ArticleJournal of chemical information and modeling2022
Discovery of New Zika Protease and Polymerase Inhibitors through the Open Science Collaboration Project OpenZika.
Article in Journal of chemical information and modeling, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 15 citations in OpenAlex.
- Identification of Sulfonamide-Vinyl Sulfone/Chalcone and Berberine-Cinnamic Acid Hybrids as Potent DENV and ZIKV NS2B/NS3 Allosteric Inhibitors.International journal of molecular sciences · 2025Article
- Article
- Introducing CRAFT: The Center for Research and Advancement in Fragments and molecular Targets.ACS medicinal chemistry letters · 2024Article
- Evaluating Known Zika Virus NS2B-NS3 Protease Inhibitor Scaffolds via In Silico Screening and Biochemical Assays.Pharmaceuticals (Basel, Switzerland) · 2023Article
- The protein disulfide isomerase inhibitor 3-methyltoxoflavin inhibits Chikungunya virus.Bioorganic & medicinal chemistry · 2023Article
- Natural Compounds as Non-Nucleoside Inhibitors of Zika Virus Polymerase through Integration of In Silico and In Vitro Approaches.Pharmaceuticals (Basel, Switzerland) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
21 authors at 8 institutions in 2 countries.
Funding
Abstract
The Zika virus (ZIKV) is a neurotropic arbovirus considered a global threat to public health. Although there have been several efforts in drug discovery projects for ZIKV in recent years, there are still no antiviral drugs approved to date. Here, we describe the results of a global collaborative crowdsourced open science project, the OpenZika project, from IBM's World Community Grid (WCG), which integrates different computational and experimental strategies for advancing a drug candidate for ZIKV. Initially, molecular docking protocols were developed to identify potential inhibitors of ZIKV NS5 RNA-dependent RNA polymerase (NS5 RdRp), NS3 protease (NS2B-NS3pro), and NS3 helicase (NS3hel). Then, a machine learning (ML) model was built to distinguish active vs inactive compounds for the cytoprotective effect against ZIKV infection. We performed three independent target-based virtual screening campaigns (NS5 RdRp, NS2B-NS3pro, and NS3hel), followed by predictions by the ML model and other filters, and prioritized a total of 61 compounds for further testing in enzymatic and phenotypic assays. This yielded five non-nucleoside compounds which showed inhibitory activity against ZIKV NS5 RdRp in enzymatic assays (IC
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.