AIMC Topic: Protein Domains

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Prediction of Protein Solubility Based on Sequence Feature Fusion and DDcCNN.

Interdisciplinary sciences, computational life sciences Jul 8, 2021
BACKGROUND: Prediction of protein solubility is an indispensable prerequisite for pharmaceutical research and production. The general and specific objective of this work is to design a new model for predicting protein solubility by using protein sequ...
Proteins Protein Domains Amino Acid Sequence Solubility Neural Networks, Computer
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TopDomain: Exhaustive Protein Domain Boundary Metaprediction Combining Multisource Information and Deep Learning.

Journal of chemical theory and computation Jun 23, 2021
Protein domains are independent, functional, and stable structural units of proteins. Accurate protein domain boundary prediction plays an important role in understanding protein structure and evolution, as well as for protein structure prediction. C...
Deep Learning Computational Biology Proteins Algorithms Protein Domains Protein Conformation
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Improving protein domain classification for third-generation sequencing reads using deep learning.

BMC genomics Apr 9, 2021
BACKGROUND: With the development of third-generation sequencing (TGS) technologies, people are able to obtain DNA sequences with lengths from 10s to 100s of kb. These long reads allow protein domain annotation without assembly, thus can produce impor...
Protein Domains Humans Algorithms High-Throughput Nucleotide Sequencing Software Deep Learning Sequence Analysis, DNA
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Characterizing the function of domain linkers in regulating the dynamics of multi-domain fusion proteins by microsecond molecular dynamics simulations and artificial intelligence.

Proteins Mar 27, 2021
Multi-domain proteins are not only formed through natural evolution but can also be generated by recombinant DNA technology. Because many fusion proteins can enhance the selectivity of cell targeting, these artificially produced molecules, called mul...
Artificial Intelligence Computational Biology Gene Expression Protein Domains Humans Mutagenesis, Insertional Amino Acids Benchmarking Molecular Dynamics Simulation Recombinant Fusion Proteins Protein Engineering Pliability
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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...
Cations, Divalent Protein Structure, Secondary Electron Transport Complex IV Disulfides Sulfonic Acids Cysteine Nitroso Compounds Sulfinic Acids Structure-Activity Relationship Models, Molecular Protein Domains Amino Acid Sequence Sulfides Glutathione Software Deep Learning Protein Processing, Post-Translational
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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...
Binding Sites Animals Caenorhabditis elegans Drug Discovery Protein Structure, Secondary Deep Learning Ligands Datasets as Topic Protein Binding Protein Domains Humans
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DEEPSMP: A deep learning model for predicting the ectodomain shedding events of membrane proteins.

Journal of bioinformatics and computational biology Jun 23, 2020
Membrane proteins play essential roles in modern medicine. In recent studies, some membrane proteins involved in ectodomain shedding events have been reported as the potential drug targets and biomarkers of some serious diseases. However, there are f...
Neural Networks, Computer Reproducibility of Results Sensitivity and Specificity Deep Learning Models, Molecular Protein Domains Membrane Proteins Databases, Protein Area Under Curve
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GPS-PBS: A Deep Learning Framework to Predict Phosphorylation Sites that Specifically Interact with Phosphoprotein-Binding Domains.

Cells May 20, 2020
Protein phosphorylation is essential for regulating cellular activities by modifying substrates at specific residues, which frequently interact with proteins containing phosphoprotein-binding domains (PPBDs) to propagate the phosphorylation signaling...
Statistics as Topic Binding Sites Phosphorylation Protein Domains Phosphoproteins Proteome Signal Transduction Databases, Protein Animals Humans Deep Learning Algorithms Protein Binding
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QUATgo: Protein quaternary structural attributes predicted by two-stage machine learning approaches with heterogeneous feature encoding.

PloS one Apr 29, 2020
Many proteins exist in natures as oligomers with various quaternary structural attributes rather than as single chains. Predicting these attributes is an essential task in computational biology for the advancement of proteomics. However, the existing...
Support Vector Machine Protein Structure, Quaternary Humans Algorithms Protein Domains Proteins Animals Machine Learning Databases, Protein Viral Proteins Computational Biology Software Sequence Analysis, Protein
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Machine Learning to Identify Flexibility Signatures of Class A GPCR Inhibition.

Biomolecules Mar 14, 2020
We show that machine learning can pinpoint features distinguishing inactive from active states in proteins, in particular identifying key ligand binding site flexibility transitions in GPCRs that are triggered by biologically active ligands. Our anal...
Protein Binding Receptors, G-Protein-Coupled Protein Domains Humans Ligands Machine Learning
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