Better binding informatics of delta variants (B.1.617.2) with ACE2 than wild, D614G or N501Y CoV-2 is fully blocked by 84 amino-acid cut of wild spike

ABSTRACT

Background and objective The B.1.617.2 known as the Delta-variant harbors diverse Spike-mutations with developed transmissibility and immune-evasion more than wild/D614G/N501Y variants. The Delta-variant claimed comparatively a large number of lives globally. In the present study, the binding-affinities of these variants’ spikes to the human lung-ACE2 were investigated. Further, a certain portion of the spike-protein with a desired mutation was tested in-silico to block the ACE2. Methods Structure of spike-variants were retrieved from PDB/GISAID and used for homology-modeling (SWISS-MODEL). A different combination of spike-ACE2 binding 11 or competitive blind-docking was performed using the Haddock 2.4 web-server. Eventually, two cut-segments (84 amino-acid of wild-spike, 432–516 Cut1) and its mutant T500S;Cut 2 were screened (Swiss-model Expasy-server) as blocker/inhibitor of all spike-variants (PyMOL-V2.2.2). Results It is shown that the stability and energy of the Delta binding-affinity to ACE2 is far more than others. The number H-bonding (5), their lengths (1.7 Å-2.8 Å) and energy, Van-der-Walls energy, Haddock-score were highly favorable for more stable-binding of Delta-RBD to ACE2. The Ramachandran-plot (Zlab/UMassMed Bioinfo) data supports this. We observed the best Haddock score as −120.8±2.6 for Delta with Van-der-Walls and electrostatic-energy as −62.9 and −208.7, respectively. The highest binding-affinity (ΔG) was −10.7 kcal/mol. Its THR500 and GLN506 strongly bind with the LYS353 of ACE2. The Cut1 and its mutant T500S completely blocked Delta-spike binding to ACE2 with ΔG -8.4 and −10.6 kcal/mol, respectively. But during the comparison between 2 Cuts, Cut1 showed better results. Conclusions Fractioned spike-protein from the conserved Receptor-Binding-Domain (RBD) could universally block the virus at entry-level, thus completely protecting any intercellular metabolism. Bioinformatics is an emerging field for screening of some drug/therapeutic targets from numerous options, minimizing time and expenses.