Development of Highly Potent Noncovalent Inhibitors of SARS-CoV-2 3CLpro.

The 3C-like protease (3CLpro) is an essential enzyme for the replication of SARS-CoV-2 and other coronaviruses and thus is a target for coronavirus drug discovery. Nearly all inhibitors of coronavirus 3CLpro reported so far are covalent inhibitors. Here, we report the development of specific, noncovalent inhibitors of 3CLpro. The most potent one, WU-04, effectively blocks SARS-CoV-2 replications in human cells with EC50 values in the 10-nM range. WU-04 also inhibits the 3CLpro of SARS-CoV and MERS-CoV with high potency, indicating that it is a pan-inhibitor of coronavirus 3CLpro. WU-04 showed anti-SARS-CoV-2 activity similar to that of PF-07321332 (Nirmatrelvir) in K18-hACE2 mice when the same dose was administered orally. Thus, WU-04 is a promising drug candidate for coronavirus treatment.

Development of Highly Potent Noncovalent Inhibitors of SARS-CoV-2 3CLpro

The 3C-like protease (3CLpro) is an essential enzyme for the replication of SARS-CoV-2 and other coronaviruses and thus is a target for coronavirus drug discovery. Nearly all inhibitors of coronavirus 3CLpro reported so far are covalent inhibitors. Here, we report the development of specific, noncovalent inhibitors of 3CLpro. The most potent one, WU-04, effectively blocks SARS-CoV-2 replications in human cells with EC50 values in the 10-nM range. WU-04 also inhibits the 3CLpro of SARS-CoV and MERS-CoV with high potency, indicating that it is a pan-inhibitor of coronavirus 3CLpro. WU-04 showed anti-SARS-CoV-2 activity similar to that of PF-07321332 (Nirmatrelvir) in K18-hACE2 mice when the same dose was administered orally. Thus, WU-04 is a promising drug candidate for coronavirus treatment. A novel oral noncovalent inhibitor of 3C-like protease, named WU-04, was developed as a promising drug candidate for COVID-19 treatment.

BRET-Based Self-Cleaving Biosensors for SARS-CoV-2 3CLpro Inhibitor Discovery.

The 3C-like protease (3CLpro) of SARS-CoV-2 is an attractive drug target for developing antivirals against SARS-CoV-2. A few small molecule inhibitors of 3CLpro are in clinical trials for COVID-19 treatments, and more inhibitors are under development. One limiting factor for 3CLpro inhibitors development is that the cellular activities of such inhibitors should be evaluated in Biosafety Level 3 (BSL-3) laboratories. Here, we design DNA-coded biosensors that can be used in BSL-2 laboratories to set up cell-based assays for 3CLpro inhibitor discovery. The biosensors were constructed by linking a green fluorescent protein (GFP2) to the N-terminus and a Renilla luciferase (RLuc8) to the C-terminus of SARS-CoV-2 3CLpro, with the linkers derived from the cleavage sequences of 3CLpro. After overexpression of the biosensors in human embryonic kidney (HEK) 293T cells, 3CLpro can be released from GFP2 and RLuc by self-cleavage, resulting in a decrease of the bioluminescence resonance energy transfer (BRET) signal. Using one of these biosensors, pBRET-10, we evaluated the cellular activities of several 3CLpro inhibitors. These inhibitors restored the BRET signal by blocking the proteolysis of pBRET-10, and their relative activities measured using pBRET-10 were consistent with their previously reported anti-SARS-CoV-2 activities. We conclude that the biosensor pBRET-10 is a useful tool for SARS-CoV-2 3CLpro inhibitor discovery. IMPORTANCE The virus proteases 3CLpro are validated drug targets for developing antivirals to treat coronavirus diseases, such as COVID-19. However, the development of 3CLpro inhibitors relies heavily on BSL-3 laboratories. Here, we report a series of BRET-based self-cleaving biosensors that can be used to set up cell-based assays to evaluate the cell permeability and cellular activity of SARS-CoV-2 3CLpro inhibitors in BSL-2 laboratories. The cell-based assay is suitable for high-throughput screening for 3CLpro inhibitors because of the simplicity and good reproducibility of our biosensors. The design strategy can also be used to design biosensors for other viral proteases for which the activation processes involve the self-cleavage of polyproteins.

Single cell atlas for 11 non-model mammals, reptiles and birds.

The availability of viral entry factors is a prerequisite for the cross-species transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Large-scale single-cell screening of animal cells could reveal the expression patterns of viral entry genes in different hosts. However, such exploration for SARS-CoV-2 remains limited. Here, we perform single-nucleus RNA sequencing for 11 non-model species, including pets (cat, dog, hamster, and lizard), livestock (goat and rabbit), poultry (duck and pigeon), and wildlife (pangolin, tiger, and deer), and investigated the co-expression of ACE2 and TMPRSS2. Furthermore, cross-species analysis of the lung cell atlas of the studied mammals, reptiles, and birds reveals core developmental programs, critical connectomes, and conserved regulatory circuits among these evolutionarily distant species. Overall, our work provides a compendium of gene expression profiles for non-model animals, which could be employed to identify potential SARS-CoV-2 target cells and putative zoonotic reservoirs.

An imperialist competition algorithm using a global search strategy for physical examination scheduling.

The outbreak of the novel coronavirus clearly highlights the importance of the need of effective physical examination scheduling. As treatment times for patients are uncertain, this remains a strongly NP-hard problem. Therefore, we introduce a complex flexible job shop scheduling model. In the process of physical examination for suspected patients, the physical examiner is considered a job, and the physical examination item and equipment correspond to an operation and a machine, respectively. We incorporate the processing time of the patient during the physical examination, the transportation time between equipment, and the setup time of the patient. A unique scheduling algorithm, called imperialist competition algorithm with global search strategy (ICA_GS) is developed for solving the physical examination scheduling problem. A local search strategy is embedded into ICA_GS for enhancing the searching behaviors, and a global search strategy is investigated to prevent falling into local optimality. Finally, the proposed algorithm is tested by simulating the execution of the physical examination scheduling processes, which verify that the proposed algorithm can better solve the physical examination scheduling problem.