Computational optimization of angiotensin-converting enzyme 2 for SARS-CoV-2 Spike molecular recognition.

Computational optimization of angiotensin-converting enzyme 2 for SARS-CoV-2 Spike molecular recognition.
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DOI:
10.1016/j.csbj.2021.05.016
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发表时间:
2021
影响因子:
6
通讯作者:
Ruocco G
Ruocco G
中科院分区:
生物学2区
文献类型:
--
作者:
Di Rienzo L;Monti M;Milanetti E;Miotto M;Boffi A;Tartaglia GG;Ruocco G

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自19型冠状病毒大流行开始以来,一直致力于确定中和宿主细胞内SARS-CoV-2复制的方法。一种有希望的阻断感染的策略包括使用人类受体血管紧张素转换酶2(ACE2)的突变体作为诱饵,与内源性ACE2竞争与SARS-CoV-2刺突蛋白的结合,从而降低病毒进入宿主细胞的能力。在这里,使用基于2D Zernike形式的计算框架,我们研究了分子结合的细节,并评估了当分子界面的ACE2侧发生突变时,ACE2-Spike结合兼容性的变化。我们通过将我们的结果与ACE2突变的实验结合亲和力变化进行比较来证明我们方法的有效性,根据分析的影响的大小,分离出与ROC曲线下区域结合亲和力增加或降低的结合亲和力增加或降低的结合亲和力。重要的是,我们方法的迭代导致了一组ACE2突变体的鉴定,其特征是与Spike的形状互补性增加。我们研究了这些ACE2突变体的物理化学性质,并提出它们是真正的棘波识别候选者。
Since the beginning of the Covid19 pandemic, many efforts have been devoted to identifying approaches to neutralize SARS-CoV-2 replication within the host cell. A promising strategy to block the infection consists of using a mutant of the human receptor angiotensin-converting enzyme 2 (ACE2) as a decoy to compete with endogenous ACE2 for the binding to the SARS-CoV-2 Spike protein, which decreases the ability of the virus to enter the host cell. Here, using a computational framework based on the 2D Zernike formalism we investigate details of the molecular binding and evaluate the changes in ACE2-Spike binding compatibility upon mutations occurring in the ACE2 side of the molecular interface. We demonstrate the efficacy of our method by comparing our results with experimental binding affinities changes upon ACE2 mutations, separating ones that increase or decrease binding affinity with an Area Under the ROC curve ranging from 0.66 to 0.93, depending on the magnitude of the effects analyzed. Importantly, the iteration of our approach leads to the identification of a set of ACE2 mutants characterized by an increased shape complementarity with Spike. We investigated the physico-chemical properties of these ACE2 mutants and propose them as bona fide candidates for Spike recognition.
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