AIMC Topic: Enzyme Inhibitors

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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...
Reproducibility of Results Molecular Docking Simulation Drug Discovery ROC Curve Humans Machine Learning Algorithms Databases, Chemical Quantitative Structure-Activity Relationship Diacylglycerol O-Acyltransferase Cheminformatics Models, Molecular Molecular Structure Molecular Dynamics Simulation Enzyme Inhibitors
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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 Machine Learning Structure-Activity Relationship Monophenol Monooxygenase Enzyme Inhibitors 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...
Enzymes Computational Biology Neural Networks, Computer Databases, Protein Machine Learning Enzyme Inhibitors Substrate Specificity
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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 ...
Antiviral Agents Coronavirus Infections Neuraminidase Acetylcholinesterase Molecular Docking Simulation Drug Design Influenza A virus Small Molecule Libraries Cysteine Endopeptidases Betacoronavirus Pneumonia, Viral Cholinesterase Inhibitors Enzyme Inhibitors Viral Nonstructural Proteins Humans Neural Networks, Computer Artificial Intelligence Pandemics COVID-19 SARS-CoV-2 Coronavirus 3C Proteases
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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...
Acetyltransferases Deep Learning Streptomyces Molecular Structure Enzyme Inhibitors Humans Drug Discovery
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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...
Humans Molecular Conformation Machine Learning Computer Simulation Drug Design Models, Molecular Enzyme Inhibitors
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Deep neural network affinity model for BACE inhibitors in D3R Grand Challenge 4.

Journal of computer-aided molecular design Jan 8, 2020
Drug Design Data Resource (D3R) Grand Challenge 4 (GC4) offered a unique opportunity for designing and testing novel methodology for accurate docking and affinity prediction of ligands in an open and blinded manner. We participated in the beta-secret...
Macrocyclic Compounds Binding Sites Humans Molecular Docking Simulation Ligands Neural Networks, Computer Drug Design Enzyme Inhibitors Protein Binding Amyloid Precursor Protein Secretases Aspartic Acid Endopeptidases
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Endocannabinoid degradation inhibitors ameliorate neuronal and synaptic alterations following traumatic brain injury.

Journal of neurophysiology Jan 8, 2020
Our previous work showed that lateral fluid percussion injury to the sensorimotor cortex (SMC) of anesthetized rats increased neuronal synaptic hyperexcitability in layer 5 (L5) neurons in ex vivo brain slices 10 days postinjury. Furthermore, endocan...
Brain Injuries, Traumatic Piperazines Piperidines Enzyme Inhibitors Carbamates Amidohydrolases Succinimides Animals Male Rats, Wistar Rats Machine Learning Monoacylglycerol Lipases Excitatory Postsynaptic Potentials Benzamides Pyramidal Cells Sensorimotor Cortex Electrophysiological Phenomena Endocannabinoids Benzodioxoles
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Deep learning enables rapid identification of potent DDR1 kinase inhibitors.

Nature biotechnology Sep 2, 2019
We have developed a deep generative model, generative tensorial reinforcement learning (GENTRL), for de novo small-molecule design. GENTRL optimizes synthetic feasibility, novelty, and biological activity. We used GENTRL to discover potent inhibitors...
Protein Conformation Animals Humans Discoidin Domain Receptor 1 Drug Evaluation, Preclinical Rats Deep Learning Microsomes, Liver Models, Molecular Mice Enzyme Inhibitors Molecular Structure Dogs
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Time-Domain Analysis of Molecular Dynamics Trajectories Using Deep Neural Networks: Application to Activity Ranking of Tankyrase Inhibitors.

Journal of chemical information and modeling Jul 19, 2019
Molecular dynamics simulations provide valuable insights into the behavior of molecular systems. Extending the recent trend of using machine learning techniques to predict physicochemical properties from molecular dynamics data, we propose to conside...
Molecular Dynamics Simulation Deep Learning Enzyme Inhibitors Time Factors Tankyrases Computational Biology
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