Efficacy and safety of Paxlovid in severe adult patients with SARS-Cov-2 infection: a multicenter randomized controlled study.

Background: Nirmatrelvir plus ritonavir (Paxlovid) reduced the risk of hospitalization or death by 89% in high-risk, ambulatory adults with COVID-19. We aimed at studying the efficacy and safety of Paxlovid in hospitalized adult patients with SARS-Cov-2 (Omicron BA.2.2 variant) infection and severe comorbidities. Methods: We conducted an open-label, multicenter, randomized controlled trial in which hospitalized adult patients with severe comorbidities were eligible and assigned in a 1:1 ratio to receive either 300 mg of nirmatrelvir plus 100 mg of ritonavir every 12 h for 5 days with standard treatment or only standard treatment. All-cause mortality on day 28, the duration of SARS-CoV-2 RNA clearance, and safety were evaluated. Findings: 264 patients (mean age, 70.35 years; 122 [46.21%] female) who met the criteria were enrolled at 5 sites in Shanghai from April 10 to May 19 in 2022. After randomization, a total of 132 patients were assigned to receive Paxlovid treatment plus standard treatment, and 132 patients were assigned to receive only standard treatment. The overall 28-day mortality was 4.92%, 8 patients died in the standard treatment group and 5 died in the Paxlovid plus standard treatment group. There was no significant difference in mortality from any cause at 28 days between the Paxlovid plus standard treatment group and the standard treatment group (absolute risk difference [ARD], 2.27; 95% CI -2.94 to 7.49, P = 0.39). There was no significant difference in the duration of SARS-CoV-2 RNA clearance among the two groups (mean days, 10 in Paxlovid plus standard treatment group and 10.50 in the standard treatment group; ARD, -0.62; 95% CI -2.29 to 1.05, P = 0.42). The incidence of adverse events that occurred during the treatment period was similar in the two groups (any adverse event, 10.61% with Paxlovid plus standard treatment vs. 7.58% with the standard, P = 0.39; serious adverse events, 4.55% vs. 3.788%, P = 0.76). Interpretation: Paxlovid showed no significant reduction in the risk of all-cause mortality on day 28 and the duration of SARS-CoV-2 RNA clearance in hospitalized adult COVID-19 patients with severe comorbidities. Funding: National Natural Science Foundation of China (grant number: 82172152, 81873944).

Efficacy and safety of Paxlovid in severe adult patients with SARS-Cov-2 infection: a multicenter randomized controlled study

Background Nirmatrelvir plus ritonavir (Paxlovid) reduced the risk of hospitalization or death by 89% in high-risk, ambulatory adults with COVID-19. We aimed at studying the efficacy and safety of Paxlovid in hospitalized adult patients with SARS-Cov-2 (Omicron BA.2.2 variant) infection and severe comorbidities. Methods We conducted an open-label, multicenter, randomized controlled trial in which hospitalized adult patients with severe comorbidities were eligible and assigned in a 1:1 ratio to receive either 300 mg of nirmatrelvir plus 100 mg of ritonavir every 12 h for 5 days with standard treatment or only standard treatment. All-cause mortality on day 28, the duration of SARS-CoV-2 RNA clearance, and safety were evaluated. Findings 264 patients (mean age, 70.35 years;122 [46.21%] female) who met the criteria were enrolled at 5 sites in Shanghai from April 10 to May 19 in 2022. After randomization, a total of 132 patients were assigned to receive Paxlovid treatment plus standard treatment, and 132 patients were assigned to receive only standard treatment. The overall 28-day mortality was 4.92%, 8 patients died in the standard treatment group and 5 died in the Paxlovid plus standard treatment group. There was no significant difference in mortality from any cause at 28 days between the Paxlovid plus standard treatment group and the standard treatment group (absolute risk difference [ARD], 2.27;95% CI −2.94 to 7.49, P = 0.39). There was no significant difference in the duration of SARS-CoV-2 RNA clearance among the two groups (mean days, 10 in Paxlovid plus standard treatment group and 10.50 in the standard treatment group;ARD, −0.62;95% CI −2.29 to 1.05, P = 0.42). The incidence of adverse events that occurred during the treatment period was similar in the two groups (any adverse event, 10.61% with Paxlovid plus standard treatment vs. 7.58% with the standard, P = 0.39;serious adverse events, 4.55% vs. 3.788%, P = 0.76). Interpretation Paxlovid showed no significant reduction in the risk of all-cause mortality on day 28 and the duration of SARS–CoV-2 RNA clearance in hospitalized adult COVID-19 patients with severe comorbidities. Funding 10.13039/501100001809National Natural Science Foundation of China (grant number: 82172152, 81873944).

