Data Base similarity (DBsimilarity) of natural products to aid compound identification on MS and NMR pipelines, similarity networking, and more

化学信息学 相似性(几何) 数据库 化学 计算机科学 化学 化学相似性 数据挖掘 情报检索 结构相似性 药物发现 人工智能 生物化学 图像(数学) 计算化学
作者
Ricardo M. Borges,Gabriela de Assis Ferreira,Mariana Martins Campos,Andrew Magno Teixeira,Fernanda das Neves Costa,Fernanda O. Chagas
出处
期刊:Phytochemical Analysis [Wiley]
卷期号:35 (1): 93-101 被引量:5
标识
DOI:10.1002/pca.3277
摘要

Abstract Introduction We developed Data Base similarity (DBsimilarity), a user‐friendly tool designed to organize structure databases into similarity networks, with the goal of facilitating the visualization of information primarily for natural product chemists who may not have coding experience. Method DBsimilarity, written in Jupyter Notebooks, converts Structure Data File (SDF) files into Comma‐Separated Values (CSV) files, adds chemoinformatics data, constructs an MZMine custom database file and an NMRfilter candidate list of compounds for rapid dereplication of MS and 2D NMR data, calculates similarities between compounds, and constructs CSV files formatted into similarity networks for Cytoscape. Results The Lotus database was used as a source for Ginkgo biloba compounds, and DBsimilarity was used to create similarity networks including NPClassifier classification to indicate biosynthesis pathways. Subsequently, a database of validated antibiotics from natural products was combined with the G. biloba compounds to identify promising compounds. The presence of 11 compounds in both datasets points to possible antibiotic properties of G. biloba , and 122 compounds similar to these known antibiotics were highlighted. Next, DBsimilarity was used to filter the NPAtlas database (selecting only those with MIBiG reference) to identify potential antibacterial compounds using the ChEMBL database as a reference. It was possible to promptly identify five compounds found in both databases and 167 others worthy of further investigation. Conclusion Chemical and biological properties are determined by molecular structures. DBsimilarity enables the creation of interactive similarity networks using Cytoscape. It is also in line with a recent review that highlights poor biological plausibility and unrealistic chromatographic behaviors as significant sources of errors in compound identification.
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