scholarly journals Flexible, Functional, and Familiar: Characteristics of SARS-CoV-2 Spike Protein Evolution

2020 ◽  
Vol 11 ◽  
Author(s):  
Dianita S. Saputri ◽  
Songling Li ◽  
Floris J. van Eerden ◽  
John Rozewicki ◽  
Zichang Xu ◽  
...  
Author(s):  
Andreina Baj ◽  
Federica Novazzi ◽  
Francesca Drago Ferrante ◽  
Angelo Genoni ◽  
Elena Tettamanzi ◽  
...  

Biochemistry ◽  
2016 ◽  
Vol 55 (43) ◽  
pp. 5977-5988 ◽  
Author(s):  
Canping Huang ◽  
Jianxun Qi ◽  
Guangwen Lu ◽  
Qihui Wang ◽  
Yuan Yuan ◽  
...  

2021 ◽  
Author(s):  
Samuel King ◽  
Xinyi E. Chen ◽  
Sarah W. S. Ng ◽  
Kimia Rostin ◽  
Tylo Roberts ◽  
...  

AbstractViral vaccines can lose their efficacy as the genomes of targeted viruses rapidly evolve, resulting in new variants that may evade vaccine-induced immunity. This process is apparent in the emergence of new SARS-CoV-2 variants which have the potential to undermine vaccination efforts and cause further outbreaks. Predictive vaccinology points to a future of pandemic preparedness in which vaccines can be developed preemptively based in part on predictive models of viral evolution. Thus, modeling the trajectory of SARS-CoV-2 spike protein evolution could have value for mRNA vaccine development. Traditionally, in silico sequence evolution has been modeled discretely, while there has been limited investigation into continuous models. Here we present the Viral Predictor for mRNA Evolution (VPRE), an open-source software tool which learns from mutational patterns in viral proteins and models their most statistically likely evolutionary trajectories. We trained a variational autoencoder with real-time and simulated SARS-CoV-2 genome data from Australia to encode discrete spike protein sequences into continuous numerical variables. To simulate evolution along a phylogenetic path, we trained a Gaussian process model with the numerical variables to project spike protein evolution up to five months in advance. Our predictions mapped primarily to a sequence that differed by a single amino acid from the most reported spike protein in Australia within the prediction timeframe, indicating the utility of deep learning and continuous latent spaces for modeling viral protein evolution. VPRE can be readily adapted to investigate and predict the evolution of viruses other than SARS-CoV-2 in temporal, geographic, and lineage-specific pathways.


2020 ◽  
Author(s):  
Cristina Garcia-Iriepa ◽  
Cecilia Hognon ◽  
Antonio Francés-Monerris ◽  
Isabel Iriepa ◽  
Tom Miclot ◽  
...  

<div><p>Since the end of 2019, the coronavirus SARS-CoV-2 has caused more than 180,000 deaths all over the world, still lacking a medical treatment despite the concerns of the whole scientific community. Human Angiotensin-Converting Enzyme 2 (ACE2) was recently recognized as the transmembrane protein serving as SARS-CoV-2 entry point into cells, thus constituting the first biomolecular event leading to COVID-19 disease. Here, by means of a state-of-the-art computational approach, we propose a rational evaluation of the molecular mechanisms behind the formation of the complex and of the effects of possible ligands. Moreover, binding free energy between ACE2 and the active Receptor Binding Domain (RBD) of the SARS-CoV-2 spike protein is evaluated quantitatively, assessing the molecular mechanisms at the basis of the recognition and the ligand-induced decreased affinity. These results boost the knowledge on the molecular grounds of the SARS-CoV-2 infection and allow to suggest rationales useful for the subsequent rational molecular design to treat severe COVID-19 cases.</p></div>


2020 ◽  
Author(s):  
Sanaa Bardaweel

Recently, an outbreak of fatal coronavirus, SARS-CoV-2, has emerged from China and is rapidly spreading worldwide. As the coronavirus pandemic rages, drug discovery and development become even more challenging. Drug repurposing of the antimalarial drug chloroquine and its hydroxylated form had demonstrated apparent effectiveness in the treatment of COVID-19 associated pneumonia in clinical trials. SARS-CoV-2 spike protein shares 31.9% sequence identity with the spike protein presents in the Middle East Respiratory Syndrome Corona Virus (MERS-CoV), which infects cells through the interaction of its spike protein with the DPP4 receptor found on macrophages. Sitagliptin, a DPP4 inhibitor, that is known for its antidiabetic, immunoregulatory, anti-inflammatory, and beneficial cardiometabolic effects has been shown to reverse macrophage responses in MERS-CoV infection and reduce CXCL10 chemokine production in AIDS patients. We suggest that Sitagliptin may be beneficial alternative for the treatment of COVID-19 disease especially in diabetic patients and patients with preexisting cardiovascular conditions who are already at higher risk of COVID-19 infection.


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