High-throughput screening of SARS-CoV-2 main and papain-like protease inhibitors.

The global COVID-19 coronavirus pandemic has infected over 109 million people, leading to over 2 million deaths up to date and still lacking of effective drugs for patient treatment. Here, we screened about 1.8 million small molecules against the main protease (Mpro) and papain like protease (PLpro), two major proteases in severe acute respiratory syndrome-coronavirus 2 genome, and identified 1851Mpro inhibitors and 205 PLpro inhibitors with low nmol/l activity of the best hits. Among these inhibitors, eight small molecules showed dual inhibition effects on both Mpro and PLpro, exhibiting potential as better candidates for COVID-19 treatment. The best inhibitors of each protease were tested in antiviral assay, with over 40% of Mpro inhibitors and over 20% of PLpro inhibitors showing high potency in viral inhibition with low cytotoxicity. The X-ray crystal structure of SARS-CoV-2 Mpro in complex with its potent inhibitor 4a was determined at 1.8 Å resolution. Together with docking assays, our results provide a comprehensive resource for future research on anti-SARS-CoV-2 drug development.

Genomic Feature Analysis of Betacoronavirus Provides Insights Into SARS and COVID-19 Pandemics.

In December 2019, the world awoke to a new betacoronavirus strain named severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Betacoronavirus consists of A, B, C and D subgroups. Both SARS-CoV and SARS-CoV-2 belong to betacoronavirus subgroup B. In the present study, we divided betacoronavirus subgroup B into the SARS1 and SARS2 classes by six key insertions and deletions (InDels) in betacoronavirus genomes, and identified a recently detected betacoronavirus strains RmYN02 as a recombinant strain across the SARS1 and SARS2 classes, which has potential to generate a new strain with similar risk as SARS-CoV and SARS-CoV-2. By analyzing genomic features of betacoronavirus, we concluded: (1) the jumping transcription and recombination of CoVs share the same molecular mechanism, which inevitably causes CoV outbreaks; (2) recombination, receptor binding abilities, junction furin cleavage sites (FCSs), first hairpins and ORF8s are main factors contributing to extraordinary transmission, virulence and host adaptability of betacoronavirus; and (3) the strong recombination ability of CoVs integrated other main factors to generate multiple recombinant strains, two of which evolved into SARS-CoV and SARS-CoV-2, resulting in the SARS and COVID-19 pandemics. As the most important genomic features of SARS-CoV and SARS-CoV-2, an enhanced ORF8 and a novel junction FCS, respectively, are indispensable clues for future studies of their origin and evolution. The WIV1 strain without the enhanced ORF8 and the RaTG13 strain without the junction FCS "RRAR" may contribute to, but are not the immediate ancestors of SARS-CoV and SARS-CoV-2, respectively.

A Negative Feedback Model to Explain Regulation of SARS-CoV-2 Replication and Transcription.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although a preliminary understanding of the replication and transcription of SARS-CoV-2 has recently emerged, their regulation remains unknown. RESULTS: By comprehensive analysis of genome sequence and protein structure data, we propose a negative feedback model to explain the regulation of CoV replication and transcription, providing a molecular basis of the "leader-to-body fusion" model. The key step leading to the proposal of our model was that the transcription regulatory sequence (TRS) motifs were identified as the cleavage sites of nsp15, a nidoviral RNA uridylate-specific endoribonuclease (NendoU). According to this model, nsp15 regulates the synthesis of subgenomic RNAs (sgRNAs), and genomic RNAs (gRNAs) by cleaving TRSs. The expression level of nsp15 controls the relative proportions of sgRNAs and gRNAs, which in turn change the expression level of nsp15 to reach equilibrium between the CoV replication and transcription. CONCLUSION: The replication and transcription of CoVs are regulated by a negative feedback mechanism that influences the persistence of CoVs in hosts. Our findings enrich fundamental knowledge in the field of gene expression and its regulation, and provide new clues for future studies. One important clue is that nsp15 may be an important and ideal target for the development of drugs (e.g., uridine derivatives) against CoVs.

