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Chemists funded by the U.S. National Science Foundation have developed a new process to synthesize a plant-based compound that shows effectiveness against triple-negative breast cancer cells. According to the American Cancer Society, triple-negative breast cancer is one of the most aggressive types of breast cancer and accounts for 10-15% of all breast cancer cases. The process also increases the compound’s potency against these cancer cells and provides a method for it to be mass-produced to enable further testing as a potential treatment.

The new process can also be used broadly to help discover new medicines by synthesizing and testing other complex organic compounds. The findings were achieved by Emory University researchers and published in The Journal of the American Chemical Society.

The compound — called phaeocaulisin A — is extracted from the flowering plant Curcuma phaeocaulis, a relative of ginger and turmeric used for centuries in traditional medicine.

“We not only efficiently replicated a complex natural product, we also improved upon it by turning it into a more potent compound,” says Mingji Dai, professor of chemistry and co-lead of the study.

“It is only the first step in a long process,” says Yong Wan, professor of pharmacology and chemical biology and study co-lead. “But the new analogue of phaeocaulisin A we have reported shows promising efficacy against triple-negative breast cancer cells, which are very aggressive and

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A new computational tool developed with support from the U.S. National Science Foundation could greatly speed up determining the 3D structure of RNAs, a critical step in developing new RNA-based drugs, identifying drug-binding sites and using RNAs in other biotechnology and biomedicine applications.

The tool, NuFold, leverages state-of-the-art machine learning techniques to predict the structure of a wide variety of RNA molecules from their sequences. This new capability will allow researchers to visualize what a given RNA structure could look like based on its sequence and identify its potential use in drug delivery, disease treatment and other applications.  The research leading to NuFold was published in Nature Communications.

RNAs are critical biological molecules — encoding information, like DNA, and performing cellular functions, like proteins — but relatively few RNA structures have been determined through experimentation thus far, which severely limits understanding of their functions. For example, RNAs in the NSF-funded Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) represent only about 3% of total entries. Experimentally determining RNA structures is often time-consuming and costly. By providing a path to reliably predicting RNA structure from sequence, NuFold could greatly expedite the discovery of RNA function and enable quicker development of RNA-based therapeutics and technologies.