Network proteins of angiotensin-converting enzyme 2 but not angiotensin-converting enzyme 2 itself are host cell receptors for SARS-Coronavirus-2 attachment

Background: Coronaviruses causing severe acute respiratory syndrome (SARS-CoV) are known to enter the host cells by attaching to the membrane bound angiotensin-converting enzyme 2 (ACE2). Using molecular docking the efficiency of interaction between SARS-CoV-2 surface proteins and ACE2 network proteins was assessed. Materials and Methods : The ACE2 protein network was identified using the STRING database. The reported SARS-CoV-2 target proteins were searched in the protein data bank and uniport database. The protein-protein interactions were assessed by molecular docking using the Chimera software. The PubChem database was searched for known inhibitors of host cell receptors interacting with SARS-CoV-2 surface proteins. Molecular docking was performed to evaluate the binding efficacy of these compounds against the SARS-CoV-2 targets using AutoDock Vina and the docked protein-ligand complex were visualised using the Chimera and PyMOL software. Results : A low binding affinity was observed between SARS-CoV-2 spike proteins (protein S, M and 6YLA) and ACE2. Coronaviruses are also reported to bind to dipeptidyl peptidase 4 (DPP4), which is a network protein of ACE2. Network analysis showed five membrane proteins associated with ACE2. The ACE2 network proteins were assessed for their binding affinity with all known SARS-CoV-2 surface proteins. The SARS-CoV-2 surface proteins showed preferential binding to network proteins such as DPP4 and Meprin A alpha but not ACE2. The binding efficacy (affinity (-5.86 to -7.10 Kcal/mol), Ki (6.32 – 22.04 mM) and IC50 (12.63 – 113.71 mM) values) of DPP4 inhibitors (saxagliptin and sitagliptin) against SARS-CoV-2 surface proteins, was observed to be at a therapeutically feasible concentration to prevent SARS-CoV-2 attachment and entry into host cells. Conclusion : SARS-CoV-2 surface proteins has better interactions with DPP4 and Meprin A alpha host cells receptors rather than ACE2. DPP4 inhibitors (saxagliptin and sitagliptin) by binding with SARS-CoV-2 surface proteins may be helpful in preventing the virus entry into the host cells.


Introduction
The recent pandemic caused by a new strain of coronavirus (SARS-CoV-2) has resulted in serious health, social and economic setbacks. [1,2] Efforts to identify effective therapeutics or vaccine against SARS-CoV-2 illness (Covid- 19) is currently been extensively explored globally. [3][4][5][6] Understanding the mechanisms by which SARS-CoV-2 enters to host cell and replicates to cause Covid-19 is necessary for our efforts to develop effective therapeutics or vaccine. Coronavirus are reported to enter the host cells by attaching to the membrane bound ACE2 using their spike protein. [7,8] The spike protein (protein S) of SARS-CoV-2 and its other reports surface proteins were hence assessed for its binding with ACE2 and its associated network proteins using established molecular docking analysis.

Materials And Methods
Protein network analysis: The ACE2 protein network was analysed using the STRING database (https://string-db.org/cgi/info.pl). [9] The STRING database was searched using the ACE2 as protein name and Homo sapiens as organism.

SARS-CoV-2 surface proteins:
The reported SARS-CoV-2 target proteins were searched in the protein data bank (https://www.rcsb.org/) and uniport database (https://www.uniprot.org/peptidesearch/). [5] The following SARS-CoV-2 proteins were identified for binding analysis: PDB Protein 3D structure and molecular docking: The 3D structure of SARS-CoV-2 targets listed above were downloaded as PDB files from the protein data bank (https://www.rcsb.org/) and were optimized for molecular docking in the Chimera software. [10] The targets for which 3D structure was not available, the protein sequence (FASTA format) was downloaded from the uniport database and the 3D structure was constructed by homology modelling using the SWISS-MODEL server (https://swissmodel.expasy.org/). [11] For generating the 3D structures in the SWISS-MODEL server, each of the protein sequence in FASTA format was loaded into the SWISS-MODEL server [11] and the molecular modelling was initiated to generate PDB format of the protein. The interfaces of all the structures generated were refined with the Galaxy Refine Complex program installed in a computer with 2.66 GHz Intel Core 2 Duo processor, 4 GB 1067 MHz DDR3 RAM and with Mac OS X as the operating system. The 3D structural model generated was validated by measuring the probability of amino acids in the interface of the models. VADAR server was also used for the validation of 3D structure modelled by plotting Ramachandran plot [5] . The protein-protein interaction (between host cell receptor and SARS-CoV-2 targets) were assessed using the Chimera software. [5], 12 The crystal structure of human ACE2 (hACE2, PDB ID: Ir42) was downloaded from the protein data bank (PDB) and the 3D structure of SARS-CoV-2 protein S (Uniport ID P59594) was constructed by homology modelling using SWISS-MODEL server. [11] The structures of sitagliptin and saxagliptin were accessed from PubChem database and were processed into PDB file format and minimised for molecular docking using the Chimera software. [5], 12 Molecular docking was performed to evaluate the binding efficacy of these compounds against the SARS-CoV-2 targets using AutoDock Vina (version 1.5.4) and the docked protein-ligand complex were visualised using the Chimera and PyMOL v 1.8.2.0 software. [10,[12][13][14] AutoDock-MGLTools was employed to visualize and modify the receptor and ligand structures to PDBQT file formats. The logistic equation [15] . The means of the IC 5, 20, 60, 80 and 100 values obtained (in x axis) were plotted against the % inhibition response (in y axis) to obtain the simulated dose response curves.

