key: cord-0866140-b70w8ega authors: Ranjan, Prashant; Neha; Devi, Chandra; Jain, Garima; Mallick, Chandana Basu; Das, Parimal title: Impact of B.1.617 and RBD SARS-CoV-2 variants on vaccine efficacy: An in-silico approach date: 2022-04-01 journal: Indian J Med Microbiol DOI: 10.1016/j.ijmmb.2022.03.009 sha: aae6ae2b88568e943e7cd124657150f425a79a24 doc_id: 866140 cord_uid: b70w8ega PURPOSE: The existing panels of COVID-19 vaccines are based on the spike protein of an earlier SARS-CoV-2 strain that emerged in Wuhan, China. However, the evolving nature of SARS-CoV-2 has resulted in the emergence of new variants, thereby posing a greater challenge in the management of the disease. India faced a deadlier second wave of infections very recently, and genomic surveillance revealed that the B.1.617 variant and its sublineages are responsible for the majority of the cases. Hence, it's crucial to determine if the current vaccines available can be effective against these variants. METHODS: To address this, we performed molecular dynamics (MD) simulation on B.1.617 along with K417G variants and other RBD variants. We studied structural alteration of the spike protein and factors affecting antibody neutralization and immune escape via In silico docking. RESULTS: We found that in seven of the 12 variants studied, there was a structural alteration in the RBD region, further affecting its stability and function. Docking analysis of RBD variants and wild-type strains revealed that these variants have a higher affinity for the ACE2 (angiotensin 2 altered enzymes) receptor. Molecular interaction with CR3022 antibody revealed that binding affinity was less in comparison to wild type, with B.1.617 showing the least binding affinity. CONCLUSIONS: The results of the extensive simulations provide novel mechanistic insights into the conformational dynamics and improve our understanding of the enhanced properties of these variants in terms of infectivity, transmissibility, neutralization potential, virulence, and host-viral replication fitness. COVID-19, a serious and continuously spreading pandemic affecting the world, creates severe ailments and apparently everlasting health problems. A few vaccines have exhibited potential & defensive effects upon COVID-19, mostly targeting the trimeric spike glycoprotein, which is involved in host cell interaction and gives passage to cell entry as well as the essential target for neutralizing antibodies. Essentially those were aimed against the earlier SARS-CoV-2 strain that emerged in 2019 in Wuhan China [1, 2] . Due to the perceived ease of transmission and expansive mutations in spike proteins, the speedy evolution of new variants of SARS-CoV-2 is of high concern. B.1.1.7 (Alpha), B.1.351 (Beta), P.1 (Gamma), and B.1.617.2 (Delta) are SARS-CoV-2 variants of concern (VOC) strains, whereas B.1.617.1 (Kappa) and B.1.617.3 (Deltaþ) are SARS-CoV-2 variations of interest (VOI) strains, according to the World Health Organization (VOI). The SARS-CoV-2 B.1.617 lineage, which was initially discovered in India, has spread around the world. B.1.617.1, B.1.617.2, and B.1.617.3 are the three sublineages that make up this lineage. Within the RBD of the S protein, mutations are identified in all of the sublineages [3] . The fast spread of the B.1.617 variation in India is thought to be related to the presence of several critical point mutations in the RBD, which may be enhancing the virus's cellular entrance, allowing it to infect a wider spectrum of target cells [4] . These alterations are also said to be the primary cause of their improved immune evasion ability. There are eight mutations in the SARSCoV-2 S protein of the B.1.617.1 (kappa) variant [5] . Seven of the eight mutations are found in the S1 region, while one is found in the S2 subunit. Two mutations in the RBD (L452R, E484Q), the area important for viral entry, are present in this variation. It was noted that several mutations of the receptor-binding domain (RBD), are essential for the interaction of Human angiotensin 2 altered enzymes (ACE2) [6] and antibodies, as well as region that neutralizes antibodies. The in-silico investigation revealed thatACE2 and potential antibodies bind in a similar area on the spike protein [7, 8] An antibody becomes very effective when forestalling viral spread by impeding the ACE2 binding site in the RBD. CR3022 antibody showed the most elevated binding affinity with SARS-CoV-2 