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Anisotine and amarogentin as promising inhibitory candidates against SARS-CoV-2 proteins: a computational investigation.

ABSTRACT: The coronavirus disease 2019 (COVID-19) pandemic, caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), presents an unprecedented challenge to global public health with researchers striving to find a possible therapeutic candidate that could limit the spread of the virus. In this context, the present study employed an in silico molecular interaction-based approach to estimate the inhibitory potential of the phytochemicals from ethnomedicinally relevant Indian plants including Justicia adhatoda, Ocimum sanctum and Swertia chirata, with reported antiviral activities against crucial SARS-CoV-2 proteins. SARS-CoV-2 proteins associated with host attachment and viral replication namely, spike protein, main protease enzyme M^pro and RNA-dependent RNA polymerase (RdRp) are promising druggable targets for COVID-19 therapeutic research. Extensive molecular docking of the phytocompounds at the binding pockets of the viral proteins revealed their promising inhibitory potential. Subsequent assessment of physicochemical features and potential toxicity of the compounds followed by robust molecular dynamics simulations and analysis of MM-PBSA energy scoring function revealed anisotine against SARS-CoV-2 spike and M^pro proteins and amarogentin against SARS-CoV-2 RdRp as potential inhibitors. It was interesting to note that these compounds displayed significantly higher binding energy scores against the respective SARS-CoV-2 proteins compared to the relevant drugs that are currently being targeted against them. Present research findings confer scopes to explore further the potential of these compounds in vitro and in vivo towards deployment as efficient SARS-CoV-2 inhibitors and development of novel effective therapeutics. Communicated by Ramaswamy H. Sarma.

SUBMITTER: Kar P

PROVIDER: S-EPMC7808002 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThe present pandemic COVID-19 is caused by SARS-CoV-2, a single-stranded positive-sense RNA virus from the Coronaviridae family. Due to a lack of antiviral drugs, vaccines against the virus are urgently required.MethodsIn this study, validated computational approaches were used to identify peptide-based epitopes from six structural proteins having antigenic properties. The Net-CTL 1.2 tool was used for the prediction of CD8+ T-cell epitopes, while the robust tools Bepi-Pred 2 and LBtope was employed for the identification of linear B-cell epitopes. Docking studies of the identified epitopes were performed using HADDOCK 2.4 and the structures were visualized by Discovery Studio and LigPlot+. Antigenicity, immunogenicity, conservancy, population coverage and allergenicity of the predicted epitopes were determined by the bioinformatics tools like VaxiJen v2.0 server, the Immune Epitope Database tools and AllerTOP v.2.0, AllergenFP 1.0 and ElliPro.ResultsThe predicted T cell and linear B-cell epitopes were considered as prime vaccine targets in case they passed the requisite parameters like antigenicity, immunogenicity, conservancy, non-allergenicity and broad range of population coverage. Among the predicted CD8+ T cell epitopes, potential vaccine targets from surface glycoprotein were; YQPYRVVVL, PYRVVVLSF, GVYFASTEK, QLTPTWRVY, and those from ORF3a protein were LKKRWQLAL, HVTFFIYNK. Similarly, RFLYIIKLI, LTWICLLQF from membrane protein and three epitopes viz; SPRWYFYYL, TWLTYTGAI, KTFPPTEPK from nucleocapsid phosphoprotein were the superior vaccine targets observed in our study. The negative values of HADDOCK and Z scores obtained for the best cluster indicated the potential of the epitopes as suitable vaccine candidates. Analysis of the 3D and 2D interaction diagrams of best cluster produced by HADDOCK 2.4 displayed the binding interaction of leading T cell epitopes within the MHC-1 peptide binding clefts. On the other hand, among linear B cell epitopes the majority of potential vaccine targets were from nucleocapsid protein, viz; 59-HGKEDLKFPRGQGVPINTNSSPDDQIGYYRRATRRIRGGDGKMKDLS-105, 227-LNQLE SKMSGKGQQQQGQTVTKKSAAEASKKPRQKRTATK-266, 3-DNGPQNQRNAPRITFGGP-20, 29-GERSGARSKQRRPQGL-45. Two other prime vaccine targets, 370-NSASFSTFKCYGVSPTKLNDLCFTNV-395 and 260-AGAAAYYVGYLQPRT-274 were identified in the spike protein. The potential B-cell conformational epitopes were predicted on the basis of a higher protrusion index indicating greater solvent accessibility. These conformational epitopes were of various lengths and belonged to spike, ORF3a, membrane and nucleocapsid proteins.ConclusionsTaken together, eleven T cell epitopes, seven B cell linear epitopes and ten B cell conformational epitopes were identified from five structural proteins of SARS-CoV-2 using advanced computational tools. These potential vaccine candidates may provide important timely directives for an effective vaccine against SARS-CoV-2.

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Anisotine and amarogentin as promising inhibitory candidates against SARS-CoV-2 proteins: a computational investigation.

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