AIMC Topic: Drug Discovery

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Machine learning models in the prediction of drug metabolism: challenges and future perspectives.

Expert opinion on drug metabolism & toxicology Nov 2, 2021
Humans Machine Learning Drug Discovery
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Using diverse potentials and scoring functions for the development of improved machine-learned models for protein-ligand affinity and docking pose prediction.

Journal of computer-aided molecular design Oct 28, 2021
The advent of computational drug discovery holds the promise of significantly reducing the effort of experimentalists, along with monetary cost. More generally, predicting the binding of small organic molecules to biological macromolecules has far-re...
Molecular Docking Simulation Drug Discovery Ligands Thermodynamics Proteins Machine Learning
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Knowledge-based approaches to drug discovery for rare diseases.

Drug discovery today Oct 27, 2021
The conventional drug discovery pipeline has proven to be unsustainable for rare diseases. Herein, we discuss recent advances in biomedical knowledge mining applied to discovering therapeutics for rare diseases. We summarize current chemogenomics dat...
Rare Diseases Drug Discovery Humans Artificial Intelligence Knowledge Bases Machine Learning
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New Insights Into Drug Repurposing for COVID-19 Using Deep Learning.

IEEE transactions on neural networks and learning systems Oct 27, 2021
The coronavirus disease 2019 (COVID-19) has continued to spread worldwide since late 2019. To expedite the process of providing treatment to those who have contracted the disease and to ensure the accessibility of effective drugs, numerous strategies...
Drug Discovery Deep Learning Antiviral Agents Neural Networks, Computer COVID-19 Drug Repositioning COVID-19 Drug Treatment Humans
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Generative Deep Learning for Targeted Compound Design.

Journal of chemical information and modeling Oct 26, 2021
In the past few years, molecular design has increasingly been using generative models from the emergent field of Deep Learning, proposing novel compounds that are likely to possess desired properties or activities. molecular design finds applicatio...
Neural Networks, Computer Drug Discovery Deep Learning Drug Design Bayes Theorem
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Machine Learning Assisted Approach for Finding Novel High Activity Agonists of Human Ectopic Olfactory Receptors.

International journal of molecular sciences Oct 26, 2021
Olfactory receptors (ORs) constitute the largest superfamily of G protein-coupled receptors (GPCRs). ORs are involved in sensing odorants as well as in other ectopic roles in non-nasal tissues. Matching of an enormous number of the olfactory stimulat...
Molecular Docking Simulation Support Vector Machine Drug Evaluation, Preclinical Female HEK293 Cells Drug Design Bayes Theorem Ligands Male In Vitro Techniques Receptors, Odorant Drug Discovery Humans User-Computer Interface Machine Learning
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Application of Deep Neural Network Models in Drug Discovery Programs.

ChemMedChem Oct 18, 2021
In silico driven optimization of compound properties related to pharmacokinetics, pharmacodynamics, and safety is a key requirement in modern drug discovery. Nowadays, large and harmonized datasets allow to implement deep neural networks (DNNs) as a ...
Factor Xa Factor Xa Inhibitors Cytochrome P-450 CYP3A Structure-Activity Relationship Molecular Structure Cytochrome P-450 CYP3A Inhibitors Humans Deep Learning Dose-Response Relationship, Drug Drug Discovery
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Success stories of AI in drug discovery - where do things stand?

Expert opinion on drug discovery Oct 13, 2021
INTRODUCTION: Artificial intelligence (AI) in drug discovery and development (DDD) has gained more traction in the past few years. Many scientific reviews have already been made available in this area. Thus, in this review, the authors have focused o...
Humans Artificial Intelligence Drug Development Drug Discovery
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Deep learning-driven scaffold hopping in the discovery of Akt kinase inhibitors.

Chemical communications (Cambridge, England) Oct 12, 2021
Scaffold hopping has been widely used in drug discovery and is a topic of high interest. Here a deep conditional transformer neural network, SyntaLinker, was applied for the scaffold hopping of a phase III clinical Akt inhibitor, AZD5363. A number of...
Drug Discovery Deep Learning Molecular Structure Humans Pyrimidines Proto-Oncogene Proteins c-akt Pyrroles Protein Kinase Inhibitors
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AI for drug discovery is advancing rapidly: We need smart biology for it to fulfill its mission.

Drug discovery today Oct 8, 2021
Natural History Needs Assessment Humans Translational Science, Biomedical Drug Development Artificial Intelligence Probability Computer Simulation Drug Discovery Forecasting
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