Inhibition of Severe Acute Respiratory Syndrome Coronavirus 2 main protease by tafenoquine in vitro

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing the current pandemic, coronavirus disease 2019 (COVID-19), has taken a huge toll on human lives and the global economy. Therefore, effective treatments against this disease are urgently needed. Here, we established a fluorescence resonance energy transfer (FRET)-based high-throughput screening platform to screen compound libraries to identify drugs targeting the SARS-CoV-2 main protease (Mpro), in particular those which are FDA-approved, to be used immediately to treat patients with COVID-19. Mpro has been shown to be one of the most important drug targets among SARS-related coronaviruses as impairment of Mpro blocks processing of viral polyproteins which halts viral replication in host cells. Our findings indicate that the anti-malarial drug tafenoquine (TFQ) induces significant conformational change in SARS-CoV-2 Mpro and diminishes its protease activity. Specifically, TFQ reduces the -helical content of Mpro, which converts it into an inactive form. Moreover, TFQ greatly inhibits SARS-CoV-2 infection in cell culture system. Hence, the current study provides a mechanistic insight into the mode of action of TFQ against SARS-CoV-2 Mpro. Moreover, the low clinical toxicity of TFQ and its strong antiviral activity against SARS-CoV-2 should warrant further testing in clinical trials.

Accurate Joint-Alignment of Indocyanine Green and Fluorescein Angiograph Sequences for Treatment of Subretinal Lesions.

In ophthalmology, aligning images in indocyanine green and fluorescein angiograph sequences is important for the treatment of subretinal lesions. This paper introduces an algorithm that is tailored to align jointly in a common reference space all the images in an angiogram sequence containing both modalities. To overcome the issues of low image contrast and low signal-to-noise ratio for late-phase images, the structural similarity between two images is enhanced using Gabor wavelet transform. Image pairs are pairwise registered and the transformations are simultaneously and globally adjusted for a mutually consistent joint alignment. The joint registration process is incremental and the success depends on the correctness of matches from the pairwise registration. To safeguard the joint process, our system performs the consistency test to exclude incorrect pairwise results automatically to ensure correct matches as more images are jointly aligned. Our dataset consists of 60 sequences of polypoidal choroidal vasculopathy collected by the EVEREST Study Group. On average, each sequence contains 20 images. Our algorithm successfully pairwise registered 95.04% of all image pairs, and joint registered 98.7% of all images, with an average alignment error of 1.58 pixels.