Development of highly potent non-covalent inhibitors of SARS-CoV-2 3CLpro

The SARS-CoV-2 virus is the causal agent of the ongoing pandemic of coronavirus disease 2019 (COVID-19). There is an urgent need for potent, specific antiviral compounds against SARS-CoV-2. 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, non-covalent 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. One-Sentence SummaryA oral non-covalent inhibitor of 3C-like protease effectively inhibits SARS-CoV-2 replication.

Study on transmission rate and quantitative structure-property relationships of alkaloids and iridoid compounds on UF membranes with MWCOS of 1000 / 中国中药杂志

<p><b>OBJECTIVE</b>Taking alkaloids and iridoid as the study, relationships of quantitative molecular structure and transmission rate on UF membrane were developed initially at exploring the mechanism of UF in Chinese herb decoction and to lay a foundation for the optimal design of membrane technology in the production of Chinese drugs preparation.</p><p><b>METHOD</b>The transmission rate of eight alkaloids and iridoid compounds in three UF membranes was determined, and quantitative structure-property relationships between quantitative molecular structure and transmission rate were developed by the data mining method of PLS or SVM.</p><p><b>RESULT</b>Quantitative structure-property relationship models of three membranes were developed by the data mining method of PLS or SVM, correlation coefficients were all greater than 0.9. The parameters in the models included LUMO, AlogP, CMR, K&H2, K&H3.</p><p><b>CONCLUSION</b>The relationship of UF transmission rate of these eight compounds and their molecular weight are not simply linearly dependent, the main factors which affect the UF transmission rate are capacity of gain or loss electron, hydrophilicity or hydrophobic and compound spatial structure.</p>