In high-throughput screening (HTS) for drug candidates from a library containing tens of thousands to millions of chemical compounds, one problem is assessing the sensitivity of an assay for detecting compounds with a particular potency. For example, when looking for inhibitors of an enzyme, what is the potency of an inhibitor that will be readily detected by an enzyme inhibition assay? Similarly, when assessing compounds that inhibit binding between receptors and ligands or similar molecule-to-molecule interactions, what potency of an inhibitor will be readily detected? In this article, the well-established concepts of Michaelis-Menten kinetics and Langmuir binding isotherms are combined with fundamental statistical principles to yield a measure of assay sensitivity. The approach is general and can be modified to accommodate situations where the reaction kinetics is known to be more complicated than situations described by the Michaelis-Menten and Langmuir equations. The calculations presented take into account the concentration of inhibitor used, the variability of the assay, the relationship between the K(m) or K(d) of the reaction and the substrate or ligand concentration used, the threshold or cutoff value used for determining "hits," and the number of replicates used in screening.
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http://dx.doi.org/10.1016/j.ab.2005.01.034 | DOI Listing |
Commun Phys
January 2025
Department of Physics and Astronomy, the University of Manchester, Manchester, UK.
Two-dimensional materials with flat electronic bands are promising for realising exotic quantum phenomena such as unconventional superconductivity and nontrivial topology. However, exploring their vast chemical space is a significant challenge. Here we introduce elf, an unsupervised convolutional autoencoder that encodes electronic band structure images into fingerprint vectors, enabling the autonomous clustering of materials by electronic properties beyond traditional chemical paradigms.
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January 2025
Department of Surgery, Stanford School of Medicine, Stanford University Medical Center, Stanford, CA, United States.
Molecular characterization of tumors is essential to identify predictive biomarkers that inform treatment decisions and improve precision immunotherapy development and administration. However, challenges such as the heterogeneity of tumors and patient responses, limited efficacy of current biomarkers, and the predominant reliance on single-omics data, have hindered advances in accurately predicting treatment outcomes. Standard therapy generally applies a "one size fits all" approach, which not only provides ineffective or limited responses, but also an increased risk of off-target toxicities and acceleration of resistance mechanisms or adverse effects.
View Article and Find Full Text PDFFront Cell Dev Biol
January 2025
Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy.
Liver cancer is a leading cause of cancer-related deaths worldwide, highlighting the need for innovative approaches to understand its complex biology and develop effective treatments. While traditional animal models have played a vital role in liver cancer research, ethical concerns and the demand for more human-relevant systems have driven the development of advanced models. Spheroids and organoids have emerged as powerful tools due to their ability to replicate tumor microenvironment and facilitate preclinical drug development.
View Article and Find Full Text PDFComput Struct Biotechnol J
December 2024
National Vaccine Innovation Platform, Scholl of Pharmacy, Nanjing Medical University, Nanjing 211166, China.
Unlabelled: The prevention and treatment of metabolic disorders, such as non-alcoholic fatty liver disease (NAFLD), have emerged as critical global health challenges. Current lipid-lowering pharmacotherapies are associated with side effects, including hepatotoxicity, rhabdomyolysis, and decreased erythrocyte counts, underscoring the urgent need for safer therapeutic alternatives. Hepatocyte nuclear factor 4α (HNF4α) has been identified as a pivotal regulator of lipid metabolism, making it an attractive target for drug development.
View Article and Find Full Text PDFFood Res Int
February 2025
Analysis and Testing Center, Jiangnan University, Wuxi 214122, China. Electronic address:
The aim of this study was to isolate strains with excellent fermentation performance from pickles, thus enhancing the quality of rapid, low-salt fermented mustard leaves (Brassica juncea var. multiceps) through process optimization and inoculation fermentation. A high-throughput screening method for acid-producing strains was developed, significantly improving screening efficiency.
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