ABSTRACT
The COVID-19 pandemic has had enormous health, economic, and social consequences. Vaccines have been successful in reducing rates of infection and hospitalization, but there is still a need for an acute treatment for the disease. We investigate whether compounds that bind the human ACE2 protein can interrupt SARS-CoV-2 replication without damaging ACE2s natural enzymatic function. Initial compounds were screened for binding to ACE2 but little interruption of ACE2 enzymatic activity. This set of compounds was extended by application of quantitative structure-activity analysis, which resulted in 512 virtual hits for further confirmatory screening. A subsequent SARS-CoV-2 replication assay revealed that five of these compounds inhibit SARS-CoV-2 replication in human cells. Further effort is required to completely determine the antiviral mechanism of these compounds, but they serve as a strong starting point for both development of acute treatments for COVID-19 and research into the mechanism of infection. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=98 SRC="FIGDIR/small/484484v1_ufig1.gif" ALT="Figure 1"> View larger version (47K): org.highwire.dtl.DTLVardef@173d7c9org.highwire.dtl.DTLVardef@5c0021org.highwire.dtl.DTLVardef@c9caaorg.highwire.dtl.DTLVardef@18d23_HPS_FORMAT_FIGEXP M_FIG TOC Graphic: Overall study design. C_FIG
ABSTRACT
The National Center for Advancing Translational Sciences (NCATS) has been actively generating SARS-CoV-2 high-throughput screening data and disseminates it through the OpenData Portal (https://opendata.ncats.nih.gov/covid19/). Here, we provide a hybrid approach that utilizes NCATS screening data from the SARS-CoV-2 cytophatic effect reduction assay to build predictive models, using both machine learning and pharmacophore-based modeling. Optimized models were used to perform two iterative rounds of virtual screening to predict small molecules active against SARS-CoV-2. Experimental testing with live virus provided 100 (~16% of predicted hits) active compounds (Efficacy > 30%, IC50 [≤] 15 M). Systematic clustering analysis of active compounds revealed three promising chemotypes which have not been previously identified as inhibitors of SARS-CoV-2 infection. Further analysis identified allosteric binders to host receptor angiotensin-converting enzyme 2, which were able to inhibit the entry of pseudoparticles bearing spike protein of wild type SARS-CoV-2 as well as South African B.1.351 and UK B.1.1.7 variants.
ABSTRACT
The imaging of the distribution of beta-amyloid (Abeta) plaques in the brain is becoming an important diagnostic modality in Alzheimer's disease (AD). Here, we synthesized novel benzothiophene derivatives and labeled them with (18)F for the potential diagnostic imaging of AD patients using positron emission tomography. The K(i) values of benzothiophene derivatives were evaluated by competitive binding assay using 2-(3'-[(125)I]iodo-4'-N-methylaminophenyl)benzothiazole as a radioligand and Abeta(1-40) or Abeta(1-42) aggregates as receptors. All synthesized benzothiophene derivatives showed high binding affinities (K(i)=0.28-6.50 nM) to both Abeta(1-40) and Abeta(1-42) aggregates. Binding affinities were increased by O-alkylation or N-alkylation of 2-(4'-hydroxyphenyl)benzothiophene or 2-(4'-aminophenyl)benzothiophene. Biodistribution studies of 2-(4'-O-(2''-[(18)F]fluoroethyl)hydroxyphenyl)benzothiophene ([(18)F]) and 2-(4'-O-(3''-[(18)F]fluoropropyl)hydroxyphenyl)benzothiophene ([(18)F]) in normal mice were performed after intravenous injection through the tail vein. In biodistribution data, [(18)F] and [(18)F] showed high initial brain uptakes at 2 min (5.2+/-0.4% and 3.3+/-0.2% ID/g, respectively), and brain activities washed out to 2.0+/-0.2% and 0.5+/-0.1% ID/g at 4 h, respectively. In conclusion, benzothiophene derivatives showed excellent binding affinities for Abeta aggregates and high initial brain uptakes in normal mice.
