AIMC Topic: Adenosine Triphosphate

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Spatiotemporal identification of druggable binding sites using deep learning.

Communications biology Oct 27, 2020
Identification of novel protein binding sites expands druggable genome and opens new opportunities for drug discovery. Generally, presence or absence of a binding site depends on the three-dimensional conformation of a protein, making binding site id...
Software Drug Delivery Systems Deep Learning Protein Binding Protein Conformation Binding Sites Ion Channel Gating Receptors, Purinergic P2X3 Receptors, G-Protein-Coupled Models, Molecular Models, Biological Adenosine Triphosphate
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Design a fluorometric aptasensor based on CoOOH nanosheets and carbon dots for simultaneous detection of lysozyme and adenosine triphosphate.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Feb 29, 2020
Simultaneous detection of biomarkers and biomolecules with great analytical performance still is challenging. A simple fluorometric dual-functional aptasensor was designed to detect Lysozyme (LYS) and adenosine triphosphate (ATP) as models of a prote...
Adenosine Triphosphate Cobalt Electronic Data Processing Muramidase Aptamers, Nucleotide Biosensing Techniques Support Vector Machine Quantum Dots Spectrometry, Fluorescence Oxides
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A Multi-Omics Interpretable Machine Learning Model Reveals Modes of Action of Small Molecules.

Scientific reports Jan 22, 2020
High-throughput screening and gene signature analyses frequently identify lead therapeutic compounds with unknown modes of action (MoAs), and the resulting uncertainties can lead to the failure of clinical trials. We developed an approach for uncover...
Humans Machine Learning Animals Gene Regulatory Networks Adenosine Triphosphate Huntington Disease Metabolomics Cell Line Mice Cell Survival Genomics Autophagy Computational Biology Proteomics
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Recognizing five molecular ligand-binding sites with similar chemical structure.

Journal of computational chemistry Oct 23, 2019
Accurate identification of ligand-binding sites and discovering the protein-ligand interaction mechanism are important for understanding proteins' functions and designing new drugs. Meanwhile, accurate computational prediction and mechanism research ...
Proteins Adenosine Triphosphate Ligands Binding Sites NAD Guanosine Triphosphate Adenosine Diphosphate Guanosine Diphosphate Support Vector Machine
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Novel Screening Method Identifies PI3Kα, mTOR, and IGF1R as Key Kinases Regulating Cardiomyocyte Survival.

Journal of the American Heart Association Oct 16, 2019
Background Small molecule kinase inhibitors (KIs) are a class of agents currently used for treatment of various cancers. Unfortunately, treatment of cancer patients with some of the KIs is associated with cardiotoxicity, and there is an unmet need fo...
Cell Survival Receptor, IGF Type 1 Phosphatidylinositol 3-Kinases TOR Serine-Threonine Kinases Machine Learning Cells, Cultured Animals Rats Adenosine Triphosphate Myocytes, Cardiac Protein Kinase Inhibitors Cardiotoxins
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Neural-network classification of cardiac disease from P cardiovascular magnetic resonance spectroscopy measures of creatine kinase energy metabolism.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance Aug 12, 2019
BACKGROUND: The heart's energy demand per gram of tissue is the body's highest and creatine kinase (CK) metabolism, its primary energy reserve, is compromised in common heart diseases. Here, neural-network analysis is used to test whether noninvasive...
Humans Adenosine Triphosphate Heart Diseases Adult Energy Metabolism Male Middle Aged Severity of Illness Index Predictive Value of Tests Myocardium Creatine Kinase Kinetics Reproducibility of Results Aged Aged, 80 and over Young Adult Neural Networks, Computer Machine Learning Biomarkers Female Magnetic Resonance Spectroscopy Phosphocreatine Phosphorus Isotopes
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Prediction of ATP-binding sites in membrane proteins using a two-dimensional convolutional neural network.

Journal of molecular graphics & modelling Jul 15, 2019
Membrane proteins, the most important drug targets, account for around 30% of total proteins encoded by the genome of living organisms. An important role of these proteins is to bind adenosine triphosphate (ATP), facilitating crucial biological proce...
Databases, Protein Amino Acid Sequence Adenosine Triphosphate Binding Sites Amino Acid Motifs Web Browser Position-Specific Scoring Matrices ROC Curve Computational Biology Membrane Proteins Models, Theoretical Machine Learning Algorithms Reproducibility of Results Neural Networks, Computer
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Machine-Learning-Driven Surface-Enhanced Raman Scattering Optophysiology Reveals Multiplexed Metabolite Gradients Near Cells.

ACS nano Feb 12, 2019
The extracellular environment is a complex medium in which cells secrete and consume metabolites. Molecular gradients are thereby created near cells, triggering various biological and physiological responses. However, investigating these molecular gr...
Humans Human Umbilical Vein Endothelial Cells Machine Learning Adenosine Triphosphate HeLa Cells Biosensing Techniques Spectrum Analysis, Raman Fibroblasts
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ATPbind: Accurate Protein-ATP Binding Site Prediction by Combining Sequence-Profiling and Structure-Based Comparisons.

Journal of chemical information and modeling Feb 8, 2018
Protein-ATP interactions are ubiquitous in a wide variety of biological processes. Correctly locating ATP binding sites from protein information is an important but challenging task for protein function annotation and drug discovery. However, there i...
Solvents Binding Sites Protein Structure, Secondary Support Vector Machine Proteins Databases, Protein Adenosine Triphosphate
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HEPNet: A Knowledge Base Model of Human Energy Pool Network for Predicting the Energy Availability Status of an Individual.

PloS one Jun 8, 2015
HEPNet is an electronic representation of metabolic reactions occurring within human cellular organization focusing on inflow and outflow of the energy currency ATP, GTP and other energy associated moieties. The backbone of HEPNet consists of primary...
Energy Metabolism Semantics Uremia NAD Acyl Coenzyme A Carnitine Ketoglutaric Acids Phosphocreatine Glucose Models, Biological Knowledge Bases Adenosine Triphosphate Humans Computer Simulation Reproducibility of Results
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