AIMC Topic: Proteins

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Advancing structure modeling from cryo-EM maps with deep learning.

Biochemical Society transactions Feb 7, 2025
Cryo-electron microscopy (cryo-EM) has revolutionized structural biology by enabling the determination of biomolecular structures that are challenging to resolve using conventional methods. Interpreting a cryo-EM map requires accurate modeling of the...
Cryoelectron Microscopy Deep Learning Proteins Models, Molecular Protein Conformation
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Scaling Graph Neural Networks to Large Proteins.

Journal of chemical theory and computation Feb 6, 2025
Graph neural network (GNN) architectures have emerged as promising force field models, exhibiting high accuracy in predicting complex energies and forces based on atomic identities and Cartesian coordinates. To expand the applicability of GNNs, and m...
Neural Networks, Computer Machine Learning Thermodynamics Graph Neural Networks Proteins Molecular Dynamics Simulation
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CL-GNN: Contrastive Learning and Graph Neural Network for Protein-Ligand Binding Affinity Prediction.

Journal of chemical information and modeling Feb 6, 2025
In the realm of drug discovery and design, the accurate prediction of protein-ligand binding affinity is of paramount importance as it underpins the functional interactions within biological systems. This study introduces a novel self-supervised lear...
Machine Learning Drug Discovery Protein Binding Proteins Ligands Neural Networks, Computer Graph Neural Networks
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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...
Drug Discovery Deep Learning Proteins Models, Molecular Protein Binding Computational Biology Protein Conformation Ligands
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Automated and explainable machine learning for monitoring lipid and protein oxidative damage in mutton using hyperspectral imaging.

Food research international (Ottawa, Ont.) Feb 1, 2025
Current detection methods for lipid and protein oxidation using hyperspectral imaging (HSI) in conjunction with machine learning (ML) necessitate the involvement of data scientists and domain experts to adjust the model architecture and tune hyperpar...
Oxidation-Reduction Hyperspectral Imaging Proteins Machine Learning Animals Oxidative Stress Lipids
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KaMLs for Predicting Protein p Values and Ionization States: Are Trees All You Need?

Journal of chemical theory and computation Jan 30, 2025
Despite its importance in understanding biology and computer-aided drug discovery, the accurate prediction of protein ionization states remains a formidable challenge. Physics-based approaches struggle to capture the small, competing contributions in...
Hydrogen-Ion Concentration Machine Learning Ions Decision Trees Databases, Protein Proteins
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Learning the language of life with AI.

Science (New York, N.Y.) Jan 30, 2025
In 2021, a year before ChatGPT took the world by storm amid the excitement about generative artificial intelligence (AI), AlphaFold 2 cracked the 50-year-old protein-folding problem, predicting three-dimensional (3D) structures for more than 200 mill...
Protein Folding Language Artificial Intelligence Proteins
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MutualDTA: An Interpretable Drug-Target Affinity Prediction Model Leveraging Pretrained Models and Mutual Attention.

Journal of chemical information and modeling Jan 29, 2025
Efficient and accurate drug-target affinity (DTA) prediction can significantly accelerate the drug development process. Recently, deep learning models have been widely applied to DTA prediction and have achieved notable success. However, existing met...
Protein Binding Proteins Pharmaceutical Preparations Binding Sites Drug Discovery Deep Learning Humans
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DO-GMA: An End-to-End Drug-Target Interaction Identification Framework with a Depthwise Overparameterized Convolutional Network and the Gated Multihead Attention Mechanism.

Journal of chemical information and modeling Jan 28, 2025
Identification of potential drug-target interactions (DTIs) is a crucial step in drug discovery and repurposing. Although deep learning effectively deciphers DTIs, most deep learning-based methods represent drug features from only a single perspectiv...
Deep Learning Neural Networks, Computer Proteins Drug Discovery
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Modern machine learning methods for protein property prediction.

Current opinion in structural biology Jan 28, 2025
Recent progress and development of artificial intelligence and machine learning (AI/ML) techniques have enabled addressing complex biomolecular problems. AI/ML models learn the underlying distribution of data they are trained on and when exposed to n...
Proteins Protein Conformation Machine Learning Computational Biology
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