Compound databases of natural products have a major impact on drug discovery projects and other areas of research. The number of databases in the public domain with compounds with natural origins is increasing. Several countries, Brazil, France, Panama and, recently, Vietnam, have initiatives in place to construct and maintain compound databases that are representative of their diversity. In this proof-of-concept study, we discuss the first version of BIOFACQUIM, a novel compound database with natural products isolated and characterized in Mexico. We discuss its construction, curation, and a complete chemoinformatic characterization of the content and coverage in chemical space. The profile of physicochemical properties, scaffold content, and diversity, as well as structural diversity based on molecular fingerprints is reported. BIOFACQUIM is available for free.

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.

Background: Natural product databases are important in drug discovery and other research areas. Their structural contents and functional group analysis are relevant to increase their knowledge in terms of chemical diversity and chemical space coverage. 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 done. This involved a functional group analysis with a novel algorithm to identify automatically 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 16.1% of compounds, 11.3% of scaffolds, and 6.3% of functional groups 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, scaffolds, and functional groups 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.

Scaffold analysis of compound data sets has reemerged as a chemically interpretable alternative to machine learning for chemical space and structure–activity relationships analysis. In this context, analog series-based scaffolds (ASBS) are synthetically relevant core structures that represent individual series of analogs. As an extension to ASBS, we herein introduce the development of a general conceptual framework that considers all putative cores of molecules in a compound data set, thus softening the often applied “single molecule–single scaffold” correspondence. A putative core is here defined as any substructure of a molecule complying with two basic rules: (a) the size of the core is a significant proportion of the whole molecule size and (b) the substructure can be reached from the original molecule through a succession of retrosynthesis rules. Thereafter, a bipartite network consisting of molecules and cores can be constructed for a database of chemical structures. Compounds linked to the same cores are considered analogs. We present case studies illustrating the potential of the general framework. The applications range from inter- and intra-core diversity analysis of compound data sets, structure–property relationships, and identification of analog series and ASBS. The molecule–core network herein presented is a general methodology with multiple applications in scaffold analysis. New statistical methods are envisioned that will be able to draw quantitative conclusions from these data. The code to use the method presented in this work is freely available as an additional file. Follow-up applications include analog searching and core structure–property relationships analyses.

Compound databases of natural products have a major impact on drug discovery projects and other areas of research. The number of databases in the public domain with compounds from natural origin is increasing. Several countries have initiatives in place to construct and maintain compound databases that are representative of their diversity. Examples are Brazil, France, Panama and recently Vietnam. Herein, we discuss the first version of BIOFACQUIM, a novel compound database with natural products isolated and characterized in Mexico. We discuss its construction, curation, and a complete chemoinformatic characterization of the content and coverage in chemical space. It is reported the profile of physicochemical properties, scaffold content, and diversity, as well as structural diversity based on molecular fingerprints. BIOFACQUIM is freely available.

Naturally occurring small molecules include a large variety of natural products from different sources that have confirmed activity against epigenetic targets. In this work we review chemoinformatic, molecular modeling and other computational approaches that have been used to uncover natural products as inhibitors of DNA metiltransferases, a major family of epigenetic targets with significant potential for the treatment of cancer and several other diseases. Examples of these computational approaches include docking, similarity-based virtual screening, and pharmacophore modeling. It is also commented the chemoinformatic-based exploration of the chemical space of naturally occurring compounds as epigenetic modulators which may have significant implications in epigenetic drug discovery and nutriepigenetics.