AIMC Topic: Molecular Structure

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BionoiNet: ligand-binding site classification with off-the-shelf deep neural network.

Bioinformatics (Oxford, England) May 1, 2020
MOTIVATION: Fast and accurate classification of ligand-binding sites in proteins with respect to the class of binding molecules is invaluable not only to the automatic functional annotation of large datasets of protein structures but also to projects...
Molecular Structure Ligands Binding Sites Neural Networks, Computer Proteins
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PTML Modeling for Alzheimer's Disease: Design and Prediction of Virtual Multi-Target Inhibitors of GSK3B, HDAC1, and HDAC6.

Current topics in medicinal chemistry Jan 1, 2020
BACKGROUND: Alzheimer's disease is characterized by a progressive pattern of cognitive and functional impairment, which ultimately leads to death. Computational approaches have played an important role in the context of drug discovery for anti-Alzhei...
Alzheimer Disease Protein Kinase Inhibitors Glycogen Synthase Kinase 3 beta Drug Design Models, Molecular Molecular Structure Histone Deacetylase Inhibitors Histone Deacetylase 1 Histone Deacetylase 6 Humans Neural Networks, Computer Machine Learning
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Artificial Intelligence Based Design of Polymers and Metal Composites: A Perspective.

Current topics in medicinal chemistry Jan 1, 2020
Artificial Intelligence Molecular Structure Metal Nanoparticles Databases, Chemical Polymers Quantitative Structure-Activity Relationship Nanocomposites Nanotubes Surface Properties
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Strategies for Design of Molecular Structures with a Desired Pharmacophore Using Deep Reinforcement Learning.

Chemical & pharmaceutical bulletin Jan 1, 2020
The goal of drug design is to discover molecular structures that have suitable pharmacological properties in vast chemical space. In recent years, the use of deep generative models (DGMs) is getting a lot of attention as an effective method of genera...
Drug Design Deep Learning Protein Binding Molecular Structure Drug Evaluation, Preclinical
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Studies for Bacterystic Evaluation against of 2-Naphthoic Acid Analogues.

Current topics in medicinal chemistry Jan 1, 2020
BACKGROUND: Staphylococcus aureus is a gram-positive spherical bacterium commonly present in nasal fossae and in the skin of healthy people; however, in high quantities, it can lead to complications that compromise health. The pathologies involved in...
Models, Molecular Molecular Structure Drug Evaluation, Preclinical Anti-Bacterial Agents Microbial Sensitivity Tests Staphylococcus aureus Naphthalenes Machine Learning
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In silico Prediction of Inhibitory Constant of Thrombin Inhibitors Using Machine Learning.

Combinatorial chemistry & high throughput screening Jan 1, 2018
BACKGROUND: Thrombin is the central protease of the vertebrate blood coagulation cascade, which is closely related to cardiovascular diseases. The inhibitory constant Ki is the most significant property of thrombin inhibitors.
Quantitative Structure-Activity Relationship Humans Machine Learning Thermodynamics Computer Simulation Thrombin Models, Molecular Drug Discovery Molecular Structure Support Vector Machine Linear Models Anticoagulants
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A Network Integration Method for Deciphering the Types of Metabolic Pathway of Chemicals with Heterogeneous Information.

Combinatorial chemistry & high throughput screening Jan 1, 2018
AIM AND OBJECTIVE: A metabolic pathway is an important type of biological pathway, which is composed of a series of chemical reactions. It provides essential molecules and energies for living organisms. To date, several metabolic pathways have been u...
Structure-Activity Relationship Metabolic Networks and Pathways Models, Molecular Molecular Structure Organic Chemicals Computational Biology Support Vector Machine
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Predicting Inhibitors for Multidrug Resistance Associated Protein-2 Transporter by Machine Learning Approach.

Combinatorial chemistry & high throughput screening Jan 1, 2018
BACKGROUND: The efflux transporter multidrug resistance associated protein-2 belongs to ATP-binding cassette superfamily which plays an important role in multidrug resistance and drugdrug interactions. Efflux transporters are considered to be importa...
Machine Learning Algorithms Multidrug Resistance-Associated Protein 2 Quantitative Structure-Activity Relationship Drug Discovery Databases, Pharmaceutical Multidrug Resistance-Associated Proteins Support Vector Machine Molecular Structure
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Machine Learning-Based Modeling of Drug Toxicity.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2018
Toxicity is an important reason for the failure of drug research and development (R&D). The traditional experimental testings for chemical toxicity profile are costly and time-consuming. Therefore, it is attractive to develop the effective and accura...
Quantitative Structure-Activity Relationship Sequence Homology, Amino Acid Ether-A-Go-Go Potassium Channels Humans Models, Biological Machine Learning Drug-Related Side Effects and Adverse Reactions Molecular Structure Software Ligands Internet Drug Design Pharmaceutical Preparations Carcinogenesis
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Editor's Highlight: Identification of Any Structure-Specific Hepatotoxic Potential of Different Pyrrolizidine Alkaloids Using Random Forests and Artificial Neural Networks.

Toxicological sciences : an official journal of the Society of Toxicology Dec 1, 2017
Pyrrolizidine alkaloids (PAs) are characteristic metabolites of some plant families and form a powerful defense mechanism against herbivores. More than 600 different PAs are known. PAs are ester alkaloids composed of a necine base and a necic acid, w...
Risk Assessment Cyclic N-Oxides Liver Algorithms Humans Quantitative Structure-Activity Relationship Heterocyclic Compounds, 2-Ring Molecular Structure Databases, Factual Dicarboxylic Acids Neural Networks, Computer Pyrrolizidine Alkaloids Reproducibility of Results Chemical and Drug Induced Liver Injury Machine Learning
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