AIMC Topic: Drug Discovery

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BRMCF: Binary Relevance and MLSMOTE Based Computational Framework to Predict Drug Functions From Chemical and Biological Properties of Drugs.

IEEE/ACM transactions on computational biology and bioinformatics Jun 5, 2023
In silico machine learning based prediction of drug functions considering the drug properties would substantially enhance the speed and reduce the cost of identifying promising drug leads. The drug function prediction capability of different drug pro...
Neural Networks, Computer Drug Discovery Amino Acid Sequence Algorithms Machine Learning
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Applying deep learning to iterative screening of medium-sized molecules for protein-protein interaction-targeted drug discovery.

Chemical communications (Cambridge, England) May 30, 2023
We combined a library of medium-sized molecules with iterative screening using multiple machine learning algorithms that were ligand-based, which resulted in a large increase of the hit rate against a protein-protein interaction target. This was demo...
NF-E2-Related Factor 2 Protein Binding Kelch-Like ECH-Associated Protein 1 Drug Discovery Deep Learning
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Sulfur-containing marine natural products as leads for drug discovery and development.

Current opinion in chemical biology May 29, 2023
Among the large series of marine natural products (MNPs), sulfur-containing MNPs have emerged as potential therapeutic agents for the treatment of a range of diseases. Herein, we reviewed 95 new sulfur-containing MNPs isolated during the period betwe...
Proteolysis Drug Discovery Artificial Intelligence Biological Products
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Targeting protein-protein interactions with low molecular weight and short peptide modulators: insights on disease pathways and starting points for drug discovery.

Expert opinion on drug discovery May 29, 2023
INTRODUCTION: Protein-protein interactions (PPIs) have been often considered undruggable targets although they are attractive for the discovery of new therapeutics. The spread of artificial intelligence and machine learning complemented with experime...
Drug Discovery Protein Binding Peptides Artificial Intelligence Molecular Weight Proteins Humans
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The application of artificial intelligence to accelerate G protein-coupled receptor drug discovery.

British journal of pharmacology May 26, 2023
The application of artificial intelligence (AI) approaches to drug discovery for G protein-coupled receptors (GPCRs) is a rapidly expanding area. Artificial intelligence can be used at multiple stages during the drug discovery process, from aiding ou...
Ligands Receptors, G-Protein-Coupled Machine Learning Artificial Intelligence Humans Drug Discovery Animals
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Artifical intelligence: a virtual chemist for natural product drug discovery.

Journal of biomolecular structure & dynamics May 26, 2023
Nature is full of a bundle of medicinal substances and its product perceived as a prerogative structure to collaborate with protein drug targets. The natural product's (NPs) structure heterogeneity and eccentric characteristics inspired scientists to...
Intelligence Drug Discovery Biological Products Artificial Intelligence Drug Design Machine Learning
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Prospective Validation of Machine Learning Algorithms for Absorption, Distribution, Metabolism, and Excretion Prediction: An Industrial Perspective.

Journal of chemical information and modeling May 22, 2023
Absorption, distribution, metabolism, and excretion (ADME), which collectively define the concentration profile of a drug at the site of action, are of critical importance to the success of a drug candidate. Recent advances in machine learning algori...
Solubility Drug Discovery Machine Learning Animals Humans Algorithms Rats Random Forest
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Using a stacked ensemble learning framework to predict modulators of protein-protein interactions.

Computers in biology and medicine May 16, 2023
Identifying small molecule protein-protein interaction modulators (PPIMs) is a highly promising and meaningful research direction for drug discovery, cancer treatment, and other fields. In this study, we developed a stacking ensemble computational fr...
Machine Learning Random Forest Drug Discovery
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Molecular Generation with Reduced Labeling through Constraint Architecture.

Journal of chemical information and modeling May 15, 2023
In the past few years, a number of machine learning (ML)-based molecular generative models have been proposed for generating molecules with desirable properties, but they all require a large amount of label data of pharmacological and physicochemical...
Drug Discovery Models, Molecular Machine Learning Neural Networks, Computer
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From jeopardy champion to drug discovery; semantic similarity artificial intelligence.

Autophagy May 14, 2023
We have employed artificial intelligence to streamline the small molecule drug screening pipeline and identified the cholesterol-reducing compound probucol in the process. Probucol augmented mitophagy and prevented loss of dopaminergic neurons in fli...
Animals Drug Discovery Artificial Intelligence Humans Mitophagy Semantics
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