AIMC Topic: Proteins

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ResNeXt-Based Rescoring Model for Proteoform Characterization in Top-Down Mass Spectra.

Interdisciplinary sciences, computational life sciences Sep 1, 2025
In top-down proteomics, the accurate identification and characterization of proteoform through mass spectrometry represents a critical objective. As a result, achieving accuracy in identification results is essential. Multiple primary structure alter...
Algorithms Deep Learning Proteomics Support Vector Machine Machine Learning Mass Spectrometry Proteins
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Transfer Learning for Predicting ncRNA-Protein Interactions.

Journal of chemical information and modeling Aug 11, 2025
Noncoding RNAs (ncRNAs) interact with proteins, playing a crucial role in regulating gene expression and cellular functions. Accurate prediction of these interactions is essential for understanding biological processes and developing novel therapeuti...
Proteins RNA, Untranslated Protein Binding Computational Biology Deep Learning Machine Learning
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Investigating the determinants of performance in machine learning for protein fitness prediction.

Protein science : a publication of the Protein Society Aug 1, 2025
Machine learning (ML) has revolutionized protein biology, solving long-standing problems in protein folding, scaffold generation, and function design tasks. A range of architectures have shown success on supervised protein fitness prediction tasks. N...
Proteins Protein Folding Machine Learning Algorithms
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DSSP 4: FAIR annotation of protein secondary structure.

Protein science : a publication of the Protein Society Aug 1, 2025
Protein secondary structure annotation is essential for understanding protein architecture, serving as a cornerstone for structural classification, alignment, visualization, and machine learning applications. The Define Secondary Structure of Protein...
Software Algorithms Models, Molecular Molecular Sequence Annotation Proteins Databases, Protein Protein Structure, Secondary
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PEGASUS: Prediction of MD-derived protein flexibility from sequence.

Protein science : a publication of the Protein Society Aug 1, 2025
Protein flexibility is essential to its biological function. However, experimental methods for its assessment, such as X-ray crystallography and nuclear magnetic resonance spectroscopy, are often limited by experimental variability and high cost, lea...
Software Databases, Protein Amino Acid Sequence Molecular Dynamics Simulation Proteins Protein Conformation
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Artificial intelligence and first-principle methods in protein redesign: A marriage of convenience?

Protein science : a publication of the Protein Society Aug 1, 2025
Since AlphaFold2's rise, many deep learning methods for protein design have emerged. Here, we validate widely used and recognized tools, compare them with first-principle methods, and explore their combinations, focusing on their effectiveness in pro...
Proteins Protein Engineering Databases, Protein Artificial Intelligence Protein Folding Models, Molecular Deep Learning Protein Conformation
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PocketDTA: A pocket-based multimodal deep learning model for drug-target affinity prediction.

Computational biology and chemistry Aug 1, 2025
Drug-target affinity prediction is a fundamental task in the field of drug discovery. Extracting and integrating structural information from proteins effectively is crucial to enhance the accuracy and generalization of prediction, which remains a sub...
Deep Learning Pharmaceutical Preparations Proteins Humans Neural Networks, Computer Drug Discovery
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HDXRank: A Deep Learning Framework for Ranking Protein Complex Predictions with Hydrogen-Deuterium Exchange Data.

Journal of chemical theory and computation Jul 22, 2025
Accurate modeling of protein-protein complex structures is essential for understanding biological mechanisms. Hydrogen-deuterium exchange (HDX) experiments provide valuable insights into binding interfaces. Incorporating HDX data into protein complex...
Deuterium Exchange Measurement Protein Conformation Deep Learning Proteins Molecular Docking Simulation
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MSCMLCIDTI: Drug-Target Interaction Prediction Based on Multiscale Feature Extraction and Deep Interactive Attention Fusion Mechanisms.

Journal of computational chemistry Jul 15, 2025
Drug-target interaction prediction serves as a crucial component in accelerating drug discovery. To overcome current limitations in deep learning approaches, specifically the inadequate representation of local features and insufficient modeling of dr...
Deep Learning Proteins Humans Pharmaceutical Preparations Drug Discovery
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Machine learning enabled protein secondary structure characterization using drop-coating deposition Raman spectroscopy.

Journal of pharmaceutical and biomedical analysis Jul 15, 2025
Protein structure characterization is critical for therapeutic protein drug development and production. Drop-coating deposition Raman (DCDR) spectroscopy offers rapid and cost-effective acquisition of vibrational spectral data characteristic of prote...
Proteins Least-Squares Analysis Algorithms Protein Structure, Secondary Machine Learning Spectrum Analysis, Raman
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