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1 Ergebnisse
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Modeling SARS-CoV-2 spike/ACE2 protein–protein interactions..:
Tragni, Vincenzo
;
Preziusi, Francesca
;
Laera, Luna
...
info:eu-repo/semantics/altIdentifier/wos/WOS:000739754400001. , 2022
Link:
http://hdl.handle.net/11563/153465
RT Journal T1
Modeling SARS-CoV-2 spike/ACE2 protein–protein interactions for predicting the binding affinity of new spike variants for ACE2, and novel ACE2 structurally related human protein targets, for COVID-19 handling in the 3PM context
UL https://suche.suub.uni-bremen.de/peid=base-ftunivbasilicata:oai:iris.unibas.it:11563_153465&Exemplar=1&LAN=DE A1 Tragni, Vincenzo A1 Preziusi, Francesca A1 Laera, Luna A1 Onofrio, Angelo A1 Mercurio, Ivan A1 Todisco, Simona A1 Volpicella, Mariateresa A1 De Grassi, Anna A1 Pierri, Ciro Leonardo YR 2022 K1 Predictive K1 Preventive and personalized medicine (PPPM/3PM) · COVID-19 · SARS-CoV-2 spike variants · Angiotensin-converting enzyme II (ACE2) · Modelling · In silico analysis · Predictive software · Protein–protein interaction · Interaction energies · Transmissibility and virulence prediction · Mutant localization · Receptor binding motif (RBM) · Receptor binding domain (RBD) · SARS-CoV-2 cell entry-factors · ACE2 structurally related proteins · Thimet oligopeptidase (THOP1) · Neurolysin (NLN) · Targeted therapy · Improved individual outcomes JF info:eu-repo/semantics/altIdentifier/wos/WOS:000739754400001 LK http://hdl.handle.net/11563/153465 DO http://hdl.handle.net/11563/153465 SF ELIB - SuUB Bremen
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