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024 7 _ |a 10.1007/s00894-022-05231-7
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100 1 _ |a Lai, Hien T. T.
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245 _ _ |a A comparative study of receptor interactions between SARS-CoV and SARS-CoV-2 from molecular modeling
260 _ _ |a Heidelberg
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520 _ _ |a The pandemic of COVID-19 severe acute respiratory syndrome, which was fatal for millions of people worldwide, triggeredthe race to understand in detail the molecular mechanisms of this disease. In this work, the differences of interactions betweenthe SARS-CoV/SARS-CoV-2 Receptor binding domain (RBD) and the human Angiotensin Converting Enzyme 2 (ACE2)receptor were studied using in silico tools. Our results show that SARS-CoV-2 RBD is more stable and forms more interactionswith ACE2 than SARS-CoV. At its interface, three stable binding patterns are observed and named red-K31, green-K353 and blue-M82 according to the central ACE2 binding residue. In SARS-CoV instead, only the first two binding patchesare persistently formed during the MD simulation. Our MM/GBSA calculations indicate the binding free energy differenceof about 2.5 kcal/mol between SARS-CoV-2 and SARS-CoV which is compatible with the experiments. The binding freeenergy decomposition points out that SARS-CoV-2 RBD–ACE2 interactions of the red-K31 ( −23.5 ± 0.2 kcal∕mol ) andblue-M82 ( −9.1 ± 0.1 kcal∕mol ) patterns contribute more to the binding affinity than in SARS-CoV ( −1.8 ± 0.02 kcal∕molfor red-K31), while the contribution of the green-K353 pattern is very similar in the two strains ( −17.8 ± 0.2 kcal∕moland −22.7 ± 0.1 kcal∕mol for SARS-CoV-2 and SARS-CoV, respectively). Five groups of mutations draw our attentionat the RBD–ACE2 binding interface, among them, the mutation –PPA469-471/GVEG482-485 has the most important andfavorable impact on SARS-CoV-2 binding to the ACE2 receptor. These results, highlighting the molecular differences in thebinding between the two viruses, contribute to the common knowledge about the new corona virus and to the developmentof appropriate antiviral treatments, addressing the necessity of ongoing pandemics.
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700 1 _ |a Nguyen, Ly H.
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700 1 _ |a Phan, Anh D.
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700 1 _ |a Kranjc Pietrucci, Agata
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700 1 _ |a Nguyen, Toan T.
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700 1 _ |a Nguyen-Manh, Duc
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773 _ _ |a 10.1007/s00894-022-05231-7
|g Vol. 28, no. 10, p. 305
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|t Journal of molecular modeling
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856 4 _ |u https://juser.fz-juelich.de/record/909710/files/Lai_J.Mol.Mod_2022.pdf
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