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Functional group and diversity analysis of BIOFACQUIM: A Mexican natural product database

化学 数据库 生物 计算生物学 计算机科学 生物信息学 药物发现
作者
Norberto Sánchez-Cruz,B. Angélica Pilón-Jiménez,José L. Medina-Franco
出处
期刊:F1000Research [F1000 Research Ltd]
卷期号:8: 2071-2071 被引量:16
标识
DOI:10.12688/f1000research.21540.2
摘要

Background: Natural product databases are important in drug discovery and other research areas. An analysis of its structural content, as well as functional group occurrence, provides a useful overview, as well as a means of comparison with related databases. BIOFACQUIM is an emerging database of natural products characterized and isolated in Mexico. Herein, we discuss the results of a first systematic functional group analysis and global diversity of an updated version of BIOFACQUIM. Methods: BIOFACQUIM was augmented through a literature search and data curation. A structural content analysis of the dataset was performed. This involved a functional group analysis with a novel algorithm to automatically identify all functional groups in a molecule and an assessment of the global diversity using consensus diversity plots. To this end, BIOFACQUIM was compared to two major and large databases: ChEMBL 25, and a herein assembled collection of natural products with 169,839 unique compounds. Results: The structural content analysis showed that 15.7% of compounds and 11.6% of scaffolds present in the current version of BIOFACQUIM have not been reported in the other large reference datasets. It also gave a diversity increase in terms of scaffolds and molecular fingerprints regarding the previous version of the dataset, as well as a higher similarity to the assembled collection of natural products than to ChEMBL 25, in terms of diversity and frequent functional groups. Conclusions: A total of 148 natural products were added to BIOFACQUIM, which meant a diversity increase in terms of scaffolds and fingerprints. Regardless of its relatively small size, there are a significant number of compounds and scaffolds that are not present in the reference datasets, showing that curated databases of natural products, such as BIOFACQUIM, can serve as a starting point to increase the biologically relevant chemical space.
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