Generate Ligands with High Affinity.

Journal of chemical information and modeling Jan 27, 2025
The drug discovery process can be significantly accelerated by using deep learning methods to suggest molecules with druglike features and, more importantly, that are good candidates to bind specific proteins of interest. We present a novel deep lear...
Models, Molecular Ligands Drug Discovery Deep Learning Protein Binding Proteins
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AI-based methods for biomolecular structure modeling for Cryo-EM.

Current opinion in structural biology Jan 27, 2025
Cryo-electron microscopy (Cryo-EM) has revolutionized structural biology by enabling the determination of macromolecular structures that were challenging to study with conventional methods. Processing cryo-EM data involves several computational steps...
Cryoelectron Microscopy Models, Molecular Macromolecular Substances Artificial Intelligence Deep Learning
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Challenges and compromises: Predicting unbound antibody structures with deep learning.

Current opinion in structural biology Jan 24, 2025
Therapeutic antibodies are manufactured, stored and administered in the free state; this makes understanding the unbound form key to designing and improving development pipelines. Prediction of unbound antibodies is challenging, specifically modellin...
Humans Models, Molecular Antibodies Deep Learning Protein Conformation Protein Binding
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MVGNN-PPIS: A novel multi-view graph neural network for protein-protein interaction sites prediction based on Alphafold3-predicted structures and transfer learning.

International journal of biological macromolecules Jan 21, 2025
Protein-protein interactions (PPI) are crucial for understanding numerous biological processes and pathogenic mechanisms. Identifying interaction sites is essential for biomedical research and targeted drug development. Compared to experimental metho...
Neural Networks, Computer Models, Molecular Protein Conformation Computational Biology Protein Interaction Mapping Algorithms Binding Sites Proteins Graph Neural Networks Protein Binding
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Deciphering Protein Secondary Structures and Nucleic Acids in Cryo-EM Maps Using Deep Learning.

Journal of chemical information and modeling Jan 21, 2025
With the resolution revolution of cryo-electron microscopy (cryo-EM) and the rapid development of image processing technology, cryo-EM has become an indispensable experimental method for determining the three-dimensional structures of biological macr...
Cryoelectron Microscopy Protein Structure, Secondary Models, Molecular Nucleic Acids Deep Learning Proteins
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Targeting protein-ligand neosurfaces with a generalizable deep learning tool.

Nature Jan 15, 2025
Molecular recognition events between proteins drive biological processes in living systems. However, higher levels of mechanistic regulation have emerged, in which protein-protein interactions are conditioned to small molecules. Despite recent advanc...
Models, Molecular Ligands Protein Binding Proteins Proto-Oncogene Proteins c-bcl-2 Bridged Bicyclo Compounds, Heterocyclic Drug Design Deep Learning Humans
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Lessons from Deep Learning Structural Prediction of Multistate Multidomain Proteins-The Case Study of Coiled-Coil NOD-like Receptors.

International journal of molecular sciences Jan 9, 2025
We test here the prediction capabilities of the new generation of deep learning predictors in the more challenging situation of multistate multidomain proteins by using as a case study a coiled-coil family of Nucleotide-binding Oligomerization Domain...
Protein Domains Protein Conformation Arabidopsis Protein Structure, Secondary Models, Molecular NLR Proteins Deep Learning Computational Biology
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CovCysPredictor: Predicting Selective Covalently Modifiable Cysteines Using Protein Structure and Interpretable Machine Learning.

Journal of chemical information and modeling Jan 8, 2025
Targeted covalent inhibition is a powerful therapeutic modality in the drug discoverer's toolbox. Recent advances in covalent drug discovery, in particular, targeting cysteines, have led to significant breakthroughs for traditionally challenging targ...
Humans Machine Learning Drug Discovery Protein Conformation Proteins Models, Molecular Cysteine Databases, Protein Ligands
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Self-Supervised Molecular Representation Learning With Topology and Geometry.

IEEE journal of biomedical and health informatics Jan 7, 2025
Molecular representation learning is of great importance for drug molecular analysis. The development in molecular representation learning has demonstrated great promise through self-supervised pre-training strategy to overcome the scarcity of labele...
Algorithms Supervised Machine Learning Models, Molecular Humans
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