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A Combined Evidence Approach to Prioritize Nipah Virus Inhibitors

A Combined Evidence Approach to Prioritize Nipah Virus Inhibitors

来源:bioRxiv_logobioRxiv
英文摘要

Abstract Nipah Virus (NiV) came into limelight due to an outbreak in Kerala, India. NiV causes severe disease and death in people with over 75% case fatality rate. It is a public health concern and has the potential to become a global pandemic. Lack of treatment has forced the containment methods to be restricted to isolation and surveillance. WHO’s ‘R&D Blueprint list of priority diseases’ (2018) indicates that there is an urgent need for accelerated research & development for addressing NiV. In the quest for druglike NiV inhibitors (NVIs) a thorough literature search followed by systematic data curation was conducted. Rigorous data analysis was done with curated NVIs for prioritizing druglike compounds. For the same, more than 1800 descriptors of NVIs were computed and comparative analysis was performed with the FDA approved small molecules and antivirals. These compounds were further evaluated through PAINS filter to study their toxicity profile. Simultaneously, compounds were also prioritized based on the robustness of the assays through which they were identified. Our efforts lead to the creation of a well-curated structured knowledgebase of 182 NVIs with 98 small molecule inhibitors. The reported IC50/EC50 values for some of these inhibitors are in the nanomolar range – as low as 0.47 nM. In order to prioritize these inhibitors, we performed several tests and applied filters to identify drug-like non-toxic compounds. Of 98, a few compounds passed DruLito & PAINS filters exhibiting drug-like properties and were also prioritized in an independent screen based only the assay robustness. The NVIs have diverse structural features and offer a wide spectrum of ways in which they can be developed further as druglike molecules. We report a knowledgebase for furthering the development of NVIs. The platform has a diverse set of 98 NVIs of which a few have been prioritized based on a combined evidence strategy. The platform has the provision to submit new inhibitors as and when reported by the community for further enhancement of NiV inhibitor landscape.

Tuteja Kanika、Sharma Tina、Scaria Vinod、Bhardwaj Anshu、Covernton Eugenia、Kumari Nishi、Kalia Kishan、Paul Priyanka Rani、Kumar Rakesh、Upadhyay Ayush

Centre of Systems Biology and Bioinformatics, Panjab UniversityBioinformatics Centre, CSIR-Institute of Microbial Technology||Academy of Scientific and Innovative Research (AcSIR)CSIR Institute of Genomics and Integrative Biology (CSIR-IGIB)Bioinformatics Centre, CSIR-Institute of Microbial Technology||Academy of Scientific and Innovative Research (AcSIR)Centre de recherches interdisciplinairesDepartment of Biotechnology, University Institute of Engineering and Technology, Panjab UniversityDepartment of Biotechnology and Bioinformatics, D.A.V. CollegeDepartment of Biochemistry, University of LucknowBioinformatics Centre, CSIR-Institute of Microbial Technology||Academy of Scientific and Innovative Research (AcSIR)Department of Microbiology, Bhaskaracharya College of Applied Sciences, Delhi University

10.1101/2020.03.12.977918

医药卫生理论医学研究方法药学

Nipah virusdruglike compoundsinhibitorscheminformaticsantiviralscrowdsourcing

Tuteja Kanika,Sharma Tina,Scaria Vinod,Bhardwaj Anshu,Covernton Eugenia,Kumari Nishi,Kalia Kishan,Paul Priyanka Rani,Kumar Rakesh,Upadhyay Ayush.A Combined Evidence Approach to Prioritize Nipah Virus Inhibitors[EB/OL].(2025-03-28)[2025-04-29].https://www.biorxiv.org/content/10.1101/2020.03.12.977918.点此复制

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