Identifying and quantifying heterogeneity in high content analysis: application of heterogeneity indices to drug discovery.

One of the greatest challenges in biomedical research, drug discovery and diagnostics is understanding how seemingly identical cells can respond differently to perturbagens including drugs for disease treatment. Although heterogeneity has become an accepted characteristic of a population of cells, in drug discovery it is not routinely evaluated or reported. The standard practice for cell-based, high content assays has been to assume a normal distribution and to report a well-to-well average value with a standard deviation. To address this important issue we sought to define a method that could be readily implemented to identify, quantify and characterize heterogeneity in cellular and small organism assays to guide decisions during drug discovery and experimental cell/tissue profiling. Our study revealed that heterogeneity can be effectively identified and quantified with three indices that indicate diversity, non-normality and percent outliers. The indices were evaluated using the induction and inhibition of STAT3 activation in five cell lines where the systems response including sample preparation and instrument performance were well characterized and controlled. These heterogeneity indices provide a standardized method that can easily be integrated into small and large scale screening or profiling projects to guide interpretation of the biology, as well as the development of therapeutics and diagnostics. Understanding the heterogeneity in the response to perturbagens will become a critical factor in designing strategies for the development of therapeutics including targeted polypharmacology

Optimization of pyrazole-containing 1,2,4-triazolo-[3,4-b]thiadiazines, a new class of STAT3 pathway inhibitors

Structure-activity relationship studies of a 1,2,4-triazolo-[3,4-b]thiadiazine scaffold, identified in an HTS campaign for selective STAT3 pathway inhibitors, determined that a pyrazole group and specific aryl substitution on the thiadiazine were necessary for activity. Improvements in potency and metabolic stability were accomplished by the introduction of an α-methyl group on the thiadiazine. Optimized compounds exhibited anti-proliferative activity, reduction of phosphorylated STAT3 levels and effects on STAT3 target genes. These compounds represent a starting point for further drug discovery efforts targeting the STAT3 pathway

A systems‐level study reveals host‐targeted repurposable drugs against SARS‐CoV‐2 infection

Abstract Understanding the mechanism of SARS‐CoV‐2 infection and identifying potential therapeutics are global imperatives. Using a quantitative systems pharmacology approach, we identified a set of repurposable and investigational drugs as potential therapeutics against COVID‐19. These were deduced from the gene expression signature of SARS‐CoV‐2‐infected A549 cells screened against Connectivity Map and prioritized by network proximity analysis with respect to disease modules in the viral–host interactome. We also identified immuno‐modulating compounds aiming at suppressing hyperinflammatory responses in severe COVID‐19 patients, based on the transcriptome of ACE2‐overexpressing A549 cells. Experiments with Vero‐E6 cells infected by SARS‐CoV‐2, as well as independent syncytia formation assays for probing ACE2/SARS‐CoV‐2 spike protein‐mediated cell fusion using HEK293T and Calu‐3 cells, showed that several predicted compounds had inhibitory activities. Among them, salmeterol, rottlerin, and mTOR inhibitors exhibited antiviral activities in Vero‐E6 cells; imipramine, linsitinib, hexylresorcinol, ezetimibe, and brompheniramine impaired viral entry. These novel findings provide new paths for broadening the repertoire of compounds pursued as therapeutics against COVID‐19