AIMC Topic: Drug Evaluation, Preclinical

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High-throughput brain activity mapping and machine learning as a foundation for systems neuropharmacology.

Nature communications Dec 3, 2018
Technologies for mapping the spatial and temporal patterns of neural activity have advanced our understanding of brain function in both health and disease. An important application of these technologies is the discovery of next-generation neurotherap...
Brain Mapping Molecular Structure Pentylenetetrazole Animals Larva Disease Models, Animal Animals, Genetically Modified Convulsants Neuropharmacology Seizures Drug Evaluation, Preclinical Zebrafish Machine Learning Brain
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Application of Bioactivity Profile-Based Fingerprints for Building Machine Learning Models.

Journal of chemical information and modeling Nov 29, 2018
The volume of high throughput screening data has considerably increased since the beginning of the automated biochemical and cell-based assays era. This information-rich data source provides tremendous repurposing opportunities for data mining. It wa...
Neural Networks, Computer Machine Learning Drug Evaluation, Preclinical High-Throughput Screening Assays
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Predictive classifier models built from natural products with antimalarial bioactivity using machine learning approach.

PloS one Sep 28, 2018
In view of the vast number of natural products with potential antiplasmodial bioactivity and cost of conducting antiplasmodial bioactivity assays, it may be judicious to learn from previous antiplasmodial bioassays and predict bioactivity of these na...
In Vitro Techniques Biological Products Quantitative Structure-Activity Relationship Workflow Models, Chemical Humans Small Molecule Libraries Drug Evaluation, Preclinical Machine Learning Antimalarials Algorithms
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Discovering Highly Potent Molecules from an Initial Set of Inactives Using Iterative Screening.

Journal of chemical information and modeling Sep 10, 2018
The versatility of similarity searching and quantitative structure-activity relationships to model the activity of compound sets within given bioactivity ranges (i.e., interpolation) is well established. However, their relative performance in the com...
Drug Discovery Drug Evaluation, Preclinical Quantitative Structure-Activity Relationship Machine Learning Algorithms
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Using predicate and provenance information from a knowledge graph for drug efficacy screening.

Journal of biomedical semantics Sep 6, 2018
BACKGROUND: Biomedical knowledge graphs have become important tools to computationally analyse the comprehensive body of biomedical knowledge. They represent knowledge as subject-predicate-object triples, in which the predicate indicates the relation...
Biological Ontologies False Negative Reactions Computer Graphics ROC Curve Drug Evaluation, Preclinical
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Integration of virtual screening and susceptibility test to discover active-site subpocket-specific biogenic inhibitors of Helicobacter pylori shikimate dehydrogenase.

International microbiology : the official journal of the Spanish Society for Microbiology Aug 24, 2018
Shikimate dehydrogenase (HpSDH) (EC 1.1.1.25) is a key enzyme in the shikimate pathway of Helicobacter pylori (H. pylori), which catalyzes the NADPH-dependent reversible reduction of 3-dehydroshikimate to shikimate. Targeting HpSDH has been recognize...
Microbial Sensitivity Tests Anti-Bacterial Agents Alcohol Oxidoreductases Computational Biology Drug Evaluation, Preclinical Helicobacter pylori Molecular Docking Simulation Crystallography, X-Ray Enzyme Inhibitors Protein Conformation Catalytic Domain
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RASPELD to Perform High-End Screening in an Academic Environment toward the Development of Cancer Therapeutics.

ChemMedChem Aug 23, 2018
The identification of compounds for dissecting biological functions and the development of novel drug molecules are central tasks that often require screening campaigns. However, the required architecture is cost- and time-intensive. Herein we descri...
NF-E2-Related Factor 2 Small Molecule Libraries Education, Graduate Ligands ErbB Receptors Protein Kinase Inhibitors Kelch-Like ECH-Associated Protein 1 Protein Binding Dose-Response Relationship, Drug Humans Robotics Antineoplastic Agents Mutation Drug Evaluation, Preclinical Biological Assay
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PAIN(S) relievers for medicinal chemists: how computational methods can assist in hit evaluation.

Future medicinal chemistry Jun 29, 2018
Small Molecule Libraries Drug Evaluation, Preclinical High-Throughput Screening Assays Humans Machine Learning Drug Discovery Models, Statistical
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Fingerprint-Based Machine Learning Approach to Identify Potent and Selective 5-HTR Ligands.

Molecules (Basel, Switzerland) May 10, 2018
The identification of subtype-selective GPCR (G-protein coupled receptor) ligands is a challenging task. In this study, we developed a computational protocol to find compounds with 5-HTR versus 5-HTR selectivity. Our approach employs the hierarchical...
Serotonin Receptor, Serotonin, 5-HT2B Drug Evaluation, Preclinical Ligands Binding Sites Humans Machine Learning Models, Molecular
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Agonists of G-Protein-Coupled Odorant Receptors Are Predicted from Chemical Features.

The journal of physical chemistry letters Apr 17, 2018
Predicting the activity of chemicals for a given odorant receptor is a longstanding challenge. Here the activity of 258 chemicals on the human G-protein-coupled odorant receptor (OR)51E1, also known as prostate-specific G-protein-coupled receptor 2 (...
Neoplasm Proteins Models, Molecular Drug Evaluation, Preclinical Fatty Acids Ligands Receptors, Odorant Protein Binding Mice Humans Receptors, G-Protein-Coupled Machine Learning Animals
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