Computation of Antigenicity Predicts SARS-CoV-2 Vaccine Breakthrough Variants (preprint)

It has been reported that multiple SARS-CoV-2 variants of concerns (VOCs) including B.1.1.7 (Alpha), B.1.351 (Beta), P.1 (Gamma), and B.1.617.2 (Delta) can reduce neutralisation by antibodies, resulting in vaccine breakthrough infections. Virus-antiserum neutralisation assays are typically performed to monitor potential vaccine breakthrough strains. However, such experimental-based methods are slow and cannot instantly validate whether newly emerging variants can break through current vaccines or therapeutic antibodies. To address this, we sought to establish a computational model to predict the antigenicity of SARS-CoV-2 variants by sequence alone and in real time. In this study, we firstly identified the relationship between the antigenic difference transformed from the amino acid sequence and the antigenic distance from the neutralisation titres. Based on this correlation, we obtained a computational model for the receptor binding domain (RBD) of the spike protein to predict the fold decrease in virus-antiserum neutralisation titres with high accuracy (~0.79). Our predicted results were comparable with experimental neutralisation titres of variants, including B.1.1.7 (Alpha), B.1.351 (Beta), B.1.617.2 (Delta), B.1.429 (Epsilon), P.1 (Gamma), B.1.526 (Iota), B.1.617.1 (Kappa), and C.37 (Lambda), as well as SARS-CoV. Here, we firstly predicted the fold of decrease of B.1.1.529 (Omicron) as 17.4-fold less susceptible to neutralisation. We visualised all 1521 SARS-CoV-2 lineages to indicate variants including B.1.621 (Mu), B.1.630, B.1.633, B.1.649, and C.1.2, which can induce vaccine breakthrough infections in addition to reported VOCs B.1.351 (Beta), P.1 (Gamma), B.1.617.2 (Delta), and B.1.1.529 (Omicron). Our study offers a quick approach to predict the antigenicity of SARS-CoV-2 variants as soon as they emerge. Furthermore, this approach can facilitate future vaccine updates to cover all major variants. An online version can be accessed at http://jdlab.online .

Clofazimine is a broad-spectrum coronavirus inhibitor that antagonizes SARS-CoV-2 replication in primary human cell culture and hamsters (preprint)

COVID-19 pandemic is the third zoonotic coronavirus (CoV) outbreak of the century after severe acute respiratory syndrome (SARS) in 2003 and Middle East respiratory syndrome (MERS) since 2012. Treatment options for CoVs are largely lacking. Here, we show that clofazimine, an anti-leprosy drug with a favorable safety and pharmacokinetics profile, possesses pan-coronaviral inhibitory activity, and can antagonize SARS-CoV-2 replication in multiple in vitro systems, including the human embryonic stem cell-derived cardiomyocytes and ex vivo lung cultures. The FDA-approved molecule was found to inhibit multiple steps of viral replication, suggesting multiple underlying antiviral mechanisms. In a hamster model of SARS-CoV-2 pathogenesis, prophylactic or therapeutic administration of clofazimine significantly reduced viral load in the lung and fecal viral shedding, and also prevented cytokine storm associated with viral infection. Additionally, clofazimine exhibited synergy when administered with remdesivir. Since clofazimine is orally bioavailable and has a comparatively low manufacturing cost, it is an attractive clinical candidate for outpatient treatment and remdesivir-based combinatorial therapy for hospitalized COVID-19 patients, particularly in developing countries. Taken together, our data provide evidence that clofazimine may have a role in the control of the current pandemic SARS-CoV-2, endemic MERS-CoV in the Middle East, and, possibly most importantly, emerging CoVs of the future.

Development of high affinity monobodies recognizing SARS-CoV-2 antigen (preprint)

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been a threat to global public health. Prompt patient identification and quarantine is the most effective way to control its rapid transmission, which can be facilitated by early detection of viral antigens. Here we present a platform to develop and optimize the fibronectin-based affinity-enhanced antibody mimetics (monobodies) for recognizing viral antigens. Specifically, we developed monobodies targeting SARS-CoV-2 nucleocapsid (N) protein. We showed that two monobodies, NN2 and NC2, bind to N protein’s N- and C-terminal domains respectively with a Kd in nM range.The specificity of the recognition was confirmed with co-immunoprecipitation and immunofluorescence assays. Furthermore, we demonstrated that one round of in vitro maturation using mRNA display can improve the binding affinity of monobodies. Machine learning algorithms were integrated with deep sequencing data for selecting candidates that improve the detection sensitivity of N. Using this pair of monobodies, we have developed an enzyme-linked immunosorbent assay (ELISA) for viral detection. We were able to detect recombinant N at 4 pg/ml and detect N in viral culture supernatant, with no cross-reactivity with other CoV. Integrating high-dense mutagenesis, mRNA display, deep sequencing and machine learning, this platform can be applied through iterations to identify and optimize monobodies against emerging viral antigens, potentiating point-of-care detection of communicable diseases in a cost-and time-sensitive manner.Authors Yushen Du, Tian-hao Zhang, Xiangzhi Meng, Yuan Shi, and Menglong Hu contributed equally to this work.

A Large-scale Drug Repositioning Survey for SARS-CoV-2 Antivirals (preprint)

The emergence of novel SARS coronavirus 2 (SARS-CoV-2) in 2019 has triggered an ongoing global pandemic of severe pneumonia-like disease designated as coronavirus disease 2019 (COVID-19). To date, more than 2.1 million confirmed cases and 139,500 deaths have been reported worldwide, and there are currently no medical countermeasures available to prevent or treat the disease. As the development of a vaccine could require at least 12-18 months, and the typical timeline from hit finding to drug registration of an antiviral is >10 years, repositioning of known drugs can significantly accelerate the development and deployment of therapies for COVID-19. To identify therapeutics that can be repurposed as SARS-CoV-2 antivirals, we profiled a library of known drugs encompassing approximately 12,000 clinical-stage or FDA-approved small molecules. Here, we report the identification of 30 known drugs that inhibit viral replication. Of these, six were characterized for cellular dose-activity relationships, and showed effective concentrations likely to be commensurate with therapeutic doses in patients. These include the PIKfyve kinase inhibitor Apilimod, cysteine protease inhibitors MDL-28170, Z LVG CHN2, VBY-825, and ONO 5334, and the CCR1 antagonist MLN-3897. Since many of these molecules have advanced into the clinic, the known pharmacological and human safety profiles of these compounds will accelerate their preclinical and clinical evaluation for COVID-19 treatment.