AIMC Topic: Protein Structure, Secondary

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Detecting protein and DNA/RNA structures in cryo-EM maps of intermediate resolution using deep learning.

Nature communications Apr 16, 2021
An increasing number of density maps of macromolecular structures, including proteins and DNA/RNA complexes, have been determined by cryo-electron microscopy (cryo-EM). Although lately maps at a near-atomic resolution are routinely reported, there ar...
Software Deep Learning Computational Biology Nucleic Acid Conformation Cryoelectron Microscopy DNA Models, Molecular RNA Protein Structure, Secondary
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A novel end-to-end method to predict RNA secondary structure profile based on bidirectional LSTM and residual neural network.

BMC bioinformatics Mar 31, 2021
BACKGROUND: Studies have shown that RNA secondary structure, a planar structure formed by paired bases, plays diverse vital roles in fundamental life activities and complex diseases. RNA secondary structure profile can record whether each base is pai...
Binding Sites Protein Structure, Secondary Research Design Neural Networks, Computer RNA
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DeepCys: Structure-based multiple cysteine function prediction method trained on deep neural network: Case study on domains of unknown functions belonging to COX2 domains.

Proteins Feb 22, 2021
Cysteine (Cys) is the most reactive amino acid participating in a wide range of biological functions. In-silico predictions complement the experiments to meet the need of functional characterization. Multiple Cys function prediction algorithm is scar...
Deep Learning Protein Processing, Post-Translational Structure-Activity Relationship Software Sulfides Glutathione Disulfides Protein Domains Amino Acid Sequence Models, Molecular Nitroso Compounds Sulfinic Acids Cations, Divalent Protein Structure, Secondary Electron Transport Complex IV Sulfonic Acids Cysteine
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Comprehensive Study on Enhancing Low-Quality Position-Specific Scoring Matrix with Deep Learning for Accurate Protein Structure Property Prediction: Using Bagging Multiple Sequence Alignment Learning.

Journal of computational biology : a journal of computational molecular cell biology Feb 22, 2021
Sequence Alignment Position-Specific Scoring Matrices Protein Conformation Protein Structure, Secondary Neural Networks, Computer Deep Learning Computational Biology Algorithms Proteins
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Structural protein fold recognition based on secondary structure and evolutionary information using machine learning algorithms.

Computational biology and chemistry Feb 12, 2021
Understanding the function of protein is conducive to research in advanced fields such as gene therapy of diseases, the development and design of new drugs, etc. The prerequisite for understanding the function of a protein is to determine its tertiar...
Protein Folding Machine Learning Algorithms Amino Acid Sequence Protein Structure, Secondary Databases, Protein Humans
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OCLSTM: Optimized convolutional and long short-term memory neural network model for protein secondary structure prediction.

PloS one Feb 3, 2021
Protein secondary structure prediction is extremely important for determining the spatial structure and function of proteins. In this paper, we apply an optimized convolutional neural network and long short-term memory neural network models to protei...
Protein Structure, Secondary Proteins Computational Biology Neural Networks, Computer Bayes Theorem
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SSnet: A Deep Learning Approach for Protein-Ligand Interaction Prediction.

International journal of molecular sciences Jan 30, 2021
Computational prediction of Protein-Ligand Interaction (PLI) is an important step in the modern drug discovery pipeline as it mitigates the cost, time, and resources required to screen novel therapeutics. Deep Neural Networks (DNN) have recently show...
Protein Domains Ligands Binding Sites Caenorhabditis elegans Datasets as Topic Drug Discovery Deep Learning Protein Binding Protein Structure, Secondary Humans Animals
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Prediction of secondary structure population and intrinsic disorder of proteins using multitask deep learning.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 25, 2021
Recent research in predicting protein secondary structure populations (SSP) based on Nuclear Magnetic Resonance (NMR) chemical shifts has helped quantitatively characterise the structural conformational properties of intrinsically disordered proteins...
Protein Structure, Secondary Deep Learning Intrinsically Disordered Proteins
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Protein molecular defect detection method based on a neural network algorithm.

Cellular and molecular biology (Noisy-le-Grand, France) Oct 31, 2020
Proteins, as the largest macromolecules in the body, are among the most important components of the body and play very vital and important roles. These substances are made up of a series of amino acid chains that, depending on the type of protein, th...
Computational Biology Proteins Amino Acid Sequence Neural Networks, Computer Databases, Protein Protein Structure, Secondary Algorithms
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A Machine Learning Protocol for Predicting Protein Infrared Spectra.

Journal of the American Chemical Society Oct 30, 2020
Infrared (IR) absorption provides important chemical fingerprints of biomolecules. Protein secondary structure determination from IR spectra is tedious since its theoretical interpretation requires repeated expensive quantum-mechanical calculations i...
Peptides Proteins Amides Spectrophotometry, Infrared Quantum Theory Protein Structure, Secondary Machine Learning Ubiquitin Protein Folding Temperature
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