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COVID-19, the current global pandemic has caused immense damage to human lives and the global economy. It is instigated by the SARS-CoV-2 virus and there is an immediate need for the identification of effective drugs against this deadly virus. SARS-CoV-2 genome codes for four structural proteins, sixteen non-structural proteins (NSPs) and several accessory proteins for its survival inside the host cells. In the present study, through in silico approaches, we aim to identify compounds that are effective against the four NSPs namely, NSP1, NSP4, NSP6 and NSP13 of SARS-CoV-2. The selection criteria of these four NSP proteins are they are least explored and potential targets. First, we have modeled the 3D structures of these proteins using homology modeling methods. Further, through molecular docking studies, we have screened the FDA-approved compounds against these modeled proteins and reported their docking scores. To gain dynamic insights, molecular dynamics studies have also been carried out for the best scored ligand against the NSPs. This study can further pave way for exposing more number of compounds against these proteins and enhance COVID-19 treatment. Supplementary Information The online version contains supplementary material available at 10.1007/s42485-021-00067-w.

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Novel vaccines are required to effectively combat the epidemic spread of tuberculosis. Using in silico approaches, this study focuses on prediction of potential B cell and T cell binding immunogenic epitopes for 30 putative outer membrane proteins of Mtb. Among these, certain immunodominant epitopes of Rv0172, Rv0295c, Rv1006, Rv2264c, and Rv2525c were found, which are capable of binding B-cell and a maximum number of MHC alleles. The selected immunodominant epitopes were screened for their allergenic and antigenic properties, their percentage identity against the human proteome and their structural properties. Further, the binding efficacy of the immunodominant epitopes of Rv0295c and Rv1006 with HLA-DRB1*04:01 was analyzed using molecular docking and molecular dynamics studies. Hence, the in silico-derived immunogenic peptides (epitopes) could potentially be used for the design of subunit vaccines against tuberculosis.

Antigen85 (Ag85) proteins of Mycobacterium tuberculosis are mycolyl transferases that aid in cell wall biosynthesis. MPT51 (Ag85D) is closely related to Ag85 proteins. We have performed a comparative molecular dynamics (MD) simulation study of Ag85 proteins (Ag85A, Ag85B, and Ag85C) and MPT51. We observe that helix α5, β7-α9 loop, and N-terminal region of helix α9 of Ag85 proteins are mobile, suggestive of lid like movement over the active site. Further, in Ag85B, we observe the proposed scooting mode of the hydrophobic gating residue Phe232. Our simulations also show a similar scooting mode for Phe232 of Ag85A and Trp158 of Ag85C. We also found aromatic residue clusters at the ends of the hydrophobic channel of Ag85 proteins, which may have functional significance. Although MPT51 lacks the tunnel, it has the aromatic clusters. The aromatic cluster region has the ability to bind trehalose. From an immunoinformatics study, a promiscuous linear epitope was identified in MPT51 which could be useful in subunit vaccine studies. Recent studies have shown that a mycobacterial protein HupB, interacts with Ag85 proteins and has a regulatory role in cell wall biogenesis, with implications in growth rate and latency. We performed molecular docking studies of HupB protein with Ag85 proteins and predicted potential sites of interaction in Ag85 proteins. The insights gained through the current study can potentially pave way for newer therapeutic interventions. Graphical Abstract Dynamics of antigen85 proteins and MPT51 from Mycobacterium tuberculosis.