key: cord-0753103-pl3qlcpo authors: Sohail, Ayesha; Nutini, Alessandro title: Forecasting the timeframe of coronavirus and human cells interaction with reverse engineering date: 2020-04-29 journal: Prog Biophys Mol Biol DOI: 10.1016/j.pbiomolbio.2020.04.002 sha: f6df77a425d4ca4091e6c013444aa65c032a60e0 doc_id: 753103 cord_uid: pl3qlcpo Abstract In December 2019, an atypical pneumonia invaded the city of Wuhan, China, and the causative agent of this disease turned out to be a new coronavirus. In January 2020, the World Health Organization named the new coronavirus 2019-nCoV and subsequently it is referred to as SARS-CoV2 and the related disease as CoViD-19 [9]. Very quickly, the epidemic led to a pandemic and it is now a worldwide emergency requiring the creation of new antiviral therapies and a related vaccine. The purpose of this article is to review and investigate further the molecular mechanism by which the SARS-CoV2 virus infection proceeds via the formation of a hetero-trimer between its protein S, the ACE2 receptor and the B0AT1 protein, which is the “entry receptor” for the infection process involving membrane fusion [10]. A reverse engineering process uses the formalism of the Hill function to represent the functions related to the dynamics of the biochemical interactions of the viral infection process. Then, using a logical evaluation of viral density that measures the rate at which the cells are hijacked by the virus (and they provide a place for the virus to replicate) and considering the “time delay” given by the interaction between cell and virus, the expected duration of the incubation period is predicted. The conclusion is that the density of the virus varies from the “exposure time” to the “interaction time” (virus-cells). This model can be used both to evaluate the infectious condition and to analyze the incubation period. Background The ongoing threat of the new coronavirus SARS-CoV2 pandemic is alarming and strategies for combating infection are highly desired. This RNA virus belongs to the β-coronavirus genus and is similar in some features to SARS-CoV. Currently, no vaccine or approved medical treatment is available. The complex dynamics of the rapid spread of this virus can be demonstrated with the aid of a computational framework. Methods A mathematical model based on the principles of cell-virus interaction is developed in this manuscript. The amino acid sequence of S proein and its interaction with the ACE-2 protein is mimicked with the aid of Hill function. The mathematical model with delay is solved with the aid of numerical solvers and the parametric values are obtained with the help of MCMC algorithm. Results A delay differential equation model is developed to demonstrate the dynamics of target cells, infected cells and the SARS-CoV2. The important parameters and coefficients are demonstrated with the aid of numerical computations. The resulting thresholds and forecasting may prove to be useful tools for future experimental studies and control strategies. Conclusions From the analysis, I is concluded that control strategy via delay is a promising technique and the role of Hill function formalism in control strategies can be better interpreted in an inexpensive manner with the aid of a theoretical framework. worldwide emergency requiring the creation of new antiviral therapies and a related vaccine. The purpose 11 of this article is to review and investigate further the molecular mechanism by which the SARS-CoV2 12 virus infection proceeds via the formation of a hetero-trimer between its protein S, the ACE2 receptor 13 and the B0AT1 protein, which is the "entry receptor" for the infection process involving membrane "animal to man" and then "man to man " transmission. In December 2019, atypical pneumonia invaded 49 the city of Wuhan, China, and the causative agent of this disease was identified as a new coronavirus that 50 has been subsequently sequenced by five independent laboratories in China (http://www.virological.org). In January 2020, the World Health Organization named the new coronavirus 2019-nCoV and subsequently 52 referred to it as SARS-CoV2 with its related disease referred to as CoViD-19 (Lai et al., 2020) . Very soon, the epidemic created a pandemic, which is still progressing due to the human mobility The Secto ectodomain, which has two subunits: a subunit-anti-receptor called S1 and a subunit S2 with 79 strong lithic action, (defined as lysis of the host cell membrane to carry out the virus-host fusion and 80 start the infectious process) fuses the virus with the membrane, allowing the viral genome to enter the 81 host. A crosstalk between S1 and S2 then activates the pre-fusion conformation, activating S2 itself. The 82 S1 subunit can be further divided into four core domains: S1a, S1b, S1c and S1d. Subunit S1 contains RBD (Receptor Binding Domain), which binds to the ACE-2 protein (angiotensin-84 converting enzyme 2) of the host cell membrane (on the surface of respiratory cells), which, in turn 85 functions as a receptor for the ligand (anti-receptor) constituted by the RBD domain itself. SARS-CoV 86 and SARS-CoV2 share 77.5% similarity in the amino acid sequence of S1. As mentioned above, viral 87 entry in the host requires S protein priming by cellular proteases, which involve S protein cleavage in S1 The binding with the ACE-2 protein occurs at the core domains S1a and this complex (ACE-2 + 97 S1a) makes the reaction irreversible. During this research, we have used the Hill function formalism to 98 illustrate the ligand-protein binding process. Details are provided in section 3. ACE-2, on the host cell 99 membrane, is usually connected to another protein called B 0 AT1. SARS-CoV2 infection begins with the 100 initial formation of a hetero trimer consisting of the RBD domain of the S1 subunit, from ACE-2 protein showing a cross reactivity with S1 subunits. Among these hybridomas, the one called 47D11 showed 117 neutralization activity for both SARS-CoV and SARS-CoV2 and targeted the RBD domain of S1b. binding that CoViD-19 shows in the infection process as described above. Our hypothesis is supported by 128 the need for activation of the infection system by the virus, given by the particular molecular kinetics that 129 leads to the formation of the "infection trimer" given by the viral S1 protein and the ACE-2 receptor While developing the computational framework, the virus-target cell interaction was studied in depth. For this purpose, Hill function formalism, which helps to depict the dynamical behaviour and the biochemical interactions, is utilized. The model development can be understood with the aid of the schematic presented in figure 3 . A standard mathematical description of this function is given as: (1) A computational framework to interpret the dynamics of viral infection is presented in this manuscript. The motivation behind the model development was to address the challenges linked with the fact that • determine/ forecast parametric values that will govern the dynamics of the mathematical model. 198 This "cytokine storm, causes the immune system to stat sending cells ready to do battle into the lung. 3. The reverse engineering approach proves to be efficient in parametric approximation for such com-220 plex dynamics. responsible for the interaction rates. Currently, the pandemic is ongoing. The model described here can 229 be implemented to future laboratory generated cell data. 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Receptor and viral determinants of sars-coronavirus adaptation to human ace2 Computational virology: from the inside out cancer drug therapy and stochastic modeling of 270 nano-motors Quantitative comparison 272 of human parainfluenza virus hemagglutinin-neuraminidase receptor binding and receptor cleavage Unexpected receptor functional mimicry elucidates activation of coronavirus 276 fusion A human monoclonal 1 antibody blocking sars-cov-2 279 infection. bioRxiv Cryo-em structure of the 2019-ncov spike in the prefusion conformation 284 et al. A new coronavirus associated with human respiratory disease in china Parameter estimation in systems biology models using spline approximation. 287 BMC systems biology The authors would like to acknowledge the support provided by Medical Officer Dr Sohail Iqbal. Conflict of Interest: 234 The authors declare that there is no conflict of interest. The authors declare that there is no conflict of interest. The authors contributed equally to the manuscript.