Discovery of human coronaviruses pan-papain-like protease inhibitors using computational approaches
	    		
		   		
	    	
    	
    	
   		
        
        	
        	
        	
        		- Author:
	        		
		        		
		        		
			        		A.Alamri MUBARAK
			        		
			        		
			        		
			        			1
			        			
			        		
			        		
			        		
			        		
			        		;
		        		
		        		
		        		
			        		Muhammad Tahir ul Qamar
			        		
			        		;
		        		
		        		
		        		
			        		Mirza Usman MUHAMMAD
			        		
			        		;
		        		
		        		
		        		
			        		M.Alqahtani SAFAR
			        		
			        		;
		        		
		        		
		        		
			        		Froeyen MATHEUS
			        		
			        		;
		        		
		        		
		        		
			        		Chen LING-LING
			        		
			        		
		        		
		        		
		        		
		        		
		        			
			        		
			        		Author Information
			        		
		        		
		        		
			        		
			        		
			        			1. Department of Pharmaceutical Chemistry
			        		
		        		
	        		
        		 
        	
        	
        	
        	
        		- Keywords:
        			
	        			
	        				
	        				
			        		
				        		COVID-19;
			        		
			        		
			        		
				        		MERS-CoV;
			        		
			        		
			        		
				        		Molecular dynamic simulation;
			        		
			        		
			        		
				        		Pan-inhibitors;
			        		
			        		
			        		
				        		Papain-like protease;
			        		
			        		
			        		
				        		SARS-CoV;
			        		
			        		
			        		
				        		SARS-CoV-2;
			        		
			        		
			        		
				        		Virtual screening
			        		
			        		
	        			
        			
        		
 
        	
            
            
            	- From:
	            		
	            			Journal of Pharmaceutical Analysis
	            		
	            		 2020;10(6):546-559
	            	
            	
 
            
            
            	- CountryChina
 
            
            
            	- Language:Chinese
 
            
            
            	- 
		        	Abstract:
			       	
			       		
				        
				        	The papain-like protease (PLpro) is vital for the replication of coronaviruses (CoVs), as well as for escaping innate-immune responses of the host. Hence, it has emerged as an attractive antiviral drug-target. In this study, computational approaches were employed, mainly the structure-based virtual screening coupled with all-atom molecular dynamics (MD) simulations to computationally identify specific inhibitors of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) PLpro, which can be further developed as potential pan-PLpro based broad-spectrum antiviral drugs. The sequence, structure, and functional con-serveness of most deadly human CoVs PLpro were explored, and it was revealed that functionally important catalytic triad residues are well conserved among SARS-CoV, SARS-CoV-2, and middle east respiratory syndrome coronavirus (MERS-CoV). The subsequent screening of a focused protease in-hibitors database composed of ~7,000 compounds resulted in the identification of three candidate compounds, ADM_13083841, LMG_15521745, and SYN_15517940. These three compounds established conserved interactions which were further explored through MD simulations, free energy calculations, and residual energy contribution estimated by MM-PB(GB)SA method. All these compounds showed stable conformation and interacted well with the active residues of SARS-CoV-2 PLpro, and showed consistent interaction profile with SARS-CoV PLpro and MERS-CoV PLpro as well. Conclusively, the re-ported SARS-CoV-2 PLpro specific compounds could serve as seeds for developing potent pan-PLpro based broad-spectrum antiviral drugs against deadly human coronaviruses. Moreover, the presented infor-mation related to binding site residual energy contribution could lead to further optimization of these compounds.