protein RBD [9, 10] . Here, in this study, we retrieved 28 different spike protein variants, and out of these 28 variants, 12 variants belong to the RBD region only. Here, we focused to know the impact of B.1.617 RBD variants that affect the interaction of CR3022 Abs and ACE2R to bind with the SARS-CoV-2 RBD as compared to others RBD variants and used molecular dynamics (MD) simulations to understand the conformational dynamics. Crystal structures of spike protein (PDBID-7AD1), ACE2 (PDBID-6ACG) and antibody CR3022 (PDBID 6YLA) were retrieved from PDB RCSB (https://www.rcsb.org/). All water molecules and hetero-atoms were removed by using Discovery studio visualization software (BIO-VIA 2020). (http://accelrys.com/products/collaborative-science/biovia -discovery-studio/visualization-download.php). Based on high similarity, 7AD1 (crystal structure of SARS-CoV-2) was selected as template for homology modeling of RBD mutant variants using the SWISS-MODEL [11] . Energy minimization and structural analysis of RBD mutant variants were done with UCSF Chimera [12] . Evaluation of the modeled structure was done by PDB-Sum (http:// www.ebi.ac.uk/thornton-srv/databases/cgi-bin/pdbsum/GetPage.pl?pd bcode¼index.html). Docking of RBD mutant variants with selected targets (ACE2 receptor and antibody structure CR3022) was carried out by PatchDock server [13] by choosing parameter RMSD esteem 4.0 and complex type as default. Docking investigation was based on geometric shape complementarities score. Higher score indicates higher binding affinity. Outcome of the results is based on the docking scores and interaction at the RBD regions. Protein-protein and antibody-protein interactions were visualized by LigPlot plus v2.2 [14] . Molecular interactions of antibody CR3022 and ACE2 receptor with RBD variants were performed by antibody script under antibody loop numbering scheme i.e. KABAT Scheme and DIMPLOT script algorithm package built into LigPlot plus v2.2 respectively. The equilibrium and the dynamic behavior of wild and mutant variants of RBD Spike protein was studied by using GROMACS [15, 16] . MD simulation brings about time-dependent conformational changes and adjustment of protein, which opens to the alteration in unique nature after establishment of mutation in protein. We used GROMOS96 54a7 force field [17] for MD simulation study. We added solvent water around protein to facilitate from spc216.gro as a non-exclusive equilibrated 3-point dissolvable water model in a dodecahedron. Here, we kept the protein in the centre at least 1.0 nm from the case edges. Further, the steepest descent algorithm was utilized for energy minimization, to remove the steric conflicts and unstable conformations. Further we equilibrate the system via NVT ensemble (constant Number of particles, Volume and Temperature) and NPTensemble (constant Number of particles, Pressure and Temperature). After achieving equilibrium process, we moved for MD run to 10ns.Data analysis was done by Gromacs tools i.e. gmx rms for RMSD (Root Mean Square Deviation), gmxrmsf for RMSF (Root Mean Square Fluctuation), gmx gyrate for radius of gyration (Rg), gmxhbond for H-bond (for intra-protein H-bonds and for H-bonds between protein and water), and gmxsasa for SASA (solvent accessible surface). We further used GRACE software for data visualization. We retrieved 28 variant mutants (S1) in spike protein identified to date. We found 12 variants/mutants in the RBD region. The RBD region is important for ACE2 and Antibody interactions. A few RBD variants have already shown to affect the vaccine efficacy as documented earlier by wet lab and dry lab results (S2 Table) , however, the vaccine efficacy against the B.1.617 and K417G variants is yet to be elucidated. We have done structural analysis of all 12 RBD mutant variants and compared them with wild type. We found that seven mutant variants (F486L, Q493N, B.1.617 (L452R & E484Q), R408I, L455Y, K417G and E484K) have structural changes in RBD region (S3). We analyzed interactions between RBD variants and ACE2 receptor. Moreover, we also checked the interactions between antibody and RBD variants. We found that seven structurally changed variants (F486L, Q493N, B.1.617, R408I, L455Y, K417G and E484K) have high docking score against ACE2 receptor compared with wild type and less docking score against antibody (CR3022) unlike wild type ( Table 1) . Out of seven variants, B.1.617 (B.1.617