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Insight into the LFA-1/SARS-CoV-2 Orf7a Complex by Protein-Protein Docking, Molecular Dynamics, and MM-GBSA Calculations.
Ongaro, Alberto; Oselladore, Erika; Memo, Maurizio; Ribaudo, Giovanni; Gianoncelli, Alessandra.
  • Ongaro A; Department of Molecular and Translational Medicine, University of Brescia, Viale Europa 11, 25123 Brescia, Italy.
  • Oselladore E; Department of Molecular and Translational Medicine, University of Brescia, Viale Europa 11, 25123 Brescia, Italy.
  • Memo M; Department of Molecular and Translational Medicine, University of Brescia, Viale Europa 11, 25123 Brescia, Italy.
  • Ribaudo G; Department of Molecular and Translational Medicine, University of Brescia, Viale Europa 11, 25123 Brescia, Italy.
  • Gianoncelli A; Department of Molecular and Translational Medicine, University of Brescia, Viale Europa 11, 25123 Brescia, Italy.
J Chem Inf Model ; 61(6): 2780-2787, 2021 06 28.
Article in English | MEDLINE | ID: covidwho-1246311
ABSTRACT
In the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) genome, open reading frames (ORFs) encode for viral accessory proteins. Among these, Orf7a structurally resembles the members of the immunoglobulin (Ig) superfamily and intracellular adhesion molecules (ICAMs), in particular. ICAMs are involved in integrin binding through lymphocyte function-associated antigen 1 (LFA-1). Based on such considerations and on previous findings on SARS-CoV, it has been postulated that the formation of the LFA-1/Orf7a complex could contribute to SARS-CoV-2 infectivity and pathogenicity. With the current work, we aim at providing insight into this macromolecular assembly, taking advantage of the recently reported SARS-CoV-2 Orf7a structure. Protein-protein docking, molecular dynamics (MD) simulations, and a Molecular Mechanical-Generalized Born Surface Area (MM-GBSA)-based stage were enrolled to provide refined models.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Limits: Humans Language: English Journal: J Chem Inf Model Journal subject: Medical Informatics / Chemistry Year: 2021 Document Type: Article Affiliation country: Acs.jcim.1c00198

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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Limits: Humans Language: English Journal: J Chem Inf Model Journal subject: Medical Informatics / Chemistry Year: 2021 Document Type: Article Affiliation country: Acs.jcim.1c00198