AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Small Molecule Libraries

Showing 141 to 150 of 159 articles

Clear Filters

BindingDB in 2024: a FAIR knowledgebase of protein-small molecule binding data.

Nucleic acids research
BindingDB (bindingdb.org) is a public, web-accessible database of experimentally measured binding affinities between small molecules and proteins, which supports diverse applications including medicinal chemistry, biochemical pathway annotation, trai...

DeepRSMA: a cross-fusion-based deep learning method for RNA-small molecule binding affinity prediction.

Bioinformatics (Oxford, England)
MOTIVATION: RNA is implicated in numerous aberrant cellular functions and disease progressions, highlighting the crucial importance of RNA-targeted drugs. To accelerate the discovery of such drugs, it is essential to develop an effective computationa...

DGCL: dual-graph neural networks contrastive learning for molecular property prediction.

Briefings in bioinformatics
In this paper, we propose DGCL, a dual-graph neural networks (GNNs)-based contrastive learning (CL) integrated with mixed molecular fingerprints (MFPs) for molecular property prediction. The DGCL-MFP method contains two stages. In the first pretraini...

Deep-PK: deep learning for small molecule pharmacokinetic and toxicity prediction.

Nucleic acids research
Evaluating pharmacokinetic properties of small molecules is considered a key feature in most drug development and high-throughput screening processes. Generally, pharmacokinetics, which represent the fate of drugs in the human body, are described fro...

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

Bioinformatics (Oxford, England)
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...

An ensemble machine learning model generates a focused screening library for the identification of CDK8 inhibitors.

Protein science : a publication of the Protein Society
The identification of an effective inhibitor is an important starting step in drug development. Unfortunately, many issues such as the characterization of protein binding sites, the screening library, materials for assays, etc., make drug screening a...

Machine learning framework to predict pharmacokinetic profile of small molecule drugs based on chemical structure.

Clinical and translational science
Accurate prediction of a new compound's pharmacokinetic (PK) profile is pivotal for the success of drug discovery programs. An initial assessment of PK in preclinical species and humans is typically performed through allometric scaling and mathematic...

Development of Drug Discovery Platforms Using Artificial Intelligence and Cheminformatics.

Chemical & pharmaceutical bulletin
Recently, remarkable progress has been achieved in artificial intelligence (AI), including machine learning. Various AI models have been proposed for drug discovery, including the design of small molecules, activity prediction, and three-dimensional ...

DD-GUI: a graphical user interface for deep learning-accelerated virtual screening of large chemical libraries (Deep Docking).

Bioinformatics (Oxford, England)
SUMMARY: Deep learning (DL) can significantly accelerate virtual screening of ultra-large chemical libraries, enabling the evaluation of billions of compounds at a fraction of the computational cost and time required by conventional docking. Here, we...

Artificial Intelligence in Drug Safety and Metabolism.

Methods in molecular biology (Clifton, N.J.)
The use of artificial intelligence methods in drug safety began in the early 2000s with applications such as predicting bacterial mutagenicity and hERG inhibition. The field has been endlessly expanding ever since and the models have become more comp...