Results
The first search in the STRING database was enhanced once to include additional nodes and 6 proteins were identified in the ACE2 network. All these 6 proteins (ACE2, DDP4, MEP1B, MEP1A, MME, PRCP and XPNPEP2) were membrane bound (Figure 1a). Six membrane associated network host cell proteins including ACE2 showed significant (p = 1.3x10 -09 ) interactions among themselves. In contrast to the published reports, SARS-CoV-2 protein S wasn't observed to be binding with hACE2 and no hydrogen bonds were observed between the two molecules.
Due to the poor interaction of SARS-CoV-2 protein S with hACE2, seventeen other SARS-CoV-2 target proteins (see methods) were assessed for their binding potential with hACE2. Only the SARS-CoV-2 6 protein M (a membrane associated matrix glycoprotein) and 6YLA (a receptor binding domain on spike) were observed very weakly bound to hACE2 (Figure 1b). In contrast both protein M and 6YLA but not protein S, were also observed to strongly bind with DPP4 ( Figure 1b).
Each of the network proteins of hACE2 were screened for molecular interactions with the seventeen SARS-CoV-2 target proteins ( Figure 2). The SARS-CoV-2 protein S did not bind to hACE2 or any of its other five network proteins. Stronger binding of SARS-CoV-2 protein M and 6YLA to DPP4 was observed compared to hACE2 (Figure 1b). The SARS-CoV-2 surface proteins were observed to effectively bind with all the network proteins of ACE2 with better efficiency (Figure 2a Discussion SARS-CoV-2 surface targets were observed to preferentially interact with ACE2 network proteins but not ACE2 itself. This wasn't surprising because the previous reports showing the interaction of ACE2 with coronavirus spike protein were performed in cell based assay systems using Vero E6 cells isolated from African green monkeys. [7,8] While structural similarities of proteins are evident across different species, the functional molecular interactions may differ between different species and as well as between different individuals of same species. The Insilco molecular interaction analysis allows to overcome this limitations by facilitating species specific molecular interaction analysis.
Further the short peptide sequences used to identify protein targets based on antibody-antigen interactions in cell based assay system may often cross react due to similarities between different protein sequence, resulting in false positive outcomes. ACE2 exists in soluble [16] as well as membrane bound [7,17] forms. It is likely that the reported affinity of SARS-CoV to soluble form of ACE2 [8] may differ with the membrane bound form of ACE2, this together with the species specific differences highlighted above may explain the weak interactions observed between ACE2 and SARS-CoV-2.
Considering the weak interactions between ACE2 and SARS-CoV-2, it is unlikely that approaches to upregulate ACE2 or using soluble forms of ACE2 [7,17] will be therapeutically beneficial in the clinical management of COVID-19.
Coronavirus are also reported to bind to DPP4 receptors on cell surface. [18,19] Both protein M and 6YLA but not protein S, were observed to strongly bind with DPP4 ( Figure 1b). Interestingly DPP4 was one of the network protein of hACE2 identified (Figure 1a). Hence a network analysis [9,20] was performed using the STRING database to identify all the primary ACE2 network proteins. The SARS-CoV-2 protein S did not bind to hACE2 or any of its other five network proteins, hence it is unlikely that this spike protein is involved in attachment and entry of the virus into the host cells. Further the stronger binding of SARS-CoV-2 protein M and 6YLA to DPP4 compared to hACE2 (Figure 1b), suggests that SARS-CoV-2 may preferentially attach to DPP4 rather than hACE2 for attaching and entering into the host cell. Consistent with this study, another strain of human coronavirus was reported to preferentially use DPP4 rather than ACE2 as the host cell entry receptor. [18,19] DPP4 is highly expressed in apical surfaces of human bronchiolar epithelial cell and lung tissue, [18,19] hence this receptor may be involved in increasing the susceptibility of the respiratory system to human coronavirus infection.
The SARS-CoV-2 surface proteins were observed to effectively bind with all the network proteins of 8 ACE2 with better efficiency (Figure 2a). Among the network proteins DPP4 and meprin A alpha were observed to bind to eight different SARS-CoV-2 surface proteins (Figure 2b). While the meprin A beta, MME, PRCP and XPNPEP2 were observed to be binding with at least 3-4 SARS-CoV-2 target proteins ( Figure 2b). This observations is in contrast to current knowledge on specific strains of coronavirus binding to selective host cell receptors. [3,6] It is likely that SARS-CoV-2 can either sequentially or preferentially interact with ACE2 network proteins (but not ACE2) for its attachment and entry into host cells. Currently the following three host cell membrane receptors; ACE2, aminopeptidase N (APN or CD13) or DPP4 are reported to be receptor for coronaviruses [8,19] . However this is the first report software. [12][13][14] Molecular docking with DPP4 and 6Y2E (SARS-CoV-2 main protease) were used as positive and negative controls respectively. The dose response effect of saxagliptin and sitagliptin against their selected targets ( Figure 3a) were simulated using the one standard deviation variation of the IC 50 values. [15] This new approach to model the dose response curves of ligand based on the IC 50 values estimated from the data of molecular docking will be a valuable tool in the Insilco and network pharmacology [9,20] for drug evaluation or repurposing.
Although DPP4 was reported as a selective receptor for hCoV-EMC, [18,19] its inhibitors were unlikely to block hCoV-EMC infection due to irrelevance of the DPP4 mediated proteolytic activity in the host cell entry of the virus. [19] However in this study DPP4 inhibitors were observed to have similar binding efficacy to both DDP4 and SARS-CoV-2 surface proteins (Figure 3