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构象变异性对奥密克戎变体季节性热稳定性和细胞进入的影响。

Effect of Conformational Variability on Seasonable Thermal Stability and Cell Entry of Omicron Variants.

作者信息

Izumi Hiroshi, Aoki Hiroshi, Nafie Laurence A, Dukor Rina K

机构信息

National Institute of Advanced Industrial Science and Technology (AIST), AIST Tsukuba West, Tsukuba, Ibaraki 305-8569, Japan.

Department of Chemistry, Syracuse University, Syracuse, New York 13244-4100, United States.

出版信息

ACS Omega. 2023 Feb 10;8(7):7111-7118. doi: 10.1021/acsomega.2c08075. eCollection 2023 Feb 21.

Abstract

The Omicron BA.1 variant of SARS-CoV-2 preferentially infects through the cathepsin-mediated endocytic pathway, but the mechanism of cell entry has not been solved yet because BA.4/5 is more fusogenic and more efficiently spread in human lung cells than BA.2. It has been unclear why the Omicron spike is inefficiently cleaved in virions compared with Delta, and how the relatively effective reproduction proceeds without the cell entry through plasma membrane fusion. Conformational variability from deep neural network-based prediction correlates well with the thermodynamic stability of variants. The difference of seasonable pandemic variants in summer and those in winter is distinguishable by this conformational stability, and the geographical optimization of variants is also traceable. Further, the predicted conformational variability maps rationalize the less efficient S1/S2 cleavage of Omicron variants and provide a valuable insight into the cell entry through the endocytic pathway. It is concluded that conformational variability prediction is able to complement transformation information on motifs in protein structures for drug discovery.

摘要

严重急性呼吸综合征冠状病毒2(SARS-CoV-2)的奥密克戎BA.1变体优先通过组织蛋白酶介导的内吞途径感染,但由于BA.4/5比BA.2具有更强的融合性且能在人肺细胞中更有效地传播,其细胞进入机制尚未得到解决。目前尚不清楚为何与德尔塔变体相比,奥密克戎刺突蛋白在病毒粒子中切割效率低下,以及在没有通过质膜融合进入细胞的情况下,相对有效的复制是如何进行的。基于深度神经网络预测得到的构象变异性与变体的热力学稳定性密切相关。通过这种构象稳定性,可以区分夏季和冬季季节性大流行变体的差异,并且变体的地理优化情况也可追溯。此外,预测的构象变异性图谱解释了奥密克戎变体S1/S2切割效率较低的原因,并为通过内吞途径进入细胞提供了有价值的见解。研究得出结论,构象变异性预测能够补充蛋白质结构中基序的转化信息,以用于药物发现。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8ca1/9948215/7fa295c9537c/ao2c08075_0001.jpg

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