Recently, a few animals have been frequently reported to have been diagnosed with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Whether they are SARS-CoV-2 intermediate hosts is worthy of great attention. The interaction of SARS-CoV-2 spike protein and its acceptor protein ACE2 is an important issue in determining viral host range and cross-species infection, while the binding capacity of Spike protein to ACE2 of different species is unknown. Here, we used the atomic structure model of SARS-CoV-2 and human ACE2 to assess the receptor utilization capacity of ACE2s from 10 kinds of animals. Results show that chimpanzees, domestic cats and cattles are more susceptible to infection by SARS-CoV-2. Cats in particular, such as pet cats and stray cats, interact very closely with humans, implying the necessity to carefully evaluate the risk of cats during the current COVID-19 pandemic. Furthermore, based on ACE2(cats)-SARS-CoV-2-RBD model, through high-throughput screening methods using a pool of 30,000 small molecules, eight compounds were selected for binding free energy calculations. All the eight compounds can effectively interfere with the binding of ACE2 and Spike protein, especially Nelfinavir, providing drug candidates for the treatment and prevention of SARS-CoV-2, suggesting further assessment of the anti-SARS-CoV-2 activity of these compounds in cell culture. Although we only reported the results of the simulation, and more laboratory and epidemiological investigation are required. Like cats are a risk factor, we can further detect SARS-CoV-2 according to the susceptibility of different animals, find the potential host of infection, and completely cut off the living space of the virus. Especially, cats could be a choice of animal model for screening antiviral drugs or vaccine candidates against SARS-CoV-2.
In order to understand the influence of the lockdown of COVID-19 on the thermal comfort of college students' dormitories, the temperature and humidity inside and outside the dormitories of a university in the severe cold region in spring were tested on site. At the same time, the environmental conditions and students' emotional state in college students' dormitories were investigated in the form of online questionnaires. Taking PMV as the overall evaluation index of thermal comfort, the linear regression equations of MTS and PMV were obtained by weighted regression analysis of MTS, PMV and air temperature. By analyzing the relationship curve between TSV and TCV, it can be seen that the comfort in the thermal environment is higher than that in the cold environment, and students are more inclined to the hot environment. The results of the questionnaire showd that during the period of COVID-19 lockdown, college students stayed in the dormitory for a long time, with little activity intensity, and a few students had irritability. Most students do not fully realize that indoor air quality can be adjusted by adaptive behavior, such as intermittent opening of doors and windows, increasing the opening of doors and windows. The regression equations of indoor residence time, exercise intensity and emotional state with TSV and TCV were fitted, and their effects on TSV and TCV were analyzed. It can be seen that the indoor residence time had no significant effect on TSV and TCV during the lockdown period. Low-intensity activity is conducive to indoor thermal comfort in spring, and human thermal comfort and thermal sensation are the best in a calm emotional state. This study is conducive to improving the thermal environment of college students' dormitories during the lockdown period, improving the comfort of dormitories, and preparing for the isolation of public health emergencies in the future.
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