AIMC Topic: Models, Molecular

Clear Filters Showing 381 to 390 of 759 articles

A protein folding robot driven by a self-taught agent.

Bio Systems Dec 29, 2020
This paper presents a computer simulation of a virtual robot that behaves as a peptide chain of the Hemagglutinin-Esterase protein (HEs) from human coronavirus. The robot can learn efficient protein folding policies by itself and then use them to sol...
Robotics Models, Molecular Amino Acid Sequence Computer Simulation Systems Biology Protein Folding Systems Analysis Coronavirus Protein Conformation Viral Proteins Humans Machine Learning Algorithms Neural Networks, Computer Hemagglutinins, Viral Viral Fusion Proteins
View on PubMed DOI

Machine Learning in Predictive Toxicology: Recent Applications and Future Directions for Classification Models.

Chemical research in toxicology Dec 23, 2020
In recent times, machine learning has become increasingly prominent in predictive toxicology as it has shifted from studies toward studies. Currently, methods together with other computational methods such as quantitative structure-activity relati...
Quantitative Structure-Activity Relationship Toxicity Tests Humans Machine Learning Models, Molecular
View on PubMed DOI

Combining Data with Predictions for Modeling Hepatic Steatosis by Using Stratified Bagging and Conformal Prediction.

Chemical research in toxicology Dec 21, 2020
Hepatic steatosis (fatty liver) is a severe liver disease induced by the excessive accumulation of fatty acids in hepatocytes. In this study, we developed reliable models for predicting hepatic steatosis on the basis of an data set of 1041 compound...
Machine Learning Databases, Factual Humans Hydrocarbons, Acyclic Computer Simulation Fatty Liver Molecular Conformation Hydrocarbons, Aromatic Models, Molecular
View on PubMed DOI

A Molecular Image-Based Novel Quantitative Structure-Activity Relationship Approach, Deepsnap-Deep Learning and Machine Learning.

Current issues in molecular biology Dec 19, 2020
The quantitative structure-activity relationship (QSAR) approach has been used in numerous chemical compounds as computational assessment for a long time. Further, owing to the high-performance modeling of QSAR, machine learning methods have been de...
Deep Learning Models, Molecular Quantitative Structure-Activity Relationship Machine Learning
View on PubMed DOI

HDAC3i-Finder: A Machine Learning-based Computational Tool to Screen for HDAC3 Inhibitors.

Molecular informatics Nov 23, 2020
Histone deacetylase 3 (HDAC3) is a potential drug target for treatment of human diseases such as cancer, chronic inflammation, neurodegenerative diseases and diabetes. Machine learning (ML) as an essential cheminformatics approach has been widely use...
Humans Histone Deacetylases Molecular Structure Drug Evaluation, Preclinical Histone Deacetylase Inhibitors Machine Learning Models, Molecular
View on PubMed DOI

Label-free SERS detection of proteins based on machine learning classification of chemo-structural determinants.

The Analyst Nov 19, 2020
Establishing standardized methods for a consistent analysis of spectral data remains a largely underexplored aspect in surface-enhanced Raman spectroscopy (SERS), particularly applied to biological and biomedical research. Here we propose an effectiv...
Machine Learning Models, Molecular Silver Spectrum Analysis, Raman Protein Conformation Nanowires
View on PubMed DOI

Assessing hERG1 Blockade from Bayesian Machine-Learning-Optimized Site Identification by Ligand Competitive Saturation Simulations.

Journal of chemical information and modeling Nov 16, 2020
Drug-induced cardiotoxicity is a potentially lethal and yet one of the most common side effects with the drugs in clinical use. Most of the drug-induced cardiotoxicity is associated with an off-target pharmacological blockade of K currents carried ou...
Models, Molecular Bayes Theorem Ether-A-Go-Go Potassium Channels Ligands Humans Machine Learning Molecular Docking Simulation
View on PubMed DOI

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...
Models, Molecular Deep Learning Models, Biological Protein Binding Protein Conformation Receptors, G-Protein-Coupled Binding Sites Software Adenosine Triphosphate Drug Delivery Systems Ion Channel Gating Receptors, Purinergic P2X3
View on PubMed DOI

Machine learning-accelerated quantum mechanics-based atomistic simulations for industrial applications.

Journal of computer-aided molecular design Oct 9, 2020
Atomistic simulations have become an invaluable tool for industrial applications ranging from the optimization of protein-ligand interactions for drug discovery to the design of new materials for energy applications. Here we review recent advances in...
Machine Learning Drug Design Drug Discovery Quantum Theory Ligands Models, Molecular Pharmaceutical Preparations
View on PubMed DOI

Predictive Modeling of Angiotensin I-Converting Enzyme Inhibitory Peptides Using Various Machine Learning Approaches.

Journal of agricultural and food chemistry Oct 1, 2020
Food-derived angiotensin I-converting enzyme (ACE) inhibitory peptides could potentially be used as safe supportive therapeutic products for high blood pressure. Theoretical approaches are promising methods with the advantage through exploring the re...
Machine Learning Models, Molecular Angiotensin-Converting Enzyme Inhibitors Hydrogen Bonding Peptides Molecular Docking Simulation Peptidyl-Dipeptidase A
View on PubMed DOI
Popular Topics
Recent Journals