In Silico Design of Peptides with Binding to the Receptor Binding Domain (RBD) of the SARS-CoV-2 and Their Utility in Bio-Sensor Development for SARS-CoV-2 Detection

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected millions of people across the globe and created not only a health emergency but also a financial crisis. This virus attacks on the angiotensin-converting enzyme 2 (ACE2) receptor situated on the surface of the host cell membrane. The spike protein of the virus binds to this receptor which is a critical step of infection. A molecule which can specifically stop this binding could be a potential therapeutic. In this study, we have tested 12 potential peptides which can bind to the receptor binding domain (RBD) of the spike protein of the virus and thus can potentially inhibit the binding of the latter on ACE2 receptor. These peptides are screened based on their binding with RBD of the spike protein and aqueous stability, obtained using several atomistic molecular dynamic simulations. The potential of mean force calculation of two most promising peptides confirmed their binding to the RBD of the spike protein. Furthermore, these two potential peptides were tested for their use in a biosensing application for SARS-CoV-2 detection. Two types of biosensing platforms, a graphene sheet and a carbon nano tube (CNT), were tested. The peptides were modified in order to functionalize the graphene and CNT. Based on the interaction between the substrate, peptide and spike protein, the utility of screened peptide for a given bio sensing platform is discussed and recommended..

Medienart:

Preprint

Erscheinungsjahr:

2021

Erschienen:

2021

Enthalten in:

chemRxiv.org - (2021) vom: 18. Nov. Zur Gesamtaufnahme - year:2021

Sprache:

Englisch

Beteiligte Personen:

Badhe, Yogesh [VerfasserIn]
Gupta, Rakesh [VerfasserIn]
Rai, Beena [VerfasserIn]

Links:

Volltext [lizenzpflichtig]
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Themen:

540
Chemistry

doi:

10.26434/chemrxiv.13102172

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

XCH019139381