Interface design of SARS-CoV-2 symmetrical nsp7 dimer and machine learning-guided nsp7 sequence prediction reveals physicochemical properties and hotspots for nsp7 stability, adaptation, and therapeutic design

The COVID-19 pandemic, driven by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), necessitates a profound understanding of the virus and its lifecycle. As an RNA virus with high mutation rates, SARS-CoV-2 exhibits genetic variability leading to the emergence of variants with potential i...

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Veröffentlicht in:	Physical chemistry chemical physics : PCCP 2024-05, Vol.26 (18), p.1446-1461
Hauptverfasser:	Yadav, Amar Jeet, Kumar, Shivank, Maurya, Shweata, Bhagat, Khushboo, Padhi, Aditya K
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptation Affinity Amino Acid Sequence Binding Copying Coronavirus RNA-Dependent RNA Polymerase - chemistry Coronavirus RNA-Dependent RNA Polymerase - genetics Coronavirus RNA-Dependent RNA Polymerase - metabolism COVID-19 COVID-19 - virology Design Dimerization Dimers Evolution Humans Machine Learning Molecular interactions Mutation Predictions Protein Multimerization Proteins Residues Ribonucleic acid RNA RNA polymerase SARS-CoV-2 - chemistry SARS-CoV-2 - genetics Severe acute respiratory syndrome coronavirus 2 Stability Structural analysis Viral diseases Viral Nonstructural Proteins - chemistry Viral Nonstructural Proteins - genetics Viral Nonstructural Proteins - metabolism Viruses
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