AIMC Topic: Proteins

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Structural Biology in the AlphaFold Era: How Far Is Artificial Intelligence from Deciphering the Protein Folding Code?

Biomolecules May 6, 2025
Proteins are biomolecules characterized by uncommon chemical and physicochemical complexities coupled with extreme responsiveness to even minor chemical modifications or environmental variations. Since the shape that proteins assume is fundamental fo...
Artificial Intelligence Machine Learning Computational Biology Humans Protein Conformation Protein Folding Proteins Models, Molecular
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M-DeepAssembly: enhanced DeepAssembly based on multi-objective multi-domain protein conformation sampling.

BMC bioinformatics May 5, 2025
BACKGROUND: Association and cooperation among structural domains play an important role in protein function and drug design. Despite remarkable advancements in highly accurate single-domain protein structure prediction through the collaborative effor...
Algorithms Deep Learning Protein Conformation Computational Biology Proteins Models, Molecular Databases, Protein Protein Domains
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Accurate identification and mechanistic evaluation of pathogenic missense variants with .

Proceedings of the National Academy of Sciences of the United States of America May 2, 2025
Understanding the effects of missense mutations or single amino acid variants (SAVs) on protein function is crucial for elucidating the molecular basis of diseases/disorders and designing rational therapies. We introduce here , a machine learning too...
Algorithms Computational Biology Databases, Protein Mutation, Missense Proteins Humans Machine Learning
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ProFun-SOM: Protein Function Prediction for Specific Ontology Based on Multiple Sequence Alignment Reconstruction.

IEEE transactions on neural networks and learning systems May 2, 2025
Protein function prediction is crucial for understanding species evolution, including viral mutations. Gene ontology (GO) is a standardized representation framework for describing protein functions with annotated terms. Each ontology is a specific fu...
Sequence Alignment Computational Biology Proteins Molecular Sequence Annotation Gene Ontology Databases, Protein Algorithms Deep Learning Humans Neural Networks, Computer
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AdptDilatedGCN: Protein-ligand binding affinity prediction based on multi-scale interaction fusion mechanism and dilated GCN.

International journal of biological macromolecules Apr 30, 2025
Predicting protein-ligand binding affinity is crucial for drug discovery. However, existing prediction methods often make insufficient use of the features of proteins and ligands, lack interactions between different information, and have difficulty i...
Ligands Deep Learning Protein Binding Computational Biology Proteins
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Massive experimental quantification allows interpretable deep learning of protein aggregation.

Science advances Apr 30, 2025
Protein aggregation is a pathological hallmark of more than 50 human diseases and a major problem for biotechnology. Methods have been proposed to predict aggregation from sequence, but these have been trained and evaluated on small and biased experi...
Proteins Protein Aggregates Deep Learning Computational Biology Humans Neural Networks, Computer
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[Nobel Prize in chemistry 2024: David Baker, Demis Hassabis et John M. Jumper. The revolution of artificial intelligence in structural biology].

Medecine sciences : M/S Apr 28, 2025
The 2024 Nobel Prize in chemistry has been awarded to Demis Hassabis and John M. Jumper (Google DeepMind) for the development of artificial intelligence-guided protein structure prediction and to David Baker (University of Washington, Seattle, USA) f...
Protein Conformation Artificial Intelligence Humans History, 20th Century Nobel Prize Computational Biology Proteins Chemistry History, 21st Century
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Frustration in physiology and molecular medicine.

Molecular aspects of medicine Apr 23, 2025
Molecules provide the ultimate language in terms of which physiology and pathology must be understood. Myriads of proteins participate in elaborate networks of interactions and perform chemical activities coordinating the life of cells. To perform th...
Humans Animals Protein Conformation Gene Regulatory Networks Protein Folding Molecular Medicine Proteins
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A hybrid variational autoencoder and WGAN with gradient penalty for tertiary protein structure generation.

Scientific reports Apr 23, 2025
Elucidating the tertiary structure of proteins is important for understanding their functions and interactions. While deep neural networks have advanced the prediction of a protein's native structure from its amino acid sequence, the focus on a singl...
Algorithms Neural Networks, Computer Deep Learning Computational Biology Protein Structure, Tertiary Proteins Autoencoder Models, Molecular
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Advances in artificial intelligence-envisioned technologies for protein and nucleic acid research.

Drug discovery today Apr 17, 2025
Artificial intelligence (AI) and machine learning (ML) have revolutionized pharmaceutical research, particularly in protein and nucleic acid studies. This review summarizes the current status of AI and ML applications in the pharmaceutical sector, fo...
Humans Precision Medicine Drug Development Nucleic Acids Animals Artificial Intelligence Proteins Drug Discovery Machine Learning
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