Rationally minimizing natural product libraries using mass spectrometry.

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Tác giả: Debopam Chakrabarti, Robert H Cichewicz, Jennifer E Collins, Jarrod B King, Laura-Isobel McCall, Cameron R Miller, Monica Ness, Crystal Okeke, Raphaella Paes, Thilini Peramuna, Natalia Mojica Santos, Karen L Wendt

Ngôn ngữ: eng

Ký hiệu phân loại:

Thông tin xuất bản: United States : mSystems , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 676198

UNLABELLED: Natural products are a critical source of novel chemotypes for drug discovery. However, the implementation of natural product extract libraries in high throughput screening is hampered by natural product structural redundancy and potential for bioactive re-discovery. This challenge and large library sizes drastically increase the time and cost during initial high throughput screens. To address these limitations, we developed a method that leverages liquid chromatography-tandem mass spectrometry spectral similarity to dramatically reduce natural product library size, with minimal bioactive loss, and applied this to a collection of fungal extracts. Importantly, this method also afforded increased bioassay hit rates against microbial targets, with broad applicability across assays and natural product sources. Thus, this method offers a broadly applicable strategy for accelerated and cost-effective natural product drug discovery. IMPORTANCE: Natural product libraries are large collections of extracts derived from fungi, plants, bacteria, or any other natural sources. These libraries play an important role in the initial phases of drug discovery, providing the basis for bioassays against a target of interest. However, these collections often comprise thousands of extracts with sometimes overlapping chemical structures, which can result in a bottleneck in both time and costs for the initial phases of drug discovery. Here, we have developed a method that uses mass spectrometry to dramatically reduce the size of these libraries, with minimal tradeoffs and improved success rates in bioassays. Ultimately, this will speed up the process of bioactive candidate identification and isolation, and drug development overall.
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