通过分子社区网络,在非目标代谢学中排序分子多样性
Elizabeth A Coler1, Alexey Melnik1,2, Ali Lotfi1
1Department of Chemistry, University of Connecticut, Storrs, CT, USA.
bioRxiv : the preprint server for biology
|August 12, 2024
概括
分子网络揭示了代谢物之间的隐藏联系. 一种新的方法,分子社区网络 (MCN),改善了代谢物家族的发现,并识别了像二联结胆酸这样的新型化合物.
科学领域:
- 代谢学和化学信息学
- 计算生物学是一种计算生物学.
- 自然产品的发现自然产品的发现.
背景情况:
- 生物分子表现出复杂的组织,而不是随机的多样性.
- 分子网络通过结构相似性将代谢物联系在一起,有助于从质谱数据中发现.
- 现有的方法使用固定的相似度值,可能使自然代谢物家族分裂.
研究的目的:
- 为优化代谢物连接引入分子社区网络 (MCN).
- 在分子网络中克服任意相似度值的局限性.
- 揭示以前"隐藏"的代谢物关系,并增强天然产品的发现.
主要方法:
- 分子社区网络 (MCN) 算法的开发和应用.
- 分析质谱数据以确定代谢物关系.
- 优化单个代谢物的连接值.
主要成果:
- MCN成功地挽救了结构相似的代谢物之间的丢失关系.
- 该方法捕获以前未被检测到的"隐藏"代谢物连接.
- 使用MCN发现了新的二酸结合胆酸.
结论:
- 分子社区网络 (MCN) 提供了一种更强大的方法来分析分子网络.
- 通过保持代谢物家族的完整性,MCN增强了天然产品的发现.
- 这种方法有助于识别新生物活性化合物.
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