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
中科院分区:
文献类型:
--
作者:
Di Rienzo L;Monti M;Milanetti E;Miotto M;Boffi A;Tartaglia GG;Ruocco G
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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影响因子:
64.8
作者:
Barnes CO;Jette CA;Abernathy ME;Dam KA;Esswein SR;Gristick HB;Malyutin AG;Sharaf NG;Huey-Tubman KE;Lee YE;Robbiani DF;Nussenzweig MC;West AP Jr;Bjorkman PJ
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Dunbrack, Roland L., Jr.
DOI:
10.1073/pnas.0812414106
发表时间:
2009-06-23
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通讯作者:
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