Hidden plant molecules show up to 25 times stronger activity against Ebola and COVID-19

Scientists at the Université de Montréal's affiliated Montreal Clinical Research Institute have identified a new family of natural molecules with strong antiviral activity, notably against the Ebola virus and SARS-CoV-2, the virus. The science-journalism coverage adds useful context, while the strongest evidential footing still comes from the underlying data, papers or institutional documentation.

The significance lies in chemistry gains force when a claimed structure or process can be described with enough precision to be reproduced by others. Synthetic routes, spectroscopic signatures, yield under defined conditions and stability under realistic operating parameters are the currency of credibility in chemistry, and a result that lacks these details cannot be evaluated independently. The distance between a discovery on a laboratory bench and a process that works reliably at scale is measured in years of optimization, and each step reveals constraints that were invisible at smaller scale. Scientists at the Université de Montréal's affiliated Montreal Clinical Research Institute (IRCM) have identified a new family of natural molecules with strong antiviral activity. This article has been reviewed according to Science X's editorial process and policies.

Editors have highlighted the following attributes while ensuring the content's credibility: Add as preferred source Journal of Natural Products (2026). Journal of Natural Products (2026).

The discovery comes at a time of renewed fears of the rapid emergence of new pandemics, and highlights the ongoing search at the IRCM for novel antiviral agents derived from. Led by UdeM emeritus medical professor Michel Chrétien and Majambu Mbikay of the IRCM's functional endoproteolysis laboratory, the development is detailed in a study published in.

As early as 2016, and again in 2020, IRCM researchers demonstrated that a plant extract rich in isoquercitrin, a flavonoid found in many plants, exhibited strong antiviral. To resolve this puzzle, Mbikay and his research assistant Annie Roy went looking for the proverbial "needle in the haystack," an effort that required nearly 30 months of intensive.

The broader interest lies in whether the claimed property or reaction pathway can be characterized with enough precision to support replication by other groups. Chemistry has a replication problem that is less discussed than the one in psychology or medicine, but it is real: synthetic procedures that work reliably in one laboratory sometimes fail to transfer, for reasons ranging from impure starting materials to undocumented temperature sensitivities. A result that comes with full experimental detail and a clear characterization of the product is far more valuable than one that reports a discovery without the procedural backbone.

Though present at only 0.4% of the analyzed extract, these newly identified molecules, named dicitriosides, proved to be up to 25 times more active than the original extract. This discovery illustrates how compounds present in vanishingly small amounts in nature can have major therapeutic potential," said Mbikay.

Because this item comes through Phys. org Chemistry as science journalism, it should be treated as contextual reporting rather than primary evidence. Good science reporting can identify why a result matters, connect it to the wider literature and make technical work readable, but the decisive evidence remains in the original paper, dataset, mission release or technical record. That distinction is especially important when a story is later repeated by aggregators, because repetition increases visibility, not evidential strength.

The next step is to see whether independent groups working with orthogonal techniques reach compatible conclusions, and whether the result scales beyond the conditions used in the original study. Chemical discoveries that matter tend to be ones whose key properties can be measured by multiple spectroscopic, crystallographic or computational methods that are unlikely to share the same blind spots. Scalability, cost and long-term stability under realistic operating conditions are additional filters that come into play before any practical application becomes viable.

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