AIMC Topic: Protein Structure, Secondary

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Machine learning enabled protein secondary structure characterization using drop-coating deposition Raman spectroscopy.

Journal of pharmaceutical and biomedical analysis Feb 25, 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...
Machine Learning Proteins Least-Squares Analysis Protein Structure, Secondary Algorithms Spectrum Analysis, Raman
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Deciphering Protein Secondary Structures and Nucleic Acids in Cryo-EM Maps Using Deep Learning.

Journal of chemical information and modeling Jan 21, 2025
With the resolution revolution of cryo-electron microscopy (cryo-EM) and the rapid development of image processing technology, cryo-EM has become an indispensable experimental method for determining the three-dimensional structures of biological macr...
Protein Structure, Secondary Nucleic Acids Cryoelectron Microscopy Proteins Models, Molecular Deep Learning
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Lessons from Deep Learning Structural Prediction of Multistate Multidomain Proteins-The Case Study of Coiled-Coil NOD-like Receptors.

International journal of molecular sciences Jan 9, 2025
We test here the prediction capabilities of the new generation of deep learning predictors in the more challenging situation of multistate multidomain proteins by using as a case study a coiled-coil family of Nucleotide-binding Oligomerization Domain...
Deep Learning Computational Biology Protein Structure, Secondary Arabidopsis Models, Molecular Protein Domains NLR Proteins Protein Conformation
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Porter 6: Protein Secondary Structure Prediction by Leveraging Pre-Trained Language Models (PLMs).

International journal of molecular sciences Dec 27, 2024
Accurately predicting protein secondary structure (PSSP) is crucial for understanding protein function, which is foundational to advancements in drug development, disease treatment, and biotechnology. Researchers gain critical insights into protein f...
Computational Biology Proteins Natural Language Processing Protein Structure, Secondary Algorithms Deep Learning Software
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AlphaMut: A Deep Reinforcement Learning Model to Suggest Helix-Disrupting Mutations.

Journal of chemical theory and computation Dec 19, 2024
Helices are important secondary structural motifs within proteins and are pivotal in numerous physiological processes. While amino acids (AA) such as alanine and leucine are known to promote helix formation, proline and glycine disfavor it. Helical s...
Models, Molecular Mutation Deep Learning Proteins Reinforcement Machine Learning Thermodynamics Protein Structure, Secondary
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Impact of Multi-Factor Features on Protein Secondary Structure Prediction.

Biomolecules Sep 13, 2024
Protein secondary structure prediction (PSSP) plays a crucial role in resolving protein functions and properties. Significant progress has been made in this field in recent years, and the use of a variety of protein-related features, including amino ...
Protein Structure, Secondary Computational Biology Proteins Machine Learning Amino Acids Amino Acid Sequence Databases, Protein
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Protein Classes Predicted by Molecular Surface Chemical Features: Machine Learning-Assisted Classification of Cytosol and Secreted Proteins.

The journal of physical chemistry. B Aug 26, 2024
Chemical structures of protein surfaces govern intermolecular interaction, and protein functions include specific molecular recognition, transport, self-assembly, etc. Therefore, the relationship between the chemical structure and protein functions p...
Proteins Databases, Protein Machine Learning Surface Properties Protein Structure, Secondary Cytosol
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Insights into the Interaction Mechanisms of Peptide and Non-Peptide Inhibitors with MDM2 Using Gaussian-Accelerated Molecular Dynamics Simulations and Deep Learning.

Molecules (Basel, Switzerland) Jul 18, 2024
Inhibiting MDM2-p53 interaction is considered an efficient mode of cancer treatment. In our current study, Gaussian-accelerated molecular dynamics (GaMD), deep learning (DL), and binding free energy calculations were combined together to probe the bi...
Proto-Oncogene Proteins c-mdm2 Peptides Protein Structure, Tertiary Deep Learning Protein Binding Binding Sites Molecular Dynamics Simulation Protein Structure, Secondary Hydrogen Bonding
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Unraveling dynamic protein structures by two-dimensional infrared spectra with a pretrained machine learning model.

Proceedings of the National Academy of Sciences of the United States of America Jun 25, 2024
Dynamic protein structures are crucial for deciphering their diverse biological functions. Two-dimensional infrared (2DIR) spectroscopy stands as an ideal tool for tracing rapid conformational evolutions in proteins. However, linking spectral charact...
Protein Conformation Protein Structure, Secondary Spectrophotometry, Infrared Machine Learning Protein Folding Proteins
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Kinetic Ensemble of Tau Protein through the Markov State Model and Deep Learning Analysis.

Journal of chemical theory and computation Mar 19, 2024
The ordered assembly of Tau protein into filaments characterizes Alzheimer's and other neurodegenerative diseases, and thus, stabilization of Tau protein is a promising avenue for tauopathies therapy. To dissect the underlying aggregation mechanisms ...
Protein Structure, Secondary gamma-Globulins Amino Acid Sequence Humans Tauopathies tau Proteins Melphalan Deep Learning
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