Introduction: Introduction
COVID-19 global pandemic is caused by a coronavirus named Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The spike structural protein of SARS-CoV-2 mediate the host attachment and viral entering to host-cells by protein-protein interactions (PPIs) with the angiotensin-converting enzyme 2 (ACE2) as a host cellular receptor. Design peptide to block these critical PPIs is a new strategy to combat COVID-19 pandemic. Formation of disulfide bridges to cyclized peptide is preferable method in order to improve its activity and bioavailability as well as to prevent its digestion by protease enzymes. The aim of this study is to design cyclic peptide inhibitors to block SARS-CoV-2 spike and human ACE2 interaction by using computational PPIs analysis, molecular docking and drug scan methods
Methods: The computational peptide design is based on the key residues leading the SARS-CoV-2 spike and human ACE2 interactions. First, the crystal structure of SARS-CoV-2 spike receptor-binding domain bound with ACE2 with 6M0J PDB ID was obtained from RCSB PDB (https://rcsb.org). DIMPLOT program from LigPlot+ software (https://www.ebi.ac.uk/thornton-srv/software/LigPlus/) was used to analysis PPIs leading residues. 2D maps generated by DIMPLOT showed hydrogen bonds and hydrophobic contacts in PPIs and used for creating a list of residues in PPIs site for inhibitory peptide design. Then, 4 peptides were design and PEP-FOLD web-server (https://bioserv.rpbs.univ-paris-diderot.fr/services/PEP-FOLD3/) was used for de novo prediction of peptide 3D structures. PEP-Cyclizer (https://bioserv.rpbs.univ-paris-diderot.fr/services/PEP-Cyclizer/) was utilized for design of head-to-tail peptide cyclization. Molecular dockings of designed cyclic peptides with SARS-CoV-2 spike were conducted using Haddock web-server (https://wenmr.science.uu.nl/). ToxTree (http://toxtree.sourceforge.net/) and FAF-drugs4 (https://fafdrugs4.rpbs.univ-paris-diderot.fr/) were used for drug scan and ADME-Tox prediction assay. The physicochemical descriptors and properties of cyclic peptides were computed by these tools
Results: PPIs anaylis were done by studying critical residues leading SARS-CoV-2 spike and human ACE2 interactions. These residues were used for computational peptide design. Four cyclic peptides including CEADLFYQSSLASC, CIEEQAKTFLDKC, CIEEQAKTFLDKFNHEAEDLC, and CFNHEAEADLFYQSSLASC were designed. The molecular docking results showed that among the designed cyclic peptides CIEEQAKTFLDKC with highest binding energy to SARS-CoV-2 spike protein and the most acceptable properties derived from drug scan studies have great potential to inhibit interaction of spike and ACE2 receptor and blocking viral entry to host cells. No mutagenic and carcinogenic effects were predicted for these peptides. Also, good bioavailability was predicted for them
Conclusion: Our computational results including residues analysis in PPIs site, molecular docking, and drug scan studies revealed the cyclic peptides with the potential to act as SARS-CoV-2 spike protein inhibitor to block coronavirus entry to human cell. These peptides are the candidate to select as SARS-CoV-2 entry inhibitor to design and development of new drugs to treatment of COVID-19 pandemic. Note that this computational study need more wet lab and dry lab analysis