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Protein Structure, Secondary

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DeepSS2GO: protein function prediction from secondary structure.

Briefings in bioinformatics 38701416
Predicting protein function is crucial for understanding biological life processes, preventing diseases and developing new drug targets. In recent years, methods based on sequence, structure and biological networks for protein function annotation hav...
Algorithms Computational Biology Databases, Protein Gene Ontology Neural Networks, Computer Protein Structure, Secondary Proteins Sequence Analysis, Protein Software
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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 38917009
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...
Machine Learning Protein Conformation Protein Folding Protein Structure, Secondary Proteins Spectrophotometry, Infrared
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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) 39064955
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...
Binding Sites Deep Learning Hydrogen Bonding Molecular Dynamics Simulation Peptides Protein Binding Protein Structure, Secondary Protein Structure, Tertiary Proto-Oncogene Proteins c-mdm2
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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 39185763
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...
Cytosol Databases, Protein Machine Learning Protein Structure, Secondary Proteins Surface Properties
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Impact of Multi-Factor Features on Protein Secondary Structure Prediction.

Biomolecules 39334921
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 ...
Amino Acid Sequence Amino Acids Computational Biology Databases, Protein Machine Learning Protein Structure, Secondary Proteins
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Porter 6: Protein Secondary Structure Prediction by Leveraging Pre-Trained Language Models (PLMs).

International journal of molecular sciences 39795988
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...
Algorithms Computational Biology Deep Learning Natural Language Processing Protein Structure, Secondary Proteins Software
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AlphaMut: A Deep Reinforcement Learning Model to Suggest Helix-Disrupting Mutations.

Journal of chemical theory and computation 39702999
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...
Deep Learning Models, Molecular Mutation Protein Structure, Secondary Proteins Reinforcement Machine Learning Thermodynamics
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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 39859213
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...
Arabidopsis Computational Biology Deep Learning Models, Molecular NLR Proteins Protein Conformation Protein Domains Protein Structure, Secondary
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Deciphering Protein Secondary Structures and Nucleic Acids in Cryo-EM Maps Using Deep Learning.

Journal of chemical information and modeling 39838545
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...
Cryoelectron Microscopy Deep Learning Models, Molecular Nucleic Acids Protein Structure, Secondary Proteins
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Machine learning enabled protein secondary structure characterization using drop-coating deposition Raman spectroscopy.

Journal of pharmaceutical and biomedical analysis 40031131
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...
Algorithms Least-Squares Analysis Machine Learning Protein Structure, Secondary Proteins Spectrum Analysis, Raman
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