AIMC Topic: Proteins

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Advancing Molecular Simulations: Merging Physical Models, Experiments, and AI to Tackle Multiscale Complexity.

The journal of physical chemistry letters Apr 3, 2025
Proteins and protein complexes form adaptable networks that regulate essential biochemical pathways and define cell phenotypes through dynamic mechanisms and interactions. Advances in structural biology and molecular simulations have revealed how pro...
Molecular Dynamics Simulation Protein Conformation Machine Learning Proteins Cryoelectron Microscopy
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Cracking the protein compartmentalization code with ProtGPS.

Trends in biochemical sciences Apr 2, 2025
Cellular protein compartmentalization is essential for function, yet the mechanisms directing proteins to their correct destinations remain unclear. Recently, Kilgore, Chinn, Mikhael, and Mitnikov et al. introduced ProtGPS, an artificial intelligence...
Humans Artificial Intelligence Proteins
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Drug-Target Affinity Prediction Based on Topological Enhanced Graph Neural Networks.

Journal of chemical information and modeling Mar 31, 2025
Graph neural networks (GNNs) have achieved remarkable success in drug-target affinity (DTA) analysis, reducing the cost of drug development. Unlike traditional one-dimensional (1D) sequence-based methods, GNNs leverage graph structures to capture ric...
Proteins Neural Networks, Computer Graph Neural Networks Pharmaceutical Preparations Drug Discovery
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Predicting protein-protein interaction with interpretable bilinear attention network.

Computer methods and programs in biomedicine Mar 30, 2025
BACKGROUND AND OBJECTIVE: Protein-protein interactions (PPIs) play the key roles in myriad biological processes, helping to understand the protein function and disease pathology. Identification of PPIs and their interaction types through wet experime...
Neural Networks, Computer Algorithms Humans Sequence Analysis, Protein Databases, Protein Computational Biology Deep Learning Amino Acid Sequence Proteins Protein Binding Protein Conformation Protein Interaction Mapping
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A review of denoising methods in single-particle cryo-EM.

Micron (Oxford, England : 1993) Mar 29, 2025
Cryo-EM has become a vital technique for resolving macromolecular structures at near-atomic resolution, enabling the visualization of proteins and large molecular complexes. However, the images are often accompanied by extremely low SNR, which poses ...
Imaging, Three-Dimensional Image Processing, Computer-Assisted Signal-To-Noise Ratio Deep Learning Proteins Single Molecule Imaging Macromolecular Substances Cryoelectron Microscopy
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Fitting Atomic Structures into Cryo-EM Maps by Coupling Deep Learning-Enhanced Map Processing with Global-Local Optimization.

Journal of chemical information and modeling Mar 28, 2025
With the breakthroughs in protein structure prediction technology, constructing atomic structures from cryo-electron microscopy (cryo-EM) density maps through structural fitting has become increasingly critical. However, the accuracy of the construct...
Deep Learning Proteins Models, Molecular Protein Conformation Cryoelectron Microscopy
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Atomic context-conditioned protein sequence design using LigandMPNN.

Nature methods Mar 28, 2025
Protein sequence design in the context of small molecules, nucleotides and metals is critical to enzyme and small-molecule binder and sensor design, but current state-of-the-art deep-learning-based sequence design methods are unable to model nonprote...
Protein Conformation Ligands Crystallography, X-Ray Models, Molecular Amino Acid Sequence Protein Binding Deep Learning Proteins
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Gold nanorods as multidimensional optical nanomaterials: machine learning-enhanced quantitative fingerprinting of proteins for diagnostic applications.

Nanoscale Mar 28, 2025
The rapid and precise quantification and identification of proteins as key diagnostic biomarkers hold significant promise in allergy testing, disease diagnosis, clinical treatment, and proteomics. This is crucial because alterations in disease-associ...
Nanotubes Proteins Gold Humans Machine Learning
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SS-DTI: A deep learning method integrating semantic and structural information for drug-target interaction prediction.

Journal of bioinformatics and computational biology Mar 25, 2025
Drug-target interaction (DTI) prediction is pivotal in drug discovery and repurposing, providing a more efficient alternative to traditional wet-lab experiments by saving time and resources and expediting the identification of potential targets. Curr...
Proteins Pharmaceutical Preparations Drug Repositioning Deep Learning Semantics Neural Networks, Computer Computational Biology Drug Discovery
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Leveraging Transfer Learning for Predicting Protein-Small-Molecule Interaction Predictions.

Journal of chemical information and modeling Mar 24, 2025
A complex web of intermolecular interactions defines and regulates biological processes. Understanding this web has been particularly challenging because of the sheer number of actors in biological systems: ∼10 proteins in a typical human cell offer ...
Machine Learning Humans Protein Binding Neural Networks, Computer Ligands Proteins Small Molecule Libraries
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