AIMC Topic: Receptors, Cytoplasmic and Nuclear

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A Machine Learning Approach for Drug-target Interaction Prediction using Wrapper Feature Selection and Class Balancing.

Molecular informatics Feb 11, 2020
Drug-Target interaction (DTI) plays a crucial role in drug discovery, drug repositioning and understanding the drug side effects which helps to identify new therapeutic profiles for various diseases. However, the exponential growth in the genomic and...
Computer Simulation Drug Discovery Drug Development Databases, Protein Machine Learning Algorithms Databases, Chemical Receptors, Cytoplasmic and Nuclear Enzymes Ion Channels Receptors, G-Protein-Coupled Pharmaceutical Preparations Amino Acid Sequence
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Prediction Model with High-Performance Constitutive Androstane Receptor (CAR) Using DeepSnap-Deep Learning Approach from the Tox21 10K Compound Library.

International journal of molecular sciences Sep 30, 2019
The constitutive androstane receptor (CAR) plays pivotal roles in drug-induced liver injury through the transcriptional regulation of drug-metabolizing enzymes and transporters. Thus, identifying regulatory factors for CAR activation is important for...
Constitutive Androstane Receptor Reproducibility of Results Drug Discovery Deep Learning Receptors, Cytoplasmic and Nuclear Algorithms Small Molecule Libraries Ligands Quantitative Structure-Activity Relationship
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Predicting drug-target interactions using Lasso with random forest based on evolutionary information and chemical structure.

Genomics Dec 11, 2018
The identification of drug-target interactions has great significance for pharmaceutical scientific research. Since traditional experimental methods identifying drug-target interactions is costly and time-consuming, the use of machine learning method...
Machine Learning Software Drug Development Receptors, Cytoplasmic and Nuclear Ion Channels Databases, Protein Position-Specific Scoring Matrices Receptors, G-Protein-Coupled Protein Conformation
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Prediction of Farnesoid X Receptor Disruptors with Machine Learning Methods.

Chemical research in toxicology Nov 8, 2018
The farnesoid X receptor (FXR) emerges as a promising drug target involved in regulating various metabolic pathways, yet some xenobiotic compounds binding to FXR would be an important determinant to induce the receptor dysfunctions that lead to undes...
Humans Machine Learning Databases, Factual ROC Curve Xenobiotics Area Under Curve Benzimidazoles Receptors, Cytoplasmic and Nuclear
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Mathematical deep learning for pose and binding affinity prediction and ranking in D3R Grand Challenges.

Journal of computer-aided molecular design Aug 16, 2018
Advanced mathematics, such as multiscale weighted colored subgraph and element specific persistent homology, and machine learning including deep neural networks were integrated to construct mathematical deep learning models for pose and binding affin...
Binding Sites Thermodynamics Cathepsins Protein Binding Databases, Protein Protein Kinases Protein Conformation Receptors, Cytoplasmic and Nuclear Ligands Crystallography, X-Ray Computer-Aided Design Drug Design Deep Learning Molecular Docking Simulation
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Chemogenomic Active Learning's Domain of Applicability on Small, Sparse qHTS Matrices: A Study Using Cytochrome P450 and Nuclear Hormone Receptor Families.

ChemMedChem Feb 5, 2018
Computational models for predicting the activity of small molecules against targets are now routinely developed and used in academia and industry, partially due to public bioactivity databases. While models based on bigger datasets are the trend, rec...
Small Molecule Libraries Cytochrome P-450 Enzyme Inhibitors Humans Machine Learning Algorithms Cytochrome P-450 Enzyme System Receptors, Cytoplasmic and Nuclear Databases, Factual Ligands
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Oleanolic acid protects against pathogenesis of atherosclerosis, possibly via FXR-mediated angiotensin (Ang)-(1-7) upregulation.

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie Dec 8, 2017
Atherosclerosis, the leading cause of cardiovascular diseases in the world, is a chronic inflammatory disorder characterized by the dysfunction of arteries. Oleanolic acid (OA) is a bioactive nature product which exists in various plants and herbs. P...
Protective Agents Diet, High-Fat Receptors, Cytoplasmic and Nuclear Lipoproteins, LDL Humans Angiotensins Disease Models, Animal Rabbits Human Umbilical Vein Endothelial Cells Cytokines Cell Cycle Apoptosis Up-Regulation Animals Atherosclerosis Oleanolic Acid Cell Survival
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Modern drug design: the implication of using artificial neuronal networks and multiple molecular dynamic simulations.

Journal of computer-aided molecular design Nov 13, 2017
We report the implementation of molecular modeling approaches developed as a part of the 2016 Grand Challenge 2, the blinded competition of computer aided drug design technologies held by the D3R Drug Design Data Resource ( https://drugdesigndata.org...
Humans Ligands Molecular Docking Simulation Protein Conformation Computer-Aided Design Receptors, Cytoplasmic and Nuclear Drug Design Neural Networks, Computer Binding Sites Protein Binding Machine Learning Molecular Dynamics Simulation
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Development of pharmacophore-based classification model for activators of constitutive androstane receptor.

Drug metabolism and pharmacokinetics Nov 17, 2016
Constitutive androstane receptor (CAR) is predominantly expressed in the liver and is important for regulating drug metabolism and transport. Despite its biological importance, there have been few attempts to develop in silico models to predict the a...
Humans Neural Networks, Computer Support Vector Machine Ligands Receptors, Cytoplasmic and Nuclear Constitutive Androstane Receptor
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Identification of New Fungal Peroxisomal Matrix Proteins and Revision of the PTS1 Consensus.

Traffic (Copenhagen, Denmark) Aug 22, 2016
The peroxisomal targeting signal type 1 (PTS1) is a seemingly simple peptide sequence at the C-terminal end of most peroxisomal matrix proteins. PTS1 can be described as a tripeptide with the consensus motif [S/A/C] [K/R/H] L. However, this descripti...
Consensus Sequence Peroxisome-Targeting Signal 1 Receptor Amino Acid Motifs Protein Sorting Signals Genome, Fungal Receptors, Cytoplasmic and Nuclear Peroxisomes Saccharomyces cerevisiae Proteins Machine Learning Genome-Wide Association Study Databases, Genetic Saccharomyces cerevisiae
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