AIMC Topic: High-Throughput Screening Assays

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High-throughput screening system for immunogenic cell death inducers using artificial intelligence-based real-time image analysis.

Computers in biology and medicine
Immunogenic cell death (ICD) can enhance the immunogenicity of cold tumors, convert them into immune-responsive hot tumors, and improve the efficacy of cancer immunotherapy. Because ICD inducers cause cell swelling, membrane rupture, and the release ...

High-throughput behavioral screening in Caenorhabditis elegans using machine learning for drug repurposing.

Scientific reports
Caenorhabditis elegans is a widely used animal model for researching new disease treatments. In recent years, automated methods have been developed to extract mobility phenotypes and analyse, using statistical methods, whether there are differences b...

Machine Learning-Assisted Iterative Screening for Efficient Detection of Drug Discovery Starting Points.

Journal of medicinal chemistry
High-throughput screening (HTS) remains central to small molecule lead discovery, but increasing assay complexity challenges the screening of large compound libraries. While retrospective studies have assessed active-learning-guided screening, extens...

Measurement and prediction of small molecule retention by Gram-negative bacteria based on a large-scale LC/MS screen.

Scientific reports
The challenge of assessing intracellular accumulation represents a major hurdle to the discovery of new antibiotics with Gram-negative activity. To address this, a high-throughput assay was developed to measure compound uptake and retention in Escher...

Modification and applications of glucose oxidase: optimization strategies and high-throughput screening technologies.

World journal of microbiology & biotechnology
Glucose oxidase (GOD), an oxidoreductase (EC 1.1.3.4), catalyzes the oxidation of β-D-glucose to gluconic acid using molecular oxygen as the electron acceptor, with concomitant generation of hydrogen peroxide. Owing to its versatile catalytic propert...

Combining the NanaPPI Toolbox and AI-Driven Virtual Inhibitor Screening for the p53-MDM2 Interaction.

Analytical chemistry
High-throughput screening for inhibitors of protein-protein interactions (PPIs) provides vital information for therapeutic intervention in diseases driven by aberrant PPIs. Traditionally, the discovery of PPI inhibitors involves sequential steps: in ...

Innovations in cancer treatment: evaluating drug resistance with lab-on-a-chip technologies.

International journal of pharmaceutics
Lab-on-a-chip (LoC) technologies have emerged as transformative tools in cancer research, particularly in evaluating drug resistance, which remains a significant barrier to effective treatment. These miniaturized platforms allow for the integration o...

Ultrahigh-Throughput Virtual Screening Strategies against PPI Targets: A Case Study of STAT Inhibitors.

Journal of chemical information and modeling
In recent years, virtual screening of ultralarge (10) libraries of synthetically accessible compounds (uHTVS) became a popular approach in hit identification. With AI-assisted virtual screening workflows, such as Deep Docking, these protocols might b...

A Machine Learning Approach to Molecular Initiating Event Prediction Using High-Throughput Transcriptomic Chemical Screening Data.

Journal of chemical information and modeling
Improved scalability of high-throughput RNA-sequencing technologies has contributed to their proposed use in regulatory contexts for chemical hazard identification. However, the high dimensionality and size of these transcriptomic data sets present a...

High-Throughput Analysis of Protein Adsorption to a Large Library of Polymers Using Liquid Extraction Surface Analysis-Tandem Mass Spectrometry (LESA-MS/MS).

Analytical chemistry
Biomaterials play an important role in medicine from contact lenses to joint replacements. High-throughput screening coupled with machine learning has identified synthetic polymers that prevent bacterial biofilm formation, prevent fungal cell attachm...