期刊
JOURNAL OF MOLECULAR LIQUIDS
卷 345, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.molliq.2021.117852
关键词
Coronavirus; MD simulation; Sensor; Electrostatic interaction; Nanostructures; Graphene; Phosphorene
资金
- Ferdowsi University of Mashhad [FUM-41073]
Through molecular dynamics simulations, it was found that phosphorene has higher affinity and sensitivity for SARS-CoV-2 RBD, making it a promising candidate for designing new nanomaterials for selective detection of the virus.
Due to the dramatic increase in the number of patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), designing new selective and sensitive sensors for the detection of this virus is of importance. In this research, by employing full atomistic molecular dynamics (MD) simulations, the interactions of the receptor-binding domain (RBD) of the SARS-CoV-2 with phosphorene and graphene nanosheets were analyzed to investigate their sensing ability against this protein. Based on the obtained results, the RBD interactions with the surface of graphene and phosphorene nanosheets do not have important effects on the folding properties of the RBD but this protein has unique dynamical behavior against each nanostructure. In the presence of graphene and phosphorene, the RBD has lower stability because due to the strong interactions between RBD and these nanostructures. This protein spreads on the surface and has lower structural compaction, but in comparison with graphene, RBD shows greater stability on the surface of the phosphorene nanosheet. Moreover, RBD forms a more stable complex with phosphorene nanosheet in comparison with graphene due to greater electrostatic and van der Waals interactions. The calculated Gibbs binding energy for the RBD complexation process with phosphorene and graphene are -200.37 and -83.65 kcal mol(-1), respectively confirming that phosphorene has higher affinity and sensitivity against this protein than graphene. Overall, the obtained results confirm that phosphorene can be a good candidate for designing new nanomaterials for selective detection of SARS-CoV-2. (C) 2021 Elsevier B.V. All rights reserved.
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