Bioinformatics analysis of the 2019 novel coronavirus genome

In December 2019, a pneumonia outbreak caused by a human coronavirus was reported in Wuhan (China). This virus was predicted as a new coronavirus, named the 2019 novel coronavirus (2019-nCoV), as it caused clinical symptoms different from Severe Acute Respiratory Syndrome (SARS) during the 2003 outbreak. Currently, most of the researchers simply use the complete genome or specific structural gene sequences to investigate coronavirus (e. g. phylogenetic analysis) without considering the functions of the products from coronavirus genes. To overcome this shortcoming, we proposed the joint analysis of the molecular function and phylogeny, and applied it in our previous study of genomes of Betacoronavirus subgroup B(BB coronavirus). In that study, we identified a 22-bp complemented palindrome from a highly conserved Coding Sequence (CDS). Both the 22-bp complemented palindrome (named Nankai complemented palindrome) and the CDS (named Nankai CDS), evolutionary conserved in BB coronavirus genomes, were identified as genomic features associated to the molecular functions of BB coronavirus. In the present study, we used these two genomic features to trace the origin of 2019-nCoV (GenBank: MN908947) and conduct a preliminary study of the mechanisms in the cross-species infection and host adaption of BB coronavirus. Our analytical results show that 2019-nCoV with large differences from the SARS coronavirus, may originate from BB coronaviruses in bats. The most important finding is that the alternative translation of Nankai CDS could produce more than 17 putative proteins, which may be responsible for the host adaption. The genotyping of 13 viruses using the 17 putative proteins revealed the high mutation rate and diversity of BB coronavirus. Our study, for the first time, aimed to explain the reason for the high host adaptability of the multi-host BB coronavirus at the molecular level using large amounts of genomic data. The findings in the present study laid foundations for the rapid detection, genotyping, vaccine development and drug design of, but not limited to BB coronavirus.

Evolutionary history, potential intermediate animal host, and cross-species analyses of SARS-CoV-2.

To investigate the evolutionary history of the recent outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in China, a total of 70 genomes of virus strains from China and elsewhere with sampling dates between 24 December 2019 and 3 February 2020 were analyzed. To explore the potential intermediate animal host of the SARS-CoV-2 virus, we reanalyzed virome data sets from pangolins and representative SARS-related coronaviruses isolates from bats, with particular attention paid to the spike glycoprotein gene. We performed phylogenetic, split network, transmission network, likelihood-mapping, and comparative analyses of the genomes. Based on Bayesian time-scaled phylogenetic analysis using the tip-dating method, we estimated the time to the most recent common ancestor and evolutionary rate of SARS-CoV-2, which ranged from 22 to 24 November 2019 and 1.19 to 1.31 × 10-3 substitutions per site per year, respectively. Our results also revealed that the BetaCoV/bat/Yunnan/RaTG13/2013 virus was more similar to the SARS-CoV-2 virus than the coronavirus obtained from the two pangolin samples (SRR10168377 and SRR10168378). We also identified a unique peptide (PRRA) insertion in the human SARS-CoV-2 virus, which may be involved in the proteolytic cleavage of the spike protein by cellular proteases, and thus could impact host range and transmissibility. Interestingly, the coronavirus carried by pangolins did not have the RRAR motif. Therefore, we concluded that the human SARS-CoV-2 virus, which is responsible for the recent outbreak of COVID-19, did not come directly from pangolins.

Transmission dynamics and evolutionary history of 2019-nCoV.

To investigate the time origin, genetic diversity, and transmission dynamics of the recent 2019-nCoV outbreak in China and beyond, a total of 32 genomes of virus strains sampled from China, Thailand, and the USA with sampling dates between 24 December 2019 and 23 January 2020 were analyzed. Phylogenetic, transmission network, and likelihood-mapping analyses of the genome sequences were performed. On the basis of the likelihood-mapping analysis, the increasing tree-like signals (from 0% to 8.2%, 18.2%, and 25.4%) over time may be indicative of increasing genetic diversity of 2019-nCoV in human hosts. We identified three phylogenetic clusters using the Bayesian inference framework and three transmission clusters using transmission network analysis, with only one cluster identified by both methods using the above genome sequences of 2019-nCoV strains. The estimated mean evolutionary rate for 2019-nCoV ranged from 1.7926 × 10-3 to 1.8266 × 10-3 substitutions per site per year. On the basis of our study, undertaking epidemiological investigations and genomic data surveillance could positively impact public health in terms of guiding prevention efforts to reduce 2019-nCOV transmission in real-time.