AIMC Topic: Drug Discovery

Clear Filters Showing 1301 to 1310 of 1568 articles

AI-recognized mitochondrial phenotype enables identification of drug targets.

Nature computational science Aug 1, 2024
Humans Drug Discovery Mitochondria Artificial Intelligence Phenotype
View on PubMed DOI

GR-pKa: a message-passing neural network with retention mechanism for pKa prediction.

Briefings in bioinformatics Jul 25, 2024
During the drug discovery and design process, the acid-base dissociation constant (pKa) of a molecule is critically emphasized due to its crucial role in influencing the ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties...
Neural Networks, Computer Drug Discovery Thermodynamics
View on PubMed DOI

MetaPredictor: in silico prediction of drug metabolites based on deep language models with prompt engineering.

Briefings in bioinformatics Jul 25, 2024
Metabolic processes can transform a drug into metabolites with different properties that may affect its efficacy and safety. Therefore, investigation of the metabolic fate of a drug candidate is of great significance for drug discovery. Computational...
Software Algorithms Humans Computational Biology Pharmaceutical Preparations Drug Discovery Deep Learning Computer Simulation
View on PubMed DOI

ADMET-AI: a machine learning ADMET platform for evaluation of large-scale chemical libraries.

Bioinformatics (Oxford, England) Jul 1, 2024
MOTIVATION: The emergence of large chemical repositories and combinatorial chemical spaces, coupled with high-throughput docking and generative AI, have greatly expanded the chemical diversity of small molecules for drug discovery. Selecting compound...
Small Molecule Libraries Drug Discovery Machine Learning Software
View on PubMed DOI

OLB-AC: toward optimizing ligand bioactivities through deep graph learning and activity cliffs.

Bioinformatics (Oxford, England) Jun 3, 2024
MOTIVATION: Deep graph learning (DGL) has been widely employed in the realm of ligand-based virtual screening. Within this field, a key hurdle is the existence of activity cliffs (ACs), where minor chemical alterations can lead to significant changes...
Ligands Neural Networks, Computer Drug Discovery Deep Learning
View on PubMed DOI

GEMF: a novel geometry-enhanced mid-fusion network for PLA prediction.

Briefings in bioinformatics May 23, 2024
Accurate prediction of protein-ligand binding affinity (PLA) is important for drug discovery. Recent advances in applying graph neural networks have shown great potential for PLA prediction. However, existing methods usually neglect the geometric inf...
Protein Binding Computational Biology Proteins Ligands Algorithms Neural Networks, Computer Drug Discovery
View on PubMed DOI

Morphological profiling for drug discovery in the era of deep learning.

Briefings in bioinformatics May 23, 2024
Morphological profiling is a valuable tool in phenotypic drug discovery. The advent of high-throughput automated imaging has enabled the capturing of a wide range of morphological features of cells or organisms in response to perturbations at the sin...
Machine Learning Drug Discovery Humans Deep Learning Image Processing, Computer-Assisted
View on PubMed DOI

Peptide-based drug discovery through artificial intelligence: towards an autonomous design of therapeutic peptides.

Briefings in bioinformatics May 23, 2024
With their diverse biological activities, peptides are promising candidates for therapeutic applications, showing antimicrobial, antitumour and hormonal signalling capabilities. Despite their advantages, therapeutic peptides face challenges such as s...
Drug Discovery Humans Computational Biology Artificial Intelligence Peptides Drug Design Machine Learning
View on PubMed DOI

Prediction of drug-protein interaction based on dual channel neural networks with attention mechanism.

Briefings in functional genomics May 15, 2024
The precise identification of drug-protein inter action (DPI) can significantly speed up the drug discovery process. Bioassay methods are time-consuming and expensive to screen for each pair of drug proteins. Machine-learning-based methods cannot acc...
Pharmaceutical Preparations Computational Biology Proteins Deep Learning Neural Networks, Computer Humans Machine Learning Algorithms Drug Discovery
View on PubMed DOI

Molecular property prediction based on graph structure learning.

Bioinformatics (Oxford, England) May 2, 2024
MOTIVATION: Molecular property prediction (MPP) is a fundamental but challenging task in the computer-aided drug discovery process. More and more recent works employ different graph-based models for MPP, which have achieved considerable progress in i...
Neural Networks, Computer Machine Learning Drug Discovery Algorithms
View on PubMed DOI
Popular Topics
Recent Journals