Background: The ORF1ab of Severe Acute Respiratory Syndrome, SARS Corona Virus, SARS-CoV-2 genome is processed into 15 non-structural proteins, NSPs by proteases and each NSP has a specific role in the life cycle and pathogenicity of the virus This research analyzes possible drugs for these proteins as targets in computational drug designing using already available experimental drugs from the drug bank database Methods: Out of 471 proteins and 8820 drugs download from Protein Data Bank, PDB and Drug Bank database respectively, 16 proteins similar to NSP 1-15 and 31 drugs as per the "Rule of three" were selected for docking Out of 88 docking results using PyRx, 18 proteins/chains with three promising drugs, DB01977, DB07132 and DB07535 were analyzed using PyMOL for final results Results: NSPs 3, 5, 11, 14 and 15 were identified as targets for the drugs, DB01977, BD07132 and DB07535 Drugs, DB01977 and DB07535 bind in the same binding pockets of NSP 5 and NSP 15 Drug, DB07132 binds with more number of residues when compared with the other two drugs and this indicates that the strength of protein-drug association is more by this drug with the NSPs than other drugs Binding pockets of NSPs for these three drugs are very close with many sharing residues in common suggesting of similarity of pharmacophore of these drugs with the target binding pockets Conclusion: The binding pockets of NSPs are well matched with the pharmacophore of drugs and with polar surface of drugs less than or equal to 100 A2, drugs, DB01977, DB07132 and DB07535 bind individually and effectively with NSPs 3, 5, 11, 14 and 15 of ORF1ab of SARS-CoV-2 genome to bring changes in the activity of SARS-CoV-2 which may be useful for biological and clinical considerations
Analysis of non-structural proteins, NSPs of SARS-CoV-2 as targets for computational drug designing