A plausible path to contain the spread of 2019 Novel Coronavirus; a computational analysis prompts to the use of ACE2 receptor blockers

Starting December 30th, 2019, a virus spread from Wuhan, in the Hubei Province of China. The virus had soon been recognized as part of the Coronavirus and temporarily named 2019 Novel Coronavirus. The dramatic increase of infections led to the death of over 400 people, by Feb 4th, 2020. By this day the virus had already crossed into 27 countries. March 11th, 2020 the World Health Organization declared the Novel Coronavirus a pandemic, pointing to over 118,000 cases of infections in over 110 countries. This public health threat drove the international community to real-time sharing of the genetic sequences isolated from the viruses. We used these freely accessible genetic data, while leveraging bioinformatic tools, with the intent to explore possible contributions to address this threat. Angiotensin-converting Enzyme 2 Inhibition has been proven to be a valuable strategy address the spread of SARS. After proving remarkable genetic similarities between SARS and the 2019 Novel Coronavirus, we computationally built the first known ex-novo model of the 2019 Novel Coronavirus Spike Glycoprotein entirely generated from its aminoacidic sequence, using I-TASEER. We then assessed the 2019 Novel Coronavirus interaction with the human Angiotensin-converting Enzyme 2. This research prompts at the potential use of Angiotensin- converting Enzyme 2 receptors blockers, as both clinical and prophylaxis measures to contain the spread of 2019 Novel Coronavirus.


Introduction
December 30th, 2019, the Wuhan Municipal Health Commission reported an increase in cases of pneumonia in Wuhan city, Hubei province of China1. On December 31st, 2019 the WHO was alerted that the specific virus infection didn't reassemble any other known virus. One week later, January 7th, all Influenza Data (GISAID) allowing scientist around the world to have access to data and be able to analyze genetic sequences5. By Jan 17th ,2020, new cases were reported in both Thailand and Japan.6 Given the global threat posed by this virus, several strategies were globally implemented by several governments, including repatriation of citizens and airlines halting their routes to China. By January 30th, multiple corporations, including Amazon, Starbuck and Apple had revised their operations in China due to COVID-2019, thus leading to important financial implications. By February 4th, over 20 thousand cases and 426 deaths were confirmed, in 27 countries. March 11th, 2020 the World Health Organization declared the Novel Coronavirus a pandemic, pointing to over 118,000 cases of infections in over 110 countries. Given the threats associated with the spread of this virus and its global implications, the international scientific community has joined forces to tackle this issue. Several portals were implemented allowing the real time sharing of information, including epidemiological7 and genetic data8. This study aims to leverage this genetic information and use bioinformatic tools to analyze the nature of this virus, so do address possible contingency remedies.
Genome analysis was performed to build a genealogy line of COVID-2019. Sequences alignments used to seek similarities to other known viral strains. Proteomic simulations were implemented to investigate the use of specific molecule as cure and/or prophylaxis measures to contain the spread of COVID-2019.

Methods
Genomic sequences were retrieved from the GISAID database.8 The chosen COVID-2019 sequence was submitted Jan 24th, 2019 to the Division of Viral Disease, Centers for Disease Control and Prevention (Atlanta, GA) by Queen et al., title: Full genome sequence of first U.S. case of COVID-2019 (Accession MN985325)9. Using the National Center for Biotechnology Information (NCBI), Basic Local Alignment Search Tool (BLAST) the full 29882 pb RNA sequence was aligned with all sequences within the NCBI repository. A genealogic tree was generated. The analysis of the output data showed high conservancy of the sequence between gene 21563 and 25384. This sequence is known to be coding for a Surface Spike (S) Glycoprotein. Spike Glycoproteins (S-Protein) are a type I membrane-bound protein, which have been proven to be key in the spread of SARS by mediating to the viral attachment to the host cell receptor angiotensin-converting enzyme 2 (ACE2). In Human, the hACE2 receptor is located in chromosome X, between pb 15,56,033 and pb 15,602,148.10 Starting from the aminoacidic sequence of, I-TASSER was used to simulate the three-dimensional structure of COVID-2019 S-Protein. The tridimensional structure was then used to analyze both structural proprieties and possible interactions with target receptors. Five structures where generated by I-TASSER, the one with higher C-Score (-1) was then chosen to perform further analysis. Swiss-Dock was used to assess the interaction between the newly generated COVID-2019 S-Protein and the These data clearly prove little mutation and tight genetic correlation between SARS and COVID-2019.
The genealogy tree also points to a plausible common host animal ancestor to be the bat. (Figure 1).
Looking at the alignments between the COVID-2019 and the SARS genome, the region between gene 21563 and gene 25384 was determined to be highly conserved. This region is known to code for the COVID-2019 S-Protein (GenBank: QHO60594.1). A BLAST alignment of this aminoacidic sequence compared to the NCBI repository, showed E-Value 0.0, Identity 80.32% and Query Cover 99% with the S-Protein of Bat SARS-like coronavirus (Accession AVP78042.1) and E-Value 0.0, 76.27% Identity query cover 100%, with the SARS Coronavirus GZ02 S-Protein (GenBank: AAS00003.1). The aminoacidic sequence of the COVID-2019 S-Protein was then used to predict a tridimensional structure using I-TASSER; Five Models were generated with C-Scores respectively of -1.00, -1.24, -1.66 and -2.41. (Figure 2). C-score is typically in the range of -5,2, where a C-score of higher value signifies a model with a high confidence and vice-versa.
While generating the COVID-2019 S-Protein structure, I-TASSER also assessed matches with several templates. Comparison with Perfusion Structure of SARS-CoV spike glycoprotein, conformation 1 (PDB 5X58) showed 100% sequence identity of the template in the threading aligned region with the query sequence and 84% identity of the whole template chains with query sequence, coverage 84% (coverage of the threading alignment, which is equal to the number of aligned residues divided by the length of query protein) and Normalized Z-Score of 4.58, whereas alignment with a Normalized S-Score >1 mean a good alignment and vice versa.
Analysis of the predicted structure compared to PDB database showed identity of 98% and coverage of the alignment of 83% when compared to SARS-CoV complex with human neutralizing S230 antibody Fab fragment. (PDB 6nb6).
All together, these data show a reliable prediction, and close similarity between COVID-2019 S-Protein and SARS-CoV S-Protein.
The docking between the COVID-2019 S-Protein and the hACE2 receptor was simulated using the Swiss-Docking servers. Output data were further interpreter using Chimera. Analysis of the data showed similarities between the target-ligand interactions of the SARS-ACE2 and the COVID-2019-ACE2 docking models. (Figures 3a and 3b). Despite a more detailed analysis of the generated docking models might be appropriate within another publication, these data strongly prove how the interaction between hACE2 and both SARS and COVID-2019 S-Protein are of the same nature. Both S-Proteins show affinity to the hACE receptor.
Despite a lower affinity is reported for the hACE2-nCoV S-Protein complex, it is still reasonable to conclude that S-Proteins interactions with the hACE2 receptor play a key role also for the replication and spread of COVID-2019. These data are in accordance also with the conclusions of Xintian Xu et al., that, constructing the Wuhan CoV S-protein by Swiss-model, and using SARS Coronavirus as a template, determined that despite the loss of hydrogen bonds due to the replacing of Arg426 and