Ali Etemadia - Medical Biotechnology Department, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences (TUMS), Tehran, Iran
Hamid Reza Moradi - Medical Biotechnology Department, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences (TUMS), Tehran, Iran
Farideh Mohammadian - Department of Medical Biotechnology, Faculty of Advanced Medical Sciences, Tabriz University of Medical Sciences, Tabriz, Iran
Mohammad Hossein Karimi-Jafari - Department of Bioinformatics, Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran
Babak Negahdari
Yazdan Asgari

The COVID-۱۹ pandemic is affecting all aspects of people lives around the world. Coronaviruses are singlestrandedRNA viruses and SARS-CoV۲ belongs to the second group of this family⁠. Spike glycoprotein (Sprotein) of the virus is the key molecule employed for cell penetration by binding to the receptor-bindingdomain (RBD) of angiotensin converting enzyme ۲(ACE۲). It is the only homing receptor recognized for thevirus till date⁠. Blocking the Interaction of S protein and ACE۲ can inhibit the virus from entering the cell andreplication. Small Proteins (۲ – ۲۰ kDa) as antiviral medications, may hold great promises as the future oftherapeutics. Owing to the advances in the field of structural biology, it is now possible to design, highlyselective small proteins. Here, we aimed at designing some novel binders to block the S protein of the SARSCoV۲.The design process was based on collecting a list of natural proteins from PDB database⁠. Collected proteinswere monomeric, expressed in E.Coli and had no RNA, DNA, ligand or mutation in their structure. Then anInitial directed docking was performed by Patchdock against SARS-CoV۲ S protein. Best performing proteinwas selected (۳HGL) and used for interface designing by Rosettas FastDesign⁠. Next the new designedmodels were filtered and Cluspro and PatchDock was used for blind docking to select the best binders. Alsotheir structural parameters and characteristics was assessed with different web based tools. In the end,according to the data gathered from previous step three best performing binders have been chosen(BIN۳۲,BIN۷۸,BIN۹۱). In order to investigate the conformational behavior of the binder's models and nativescaffold, MD simulation was used⁠. The results showed that BIN۳۲,BIN۷۸,BIN۹۱ have a high binding energytowards S proteins of the SARS-CoV۲. (-۲۲.۴۳, -۲۰.۹۱ and -۱۷.۰۱ kcal/mol respectively)

Protein design, COVID-۱۹, Rosetta, MD simulations, Small Proteins