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Hybrid In Silico Approach Reveals Novel Inhibitors of Multiple SARS-CoV-2 Variants.

ABSTRACT: The National Center for Advancing Translational Sciences (NCATS) has been actively generating SARS-CoV-2 high-throughput screening data and disseminates it through the OpenData Portal (https://opendata.ncats.nih.gov/covid19/). Here, we provide a hybrid approach that utilizes NCATS screening data from the SARS-CoV-2 cytopathic effect reduction assay to build predictive models, using both machine learning and pharmacophore-based modeling. Optimized models were used to perform two iterative rounds of virtual screening to predict small molecules active against SARS-CoV-2. Experimental testing with live virus provided 100 (∼16% of predicted hits) active compounds (efficacy > 30%, IC₅₀ ≤ 15 μM). Systematic clustering analysis of active compounds revealed three promising chemotypes which have not been previously identified as inhibitors of SARS-CoV-2 infection. Further investigation resulted in the identification of allosteric binders to host receptor angiotensin-converting enzyme 2; these compounds were then shown to inhibit the entry of pseudoparticles bearing spike protein of wild-type SARS-CoV-2, as well as South African B.1.351 and UK B.1.1.7 variants.

SUBMITTER: Jain S

PROVIDER: S-EPMC8482323 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

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Hybrid <i>In Silico</i> Approach Reveals Novel Inhibitors of Multiple SARS-CoV-2 Variants.

Jain Sankalp S Talley Daniel C DC Baljinnyam Bolormaa B Choe Jun J Hanson Quinlin Q Zhu Wei W Xu Miao M Chen Catherine Z CZ Zheng Wei W Hu Xin X Shen Min M Rai Ganesha G Hall Matthew D MD Simeonov Anton A Zakharov Alexey V AV

ACS pharmacology & translational science 20210917 5

The National Center for Advancing Translational Sciences (NCATS) has been actively generating SARS-CoV-2 high-throughput screening data and disseminates it through the OpenData Portal (https://opendata.ncats.nih.gov/covid19/). Here, we provide a hybrid approach that utilizes NCATS screening data from the SARS-CoV-2 cytopathic effect reduction assay to build predictive models, using both machine learning and pharmacophore-based modeling. Optimized models were used to perform two iterative rounds ...[more]

PMID: 34608449

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Project description:The world has faced unprecedented disruptions like global quarantine and the COVID-19 pandemic due to SARS-CoV-2. To combat these unsettling situations, several effective vaccines have been developed and are currently being used. However, the emergence of new variants due to the high mutation rate of SARS-CoV-2 challenges the efficacy of existing vaccines and has highlighted the need for novel vaccines that will be effective against various SARS-CoV-2 variants. In this study, we exploited the four structural proteins of SARS-CoV-2 to execute a potential multi-epitope vaccine against SARS-CoV-2 and its variants. The vaccine was designed by utilizing the antigenic, non-toxic, and non-allergenic B-cell and T-cell epitopes, which were selected from conserved regions of viral proteins. To build a vaccine construct, epitopes were connected through different linkers and an adjuvant was also attached at the start of the construct to enhance the immunogenicity and specificity of the epitopes. The vaccine construct was then screened through the aforementioned filters and it scored 0.6019 against the threshold of 0.4 on VexiJen 2.0 which validates its antigenicity. Toll-like receptors (i.e., TLR2, TLR3, TLR4, TLR5, and TLR8) and vaccine construct were docked by Cluspro 2.0, and TLR8 showed strong interaction with construct having a maximum negative binding energy of - 1577.1 kCal/mole. C-IMMSIM's immune simulations over three doses of the vaccine and iMODS' molecular dynamic simulations were executed to assess the reliability of the docked complexes. The stability of the vaccine construct was evaluated through the physicochemical analyses and the findings suggested that the manufactured vaccine is stable under a wide range of circumstances and can trigger immune responses against various SARS-CoV-2 variants (due to conserved epitopes). However, to strengthen the formulation of the vaccine and assess its safety and effectiveness, additional investigations and studies are required to support the computational data of this research at in-vitro and in-vivo levels.Supplementary informationThe online version contains supplementary material available at 10.1007/s40203-023-00156-2.

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Hybrid In Silico Approach Reveals Novel Inhibitors of Multiple SARS-CoV-2 Variants.

Publications

Hybrid <i>In Silico</i> Approach Reveals Novel Inhibitors of Multiple SARS-CoV-2 Variants.

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