AIMC Topic: Enzyme Inhibitors

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LCP: Simple Representation of Docking Poses for Machine Learning: A Case Study on Xanthine Oxidase Inhibitors.

Molecular informatics Nov 29, 2021
In this paper, we propose a simple descriptor called the ligand coordinate profile (LCP) for describing docking poses. The LCP descriptor is generated from the coordinates of the polar hydrogen and heavy atoms of the docked ligand. We hypothesize tha...
Protein Binding Ligands Enzyme Inhibitors Xanthine Oxidase Machine Learning Molecular Docking Simulation
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StackHCV: a web-based integrative machine-learning framework for large-scale identification of hepatitis C virus NS5B inhibitors.

Journal of computer-aided molecular design Oct 8, 2021
Fast and accurate identification of inhibitors with potency against HCV NS5B polymerase is currently a challenging task. As conventional experimental methods is the gold standard method for the design and development of new HCV inhibitors, they often...
Internet Hepacivirus Hepatitis C Enzyme Inhibitors Algorithms Antiviral Agents Support Vector Machine Viral Nonstructural Proteins RNA-Dependent RNA Polymerase Humans Machine Learning
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Identification of kinase inhibitors that rule out the CYP27B1-mediated activation of vitamin D: an integrated machine learning and structure-based drug designing approach.

Molecular diversity Jul 16, 2021
CYP27B1, a cytochrome P450-containing hydroxylase enzyme, converts vitamin D precursor calcidiol (25-hydroxycholecalciferol) to its active form calcitriol (1α,25(OH)D). Tyrosine kinase inhibitor such as imatinib is reported to interfere with the acti...
25-Hydroxyvitamin D3 1-alpha-Hydroxylase Structure-Activity Relationship Metabolic Networks and Pathways Models, Molecular Protein Binding Support Vector Machine Vitamin D Small Molecule Libraries Databases, Pharmaceutical Phosphotransferases Molecular Dynamics Simulation Amino Acid Sequence Enzyme Inhibitors Binding Sites Neural Networks, Computer Machine Learning Algorithms Reproducibility of Results Animals Molecular Docking Simulation Drug Design Humans
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Ensemble learning application to discover new trypanothione synthetase inhibitors.

Molecular diversity Jul 15, 2021
Trypanosomatid-caused diseases are among the neglected infectious diseases with the highest disease burden, affecting about 27 million people worldwide and, in particular, socio-economically vulnerable populations. Trypanothione synthetase (TryS) is ...
Humans Drug Evaluation, Preclinical ROC Curve Databases, Pharmaceutical Enzyme Inhibitors Machine Learning Models, Theoretical Amide Synthases Antiprotozoal Agents Algorithms Structure-Activity Relationship Drug Discovery Metabolic Networks and Pathways
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Discovery of novel DGAT1 inhibitors by combination of machine learning methods, pharmacophore model and 3D-QSAR model.

Molecular diversity Jun 23, 2021
DGAT1 plays a crucial controlling role in triglyceride biosynthetic pathways, which makes it an attractive therapeutic target for obesity. Thus, development of DGAT1 inhibitors with novel chemical scaffolds is desired and important in the drug discov...
Quantitative Structure-Activity Relationship Diacylglycerol O-Acyltransferase Cheminformatics Molecular Dynamics Simulation Enzyme Inhibitors Databases, Chemical Machine Learning Algorithms Reproducibility of Results Molecular Docking Simulation Drug Discovery ROC Curve Models, Molecular Molecular Structure Humans
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SAR and QSAR research on tyrosinase inhibitors using machine learning methods.

SAR and QSAR in environmental research Feb 1, 2021
Tyrosinase is a key rate-limiting enzyme in the process of melanin synthesis, which is closely related to human pigmentation disorders. Tyrosinase inhibitors can down-regulate tyrosinase to effectively reduce melanin synthesis. In this work, we condu...
Neural Networks, Computer Monophenol Monooxygenase Machine Learning Enzyme Inhibitors Structure-Activity Relationship Quantitative Structure-Activity Relationship
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Enzyme Promiscuity Prediction Using Hierarchy-Informed Multi-Label Classification.

Bioinformatics (Oxford, England) Jan 30, 2021
MOTIVATION: As experimental efforts are costly and time consuming, computational characterization of enzyme capabilities is an attractive alternative. We present and evaluate several machine-learning models to predict which of 983 distinct enzymes, a...
Neural Networks, Computer Machine Learning Computational Biology Databases, Protein Enzyme Inhibitors Substrate Specificity Enzymes
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Drug Design of Targeted Chemical Libraries Based on Artificial Intelligence and Pair-Based Multiobjective Optimization.

Journal of chemical information and modeling Sep 9, 2020
Artificial intelligence and multiobjective optimization represent promising solutions to bridge chemical and biological landscapes by addressing the automated design of compounds as a result of a humanlike creative process. In the present study, we ...
Cysteine Endopeptidases Betacoronavirus Pneumonia, Viral Coronavirus 3C Proteases Enzyme Inhibitors Viral Nonstructural Proteins Pandemics Small Molecule Libraries COVID-19 SARS-CoV-2 Molecular Docking Simulation Humans Neural Networks, Computer Artificial Intelligence Coronavirus Infections Drug Design Neuraminidase Influenza A virus Acetylcholinesterase Antiviral Agents Cholinesterase Inhibitors
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Discovery of Novel Inhibitors of a Critical Brain Enzyme Using a Homology Model and a Deep Convolutional Neural Network.

Journal of medicinal chemistry Jul 30, 2020
Rare neglected diseases may be neglected but are hardly rare, affecting hundreds of millions of people around the world. Here, we present a hit identification approach using AtomNet, the world's first deep convolutional neural network for structure-b...
Humans Drug Discovery Deep Learning Streptomyces Molecular Structure Enzyme Inhibitors Acetyltransferases
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Cov_FB3D: A De Novo Covalent Drug Design Protocol Integrating the BA-SAMP Strategy and Machine-Learning-Based Synthetic Tractability Evaluation.

Journal of chemical information and modeling Apr 9, 2020
drug design actively seeks to use sets of chemical rules for the fast and efficient identification of structurally new chemotypes with the desired set of biological properties. Fragment-based design tools have been successfully applied in the disco...
Drug Design Humans Machine Learning Models, Molecular Computer Simulation Enzyme Inhibitors Molecular Conformation
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