Biological activity-based modeling identifies antiviral leads against SARS-CoV-2.

Computational approaches for drug discovery, such as quantitative structure-activity relationship, rely on structural similarities of small molecules to infer biological activity but are often limited to identifying new drug candidates in the chemical spaces close to known ligands. Here we report a biological activity-based modeling (BABM) approach, in which compound activity profiles established across multiple assays are used as signatures to predict compound activity in other assays or against a new target. This approach was validated by identifying candidate antivirals for Zika and Ebola viruses based on high-throughput screening data. BABM models were then applied to predict 311 compounds with potential activity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Of the predicted compounds, 32% had antiviral activity in a cell culture live virus assay, the most potent compounds showing a half-maximal inhibitory concentration in the nanomolar range. Most of the confirmed anti-SARS-CoV-2 compounds were found to be viral entry inhibitors and/or autophagy modulators. The confirmed compounds have the potential to be further developed into anti-SARS-CoV-2 therapies.

Cell-Based No-Wash Fluorescence Assays for Compound Screens Using a Fluorescence Cytometry Plate Reader.

High-throughput cell-based fluorescent imaging assays often require removal of background fluorescent signal to obtain robust measurements. Processing high-density microplates to remove background signal is challenging because of equipment requirements and increasing variation after multiple plate wash steps. Here, we present the development of a wash-free cell-based fluorescence assay method for high-throughput screening using a laser scanning fluorescence plate cytometer. The cytometry data consisted of cell count and fluorescent intensity measurements for phenotypic screening. We obtained robust screening results by applying this assay methodology to the lysosomal storage disease Niemann-Pick disease type A. We further demonstrated that this cytometry method can be applied to the detection of cholesterol in Niemann-Pick disease type C. Lastly, we used the Mirrorball method to obtain preliminary results for the detection of Zika and Dengue viral envelope protein. The advantages of this assay format include 1) no plate washing, 2) 4-fold faster plate scan and analysis time, 3) high throughput, and 4) >10-fold smaller direct data files. In contrast, traditional imaging assays require multiple plate washes to remove the background signal, long plate scan and data analysis times, and large data files. Therefore, this versatile and broadly applicable Mirrorball-based method greatly improves the throughput and data quality of image-based screening by increasing sensitivity and efficiency while reducing assay artifacts. SIGNIFICANCE STATEMENT: This work has resulted in the development of broadly applicable cell-based fluorescence imaging assays without the requirement of washing out reagents to reduce background signal, which effectively decreases the need for extensive plate processing by the researcher. We demonstrate this high-throughput method for drug screening against lysosomal storage diseases and a commonly used viral titer assay.

High-Throughput Zika Viral Titer Assay for Rapid Screening of Antiviral Drugs.

Zika virus has recently emerged as a worldwide pathogen and public health burden due to its rapid spread and identification as a causative agent for multiple neurological defects, including congenital microcephaly. While there has been a flurry of recent research to address this emerging pathogen, there are currently no approved drug treatments for ZIKV infection. The gold standard for testing antiviral activity is to quantify infectious virion production. However, current infectious viral production assays, such as the plaque-forming or focus-forming unit assay, are tedious and labor intensive with a low-screening throughput. To facilitate drug development, we developed a Zika viral titration assay using an automated imaging system and an image analysis algorithm for viral colony quantification. This assay retained the principle of the classical virus titer assay, while improving workflow and offering higher screening throughput. In addition, this assay can be broadly adapted to quantification of other viruses.