AIMC Topic: Protein Domains

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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...
Humans Animals Drug Discovery Deep Learning Datasets as Topic Binding Sites Caenorhabditis elegans Protein Structure, Secondary Protein Binding Protein Domains Ligands
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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...
Area Under Curve Models, Molecular Protein Domains Membrane Proteins Neural Networks, Computer Databases, Protein Sensitivity and Specificity Reproducibility of Results Deep Learning
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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...
Animals Deep Learning Protein Binding Proteome Humans Algorithms Protein Domains Phosphoproteins Statistics as Topic Signal Transduction Binding Sites Databases, Protein Phosphorylation
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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 Proteins Software Sequence Analysis, Protein Databases, Protein Protein Domains Humans Animals Protein Structure, Quaternary Algorithms Viral Proteins Machine Learning Computational Biology
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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...
Receptors, G-Protein-Coupled Protein Domains Ligands Humans Machine Learning Protein Binding
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Sequence-Based Prediction of Fuzzy Protein Interactions.

Journal of molecular biology Feb 27, 2020
It is becoming increasingly recognised that disordered proteins may be fuzzy, in that they can exhibit a wide variety of binding modes. In addition to the well-known process of folding upon binding (disorder-to-order transition), many examples are em...
Protein Folding Sequence Analysis, Protein Protein Interaction Domains and Motifs Amino Acid Sequence Intrinsically Disordered Proteins Protein Conformation Sequence Homology Humans Algorithms Protein Binding Models, Molecular Protein Domains Fuzzy Logic Databases, Protein
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Learning a functional grammar of protein domains using natural language word embedding techniques.

Proteins Nov 25, 2019
In this paper, using Word2vec, a widely-used natural language processing method, we demonstrate that protein domains may have a learnable implicit semantic "meaning" in the context of their functional contributions to the multi-domain proteins in whi...
Proteins Databases, Protein Natural Language Processing Semantics Molecular Sequence Annotation Protein Domains Datasets as Topic Humans Gene Ontology
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Computational and artificial neural network based study of functional SNPs of human LEPR protein associated with reproductive function.

Journal of cellular biochemistry Jun 25, 2019
Genetic polymorphisms are mostly associated with inherited diseases, detecting and analyzing the biological significance of functional single-nucleotide polymorphisms (SNPs) using wet laboratory experiments is an arduous task hence the computational ...
Neural Networks, Computer Receptors, Leptin Molecular Docking Simulation Protein Domains Infertility Polymorphism, Single Nucleotide Humans Amino Acid Substitution Mutation, Missense
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DeepACLSTM: deep asymmetric convolutional long short-term memory neural models for protein secondary structure prediction.

BMC bioinformatics Jun 17, 2019
BACKGROUND: Protein secondary structure (PSS) is critical to further predict the tertiary structure, understand protein function and design drugs. However, experimental techniques of PSS are time consuming and expensive, and thus it's very urgent to ...
Neural Networks, Computer Protein Domains Deep Learning Algorithms Protein Structure, Secondary Models, Theoretical Proteins
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Predicting drug-target interaction network using deep learning model.

Computational biology and chemistry Mar 25, 2019
BACKGROUND: Traditional methods for drug discovery are time-consuming and expensive, so efforts are being made to repurpose existing drugs. To find new ways for drug repurposing, many computational approaches have been proposed to predict drug-target...
Databases, Chemical Genes, Neoplasm Proteins Protein Binding Breast Neoplasms Databases, Protein Molecular Structure Protein Domains Computational Biology Antineoplastic Agents Drug Repositioning Models, Chemical Amino Acid Sequence Support Vector Machine Deep Learning
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