AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Models, Molecular

Showing 291 to 300 of 628 articles

Clear Filters

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...
Humans Machine Learning Bayes Theorem Ligands Ether-A-Go-Go Potassium Channels Molecular Docking Simulation Models, Molecular
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 Models, Biological Adenosine Triphosphate Protein Binding Receptors, G-Protein-Coupled Ion Channel Gating Receptors, Purinergic P2X3 Protein Conformation Binding Sites Drug Delivery Systems Deep Learning Software
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 Ligands Models, Molecular Pharmaceutical Preparations Quantum Theory Drug Design Drug Discovery
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...
Peptidyl-Dipeptidase A Angiotensin-Converting Enzyme Inhibitors Hydrogen Bonding Machine Learning Molecular Docking Simulation Peptides Models, Molecular
View on PubMed DOI

Evolutionary insights into the active-site structures of the metallo-β-lactamase superfamily from a classification study with support vector machine.

Journal of biological inorganic chemistry : JBIC : a publication of the Society of Biological Inorganic Chemistry Sep 18, 2020
The metallo-β-lactamase (MβL) superfamily, which is intriguing due to its enzyme promiscuity, is a good model enzyme superfamily for studies of catalytic function evolution. Our previous study traced the evolution of the phosphotriesterase activity o...
Computational Biology Catalytic Domain Models, Molecular Kinetics Support Vector Machine beta-Lactamases Evolution, Molecular
View on PubMed DOI

ODiNPred: comprehensive prediction of protein order and disorder.

Scientific reports Sep 8, 2020
Structural disorder is widespread in eukaryotic proteins and is vital for their function in diverse biological processes. It is therefore highly desirable to be able to predict the degree of order and disorder from amino acid sequence. It is, however...
Intrinsically Disordered Proteins Protein Folding Databases, Protein Models, Molecular Amino Acids Computational Biology Proteins Humans Software Algorithms Neural Networks, Computer
View on PubMed DOI

Computational Method for Quantitative Comparison of Activity Landscapes on the Basis of Image Data.

Molecules (Basel, Switzerland) Aug 29, 2020
Activity landscape (AL) models are used for visualizing and interpreting structure-activity relationships (SARs) in compound datasets. Therefore, ALs are designed to present chemical similarity and compound potency information in context. Different t...
Models, Molecular Machine Learning Drug Discovery Drug Design Structure-Activity Relationship
View on PubMed DOI

Comprehensive Prediction of Molecular Recognition in a Combinatorial Chemical Space Using Machine Learning.

ACS combinatorial science Aug 17, 2020
In combinatorial chemical approaches, optimizing the composition and arrangement of building blocks toward a particular function has been done using a number of methods, including high throughput molecular screening, molecular evolution, and computat...
High-Throughput Screening Assays Peptides Combinatorial Chemistry Techniques Protein Binding Peptide Library Machine Learning Molecular Structure Structure-Activity Relationship Amino Acid Sequence Models, Molecular Ligands
View on PubMed DOI

A deep attention network for predicting amino acid signals in the formation of [Formula: see text]-helices.

Journal of bioinformatics and computational biology Aug 6, 2020
The secondary and tertiary structure of a protein has a primary role in determining its function. Even though many folding prediction algorithms have been developed in the past decades - mainly based on the assumption that folding instructions are en...
Models, Molecular Amino Acids Protein Conformation, alpha-Helical Protein Structure, Secondary Machine Learning Software Databases, Protein
View on PubMed DOI

Predicting protein model correctness in Coot using machine learning.

Acta crystallographica. Section D, Structural biology Jul 27, 2020
Manually identifying and correcting errors in protein models can be a slow process, but improvements in validation tools and automated model-building software can contribute to reducing this burden. This article presents a new correctness score that ...
Protein Conformation Proteins Machine Learning Models, Molecular Software Crystallography, X-Ray
View on PubMed DOI
Popular Topics
Recent Journals