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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.

The growing use of short-interfering RNA (siRNA)-based therapeutics for viral diseases reflects the most recent innovations in anti-viral vaccines and drugs. These drugs play crucial roles in the fight against many hitherto incurable diseases, the causes, pathophysiologies, and molecular processes of which remain unknown. Targeted liver drug delivery systems are in clinical trials. The receptor-mediated endocytosis approach involving the abundant asialoglycoprotein receptors (ASGPRs) on the surfaces of liver cells show great promise. We here review N -acetylgalactosamine (GalNAc)-siRNA conjugates that treat viral diseases such as hepatitis B infection, but we also mention that novel, native conjugate-based, targeted siRNA anti-viral drugs may also cure several life-threatening diseases such as hemorrhagic cystitis, multifocal leukoencephalopathy, and severe acute respiratory syndrome caused by coronaviruses and human herpes virus.

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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.

M. tuberculosis proliferates within the macrophages during infection and they are bounded by carbohydrates in the cell wall, called lectins. Despite their surface localization, the studies on exact functions of lectins are unexplored. Hence, in our study, using insilico approaches, 11 potential lectins of Mtb was explored as potential drug targets and vaccine candidates. Initially, a gene interaction network was constructed for the 11 potential lectins and identified its functional partners. A gene ontology analysis was also performed for the 11 mycobacterial lectins along with its functional partners and found most of the proteins are present in the extracellular region of the bacterium and belongs to the PE/PPE family of proteins. Further, molecular docking studies were performed for two of the potential lectins (Rv2075c and Rv1917c). A novel series of quinoxalinone and fucoidan derivatives have been made to dock against these selected lectins. Molecular docking study reveals that quinoxalinone derivatives showed better affinity against Rv2075c, whereas fucoidan derivatives have good binding affinity against Rv1917c. Moreover, the mycobacterial lectins can interact with the host and they are considered as potential vaccine candidates. Hence, immunoinformatics study was carried out for all the 11 potential lectins. B-cell and T-cell binding epitopes were predicted using insilico tools. Further, an immunodominant epitope 1062 SIPAIPLSVEV 1072 of Rv1917c was identified, which was predicted to bind B-cell and most of the MHC alleles. Thus, the study has explored that mycobacterial lectins could be potentially used as drug targets and vaccine candidates for tuberculosis treatment.

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