A novel infectious agent, SARS-CoV-2, is responsible for causing the severe respiratory disease COVID-19 and death in humans. Spike glycoprotein plays a key role in viral particles entering host cells, mediating receptor recognition and membrane fusion, and are considered useful targets for antiviral vaccine candidates. Therefore, computational techniques can be used to design a safe, antigenic, immunogenic, and stable vaccine against this pathogen. Drawing upon the structure of the S glycoprotein, we are trying to develop a potent multi-epitope subunit vaccine against SARS-CoV-2. The vaccine was designed based on cytotoxic T-lymphocyte and helper T-lymphocyte epitopes with an N-terminal adjuvant via conducting immune filters and an extensive immunoinformatic investigation. The safety and immunogenicity of the designed vaccine were further evaluated via using various physicochemical, allergenic, and antigenic characteristics. Vaccine-target (toll-like receptors: TLR2 and TLR4) interactions, binding affinities, and dynamical stabilities were inspected through molecular docking and molecular dynamic (MD) simulation methods. Moreover, MD simulations for dimeric TLRs/vaccine in the membrane-aqueous environment were performed to understand the differential domain organization of TLRs/vaccine. Further, dynamical behaviors of vaccine/TLR systems were inspected via identifying the key residues (named HUB nodes) that control interaction stability and provide a clear molecular mechanism. The obtained results from molecular docking and MD simulation revealed a strong and stable interaction between vaccine and TLRs. The vaccine's ability to stimulate the immune response was assessed by using computational immune simulation. This predicted a significant level of cytotoxic T cell and helper T cell activation, as well as IgG, interleukin 2, and interferon-gamma production. This study shows that the designed vaccine is structurally and dynamically stable and can trigger an effective immune response against viral infections.

Pandemic COVID-19 infections have spread throughout the world. There is no effective treatment against this disease. Viral RNA-dependent RNA polymerase (RdRp) catalyzes the replication of RNA from RNA and the main protease (M^pro) has a role in the processing of polyproteins that are translated from the RNA of SARS-CoV-2, and thus these two enzymes are strong candidates for targeting by anti-viral drugs. Small molecules such as lopinavir and favipiravir significantly inhibit the activity of M^pro and RdRp in vitro. Studies have shown that structurally modified lopinavir, favipiravir, and other similar compounds can inhibit COVID-19 main protease (M^pro) and RNA-dependent RNA polymerase (RdRp). In this study, lopinavir and its structurally similar compounds were chosen to bind the main protease, and favipiravir was chosen to target RNA-dependent RNA polymerase. Molecular docking and the quantitative structure-activity relationships (QSAR) study revealed that the selected candidates have favorable binding affinity but less druggable properties. To improve the druggability, four structural analogues of lopinavir and one structural analogue of favipiravir was designed by structural modification. Molecular interaction analyses have displayed that lopinavir and favipiravir analogues interact with the active site residues of M^pro and RdRp, respectively. Absorption, distribution, metabolism, excretion and toxicity (ADMET) properties, medicinal chemistry profile, and physicochemical features were shown that all structurally modified analogues are less toxic and contain high druggable properties than the selected candidates. Subsequently, 50 ns molecular dynamics simulation of the top four docked complexes demonstrated that CID44271905, a lopinavir analogue, forms the most stable complex with the M^pro. Further MMPBSA analyses using the MD trajectories also confirmed the higher binding affinity of CID44271905 towards M^pro. In summary, this study demonstrates a new way to identify leads for novel anti-viral drugs against COVID-19. Communicated by Ramaswamy H. Sarma

In this work, we report in-depth computational studies of three plausible tautomeric forms, generated through the migration of two acidic protons of the N⁴-hydroxylcytosine fragment, of molnupiravir, which is emerging as an efficient drug to treat COVID-19. The DFT calculations were performed to verify the structure of these tautomers, as well as their electronic and optical properties. Molecular docking was applied to examine the influence of the structures of the keto-oxime, keto-hydroxylamine and hydroxyl-oxime tautomers on a series of the SARS-CoV-2 proteins. These tautomers exhibited the best affinity behavior (−9.90, −7.90, and −9.30 kcal/mol, respectively) towards RdRp-RTR and Nonstructural protein 3 (nsp3_range 207–379-MES).