AIMC Topic: Proteins

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GeoNet enables the accurate prediction of protein-ligand binding sites through interpretable geometric deep learning.

Structure (London, England : 1993) Nov 1, 2024
The identification of protein binding residues is essential for understanding their functions in vivo. However, it remains a computational challenge to accurately identify binding sites due to the lack of known residue binding patterns. Local residue...
Binding Sites RNA Ligands DNA Models, Molecular Deep Learning Protein Binding Computational Biology Proteins
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Challenge for Deep Learning: Protein Structure Prediction of Ligand-Induced Conformational Changes at Allosteric and Orthosteric Sites.

Journal of chemical information and modeling Nov 1, 2024
In the realm of biomedical research, understanding the intricate structure of proteins is crucial, as these structures determine how proteins function within our bodies and interact with potential drugs. Traditionally, methods like X-ray crystallogra...
Deep Learning Proteins Allosteric Site Ligands Protein Conformation Databases, Protein Models, Molecular
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Exploring structural diversity across the protein universe with The Encyclopedia of Domains.

Science (New York, N.Y.) Nov 1, 2024
The AlphaFold Protein Structure Database (AFDB) contains more than 214 million predicted protein structures composed of domains, which are independently folding units found in multiple structural and functional contexts. Identifying domains can enabl...
Protein Domains Protein Folding Proteins Databases, Protein Deep Learning
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Using deep-learning predictions reveals a large number of register errors in PDB depositions.

IUCrJ Nov 1, 2024
The accuracy of the information in the Protein Data Bank (PDB) is of great importance for the myriad downstream applications that make use of protein structural information. Despite best efforts, the occasional introduction of errors is inevitable, e...
Models, Molecular Protein Conformation Deep Learning Proteins Databases, Protein
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Molecular tweaking by generative cheminformatics and ligand-protein structures for rational drug discovery.

Bioorganic chemistry Oct 28, 2024
The purpose of this review is two-fold: (1) to summarize artificial intelligence and machine learning approaches and document the role of ligand-protein structures in directing drug discovery; (2) to present examples of drugs from the recent literatu...
Proteins Molecular Structure Ligands Cheminformatics Machine Learning Drug Discovery Humans Artificial Intelligence
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GraphPBSP: Protein binding site prediction based on Graph Attention Network and pre-trained model ProstT5.

International journal of biological macromolecules Oct 28, 2024
Protein-protein/peptide interactions play crucial roles in various biological processes. Exploring their interactions attracts wide attention. However, accurately predicting their binding sites remains a challenging task. Here, we develop an effectiv...
Neural Networks, Computer Algorithms Proteins Binding Sites Protein Binding Computational Biology
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Generative AI Models for the Protein Scaffold Filling Problem.

Journal of computational biology : a journal of computational molecular cell biology Oct 23, 2024
De novo protein sequencing is an important problem in proteomics, playing a crucial role in understanding protein functions, drug discovery, design and evolutionary studies, etc. Top-down and bottom-up tandem mass spectrometry are popular approaches ...
Algorithms Computational Biology Proteomics Humans Amino Acid Sequence Proteins Databases, Protein Artificial Intelligence Sequence Analysis, Protein
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Perspective: on the importance of extensive, high-quality and reliable deposition of biomolecular NMR data in the age of artificial intelligence.

Journal of biomolecular NMR Oct 20, 2024
Artificial intelligence (AI) models are revolutionising scientific data analysis but are reliant on large training data sets. While artificial training data can be used in the context of NMR processing and data analysis methods, relating NMR paramete...
Nuclear Magnetic Resonance, Biomolecular Artificial Intelligence Proteins
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How the technologies behind self-driving cars, social networks, ChatGPT, and DALL-E2 are changing structural biology.

BioEssays : news and reviews in molecular, cellular and developmental biology Oct 15, 2024
The performance of deep Neural Networks (NNs) in the text (ChatGPT) and image (DALL-E2) domains has attracted worldwide attention. Convolutional NNs (CNNs), Large Language Models (LLMs), Denoising Diffusion Probabilistic Models (DDPMs)/Noise Conditio...
Humans Neural Networks, Computer Proteins Deep Learning Social Networking
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GraphPI: Efficient Protein Inference with Graph Neural Networks.

Journal of proteome research Oct 13, 2024
The integration of deep learning approaches in biomedical research has been transformative, enabling breakthroughs in various applications. Despite these strides, its application in protein inference is impeded by the scarcity of extensively labeled ...
Databases, Protein Proteomics Proteins Deep Learning Computational Biology Humans Neural Networks, Computer Algorithms
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