AIMC Topic: Drug Evaluation, Preclinical

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Broad-Spectrum Profiling of Drug Safety via Learning Complex Network.

Clinical pharmacology and therapeutics Feb 28, 2020
Drug safety is a severe clinical pharmacology and toxicology problem that has caused immense medical and social burdens every year. Regretfully, a reproducible method to assess drug safety systematically and quantitatively is still missing. In this s...
Drug Discovery Drug Evaluation, Preclinical Drug-Related Side Effects and Adverse Reactions Adverse Drug Reaction Reporting Systems Humans Machine Learning Animals
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Discovery of Small-Molecule Activators for Glucose-6-Phosphate Dehydrogenase (G6PD) Using Machine Learning Approaches.

International journal of molecular sciences Feb 23, 2020
Glucose-6-Phosphate Dehydrogenase (G6PD) is a ubiquitous cytoplasmic enzyme converting glucose-6-phosphate into 6-phosphogluconate in the pentose phosphate pathway (PPP). The G6PD deficiency renders the inability to regenerate glutathione due to lack...
Glucosephosphate Dehydrogenase NADP Pentose Phosphate Pathway Glutathione X-Ray Diffraction Protein Interaction Domains and Motifs Drug Discovery Oxidative Stress Oxidation-Reduction Glucosephosphate Dehydrogenase Deficiency Drug Evaluation, Preclinical Catalytic Domain Machine Learning Humans Animals Molecular Docking Simulation
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Validating the validation: reanalyzing a large-scale comparison of deep learning and machine learning models for bioactivity prediction.

Journal of computer-aided molecular design Jan 20, 2020
Machine learning methods may have the potential to significantly accelerate drug discovery. However, the increasing rate of new methodological approaches being published in the literature raises the fundamental question of how models should be benchm...
Humans Machine Learning Algorithms User-Computer Interface ROC Curve Support Vector Machine Area Under Curve Computer Simulation Drug Discovery Deep Learning Benchmarking Drug Evaluation, Preclinical
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Machine Learning Models Based on Molecular Fingerprints and an Extreme Gradient Boosting Method Lead to the Discovery of JAK2 Inhibitors.

Journal of chemical information and modeling Dec 4, 2019
Developing Janus kinase 2 (JAK2) inhibitors has become a significant focus for small-molecule drug discovery programs in recent years because the inhibition of JAK2 may be an effective approach for the treatment of myeloproliferative neoplasm. Here, ...
Drug Evaluation, Preclinical Janus Kinase 2 Protein Kinase Inhibitors Machine Learning Drug Discovery User-Computer Interface
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Development of New Methods Needs Proper Evaluation-Benchmarking Sets for Machine Learning Experiments for Class A GPCRs.

Journal of chemical information and modeling Nov 22, 2019
New computational approaches for virtual screening applications are constantly being developed. However, before a particular tool is used to search for new active compounds, its effectiveness in the type of task must be examined. In this study, we co...
Benchmarking Drug Evaluation, Preclinical Ligands Machine Learning User-Computer Interface Receptors, G-Protein-Coupled
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Machine learning for target discovery in drug development.

Current opinion in chemical biology Nov 14, 2019
The discovery of macromolecular targets for bioactive agents is currently a bottleneck for the informed design of chemical probes and drug leads. Typically, activity profiling against genetically manipulated cell lines or chemical proteomics is pursu...
Pentacyclic Triterpenes Receptors, Cannabinoid Sesquiterpenes, Guaiane Proteomics Drug Evaluation, Preclinical Sesquiterpenes Lipoxygenase Machine Learning Naphthoquinones Molecular Targeted Therapy Computer Simulation Humans Transient Receptor Potential Channels Antineoplastic Agents
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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...
Models, Molecular Molecular Structure Dogs Drug Evaluation, Preclinical Microsomes, Liver Enzyme Inhibitors Deep Learning Mice Rats Humans Animals Protein Conformation Discoidin Domain Receptor 1
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Hidden bias in the DUD-E dataset leads to misleading performance of deep learning in structure-based virtual screening.

PloS one Aug 20, 2019
Recently much effort has been invested in using convolutional neural network (CNN) models trained on 3D structural images of protein-ligand complexes to distinguish binding from non-binding ligands for virtual screening. However, the dearth of reliab...
Databases, Pharmaceutical Pharmaceutical Preparations Drug Evaluation, Preclinical Deep Learning Ligands User-Computer Interface Proteins
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Artificial Intelligence for Drug Toxicity and Safety.

Trends in pharmacological sciences Aug 2, 2019
Interventional pharmacology is one of medicine's most potent weapons against disease. These drugs, however, can result in damaging side effects and must be closely monitored. Pharmacovigilance is the field of science that monitors, detects, and preve...
Product Surveillance, Postmarketing Humans Artificial Intelligence Machine Learning Animals Drug Evaluation, Preclinical Pharmacovigilance Drug-Related Side Effects and Adverse Reactions Quantitative Structure-Activity Relationship Toxicity Tests Adverse Drug Reaction Reporting Systems
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The Missing Pieces of Artificial Intelligence in Medicine.

Trends in pharmacological sciences Jul 2, 2019
Stakeholders across the entire healthcare chain are looking to incorporate artificial intelligence (AI) into their decision-making process. From early-stage drug discovery to clinical decision support systems, we have seen examples of how AI can impr...
Drug Evaluation, Preclinical Clinical Trials as Topic Interdisciplinary Research Humans Artificial Intelligence Delivery of Health Care Precision Medicine Drug Development
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