Active site-based analysis of structural proteins for drug targets in different human Coronaviruses.

Seven types of Coronaviruses (CoVs) have been identified that can cause infection in humans, including HCoV-229E, HCoV-NL63, HCoV-OC43, HCoV-HKU1, SARS-CoV, HCoV-MERS, and SARS-CoV-2. In this study, we investigated the genetic structure, the homology of the structural protein sequences, as well as the investigation of the active site of structural proteins. The active site of structural proteins was determined based on the previous studies, and the homology of their amino acid sequences and structure was compared. Multiple sequence alignment of Spike protein of HCoVs showed that the receptor-binding domain of SARS-CoV-2, SARS-CoV, and MERS-CoV was located at a similar site to the S1 subunit. The binding motif of PDZ (postsynaptic density-95/disks large/zona occludens-1) of the envelope protein, was conserved in SARS-CoV and SARS-CoV-2 according to multiple sequence alignment but showed different changes in the other HCoVs. Overall, spike protein showed the most variation in its active sites, but the other structural proteins were highly conserved. In this study, for the first time, the active site of all structural proteins of HCoVs as a drug target was investigated. The binding site of these proteins can be suitable targets for drugs or vaccines among HCoVs.

Reverse vaccinology approach to design a novel multi-epitope vaccine candidate against COVID-19: an in silico study.

At present, novel Coronavirus (2019-nCoV, the causative agent of COVID-19) has caused worldwide social and economic disruption. The disturbing statistics of this infection promoted us to develop an effective vaccine candidate against the COVID-19. In this study, bioinformatics approaches were employed to design and introduce a novel multi-epitope vaccine against 2019-nCoV that can potentially trigger both CD4+ and CD8+ T-cell immune responses and investigated its biological activities by computational tools. Three known antigenic proteins (Nucleocapsid, ORF3a, and Membrane protein, hereafter called NOM) from the virus were selected and analyzed for prediction of the potential immunogenic B and T-cell epitopes and then validated using bioinformatics tools. Based on in silico analysis, we have constructed a multi-epitope vaccine candidate (NOM) with five rich-epitopes domain including highly scored T and B-cell epitopes. After predicting and evaluating of the third structure of the protein candidate, the best 3 D predicted model was applied for docking studies with Toll-like receptor 4 (TLR4) and HLA-A*11:01. In the next step, molecular dynamics (MD) simulation was used to evaluate the stability of the designed fusion protein with TLR4 and HLA-A*11:01 receptors. MD studies demonstrated that the NOM-TLR4 and NOM-HLA-A*11:01 docked models were stable during simulation time. In silico evaluation showed that the designed chimeric protein could simultaneously elicit humoral and cell-mediated immune responses. Communicated by Ramaswamy H. Sarma.