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The precise determination of viral titers in virological studies is a critical step to assess the infectious viral concentration of a sample. Although conventional titration methods, such as endpoint dilution or plaque forming units are the gold standards, their widespread use for screening experiments remains limited due to the time-consuming aspect and resource-intensive requirements. This study introduces a rapid and user-friendly high-throughput screening assay for evaluating viral titers. The colorimetric method used relies upon assessing virus-induced cytopathic effects by measuring the reduction of a tetrazolium reagent to formazan through cellular dehydrogenation within mitochondria. The resulting formazan quantity is correlated with the viral titer and can be easily quantified by a colorimetric measurement. In this perspective, this manuscript describes two case studies for the titration of the porcine respiratory coronavirus virus and bovine alpha herpesvirus 1, highlighting, respectively, a linear regime between 100 and 2000 TCID/ml and 500- PFU/ml for rapid titration within these ranges. The proposed technique's advantages and drawbacks are discussed, along with potential applications such as drug screening and the assessment of viral survival on inert surfaces.
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http://dx.doi.org/10.1093/biomethods/bpaf049 | DOI Listing |
J Anim Ecol
September 2025
Sorbonne Université, UPEC, Paris 7, CNRS, INRA, IRD, Institut d'Ecologie et des Sciences de l'Environnement de Paris, Paris, France.
Research Highlight: Bralet, T., Aaziz, R., Tornos, J.
View Article and Find Full Text PDFActa Pharmacol Sin
September 2025
Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Soochow University, Suzhou 215006, China.
Non-small cell lung cancer (NSCLC) is an aggressive malignancy with a poor prognosis. Abnormal expression of focal adhesion kinase (FAK) is closely linked to NSCLC progression, highlighting the need for effective FAK inhibitors in NSCLC treatment. In this study we conducted high-throughput virtual screening combined with cellular assays to identify potential FAK inhibitors for NSCLC treatment.
View Article and Find Full Text PDFBioorg Med Chem Lett
September 2025
Galapagos SASU, 102 avenue Gaston Roussel, 93230 Romainville, France. Electronic address:
The salt-inducible kinase (SIK) family encompasses three isoforms, SIK1, SIK2, and SIK3, which are members of the AMP-activated protein kinase (AMPK) family of serine/threonine protein kinases. SIK inhibition has emerged as a potential therapeutic approach across multiple indications, as SIKs regulate a diverse set of physiological processes such as metabolism, bone remodeling, immune response, malignancies, skin pigmentation, and circadian rhythm. Within isoform-specific SIK inhibitors there is a need to understand the distinct role of each protein, and here we describe the first SIK1 selective inhibitors.
View Article and Find Full Text PDFCell Chem Biol
September 2025
Department of Biological Sciences, College of Natural Science, Seoul National University, Seoul 08826, South Korea. Electronic address:
The nucleotide-binding oligomerization domain (NOD)-like receptor protein 3 (NLRP3) inflammasome detects a broad spectrum of pathogen- and damage-associated molecular patterns (PAMPs and DAMPs), initiating inflammatory responses through caspase-1 activation and interleukin (IL)-1β/IL-18 release. Dysregulated NLRP3 activation is implicated in a range of diseases, including infectious diseases, autoinflammatory disorders, metabolic disorders, and cancer, making it an attractive therapeutic target. Here, we identify ZAP-180013 as a potent and selective small-molecule inhibitor of NLRP3 through high-throughput chemical screening.
View Article and Find Full Text PDFJ Chem Inf Model
September 2025
Department of Chemistry, Delaware State University, Dover, Delaware 19901, United States.
The calculation of the highest occupied molecular orbital-lowest unoccupied molecular orbital (HOMO-LUMO) gap for chemical molecules is computationally intensive using quantum mechanics (QM) methods, while experimental determination is often costly and time-consuming. Machine Learning (ML) offers a cost-effective and rapid alternative, enabling efficient predictions of HOMO-LUMO gap values across large data sets without the need for extensive QM computations or experiments. ML models facilitate the screening of diverse molecules, providing valuable insights into complex chemical spaces and integrating seamlessly into high-throughput workflows to prioritize candidates for experimental validation.
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