Predicting biological pathways of chemical compounds with a profile-inspired approach

Assignment of chemical compounds to biological pathways is a crucial step to understand the relationship between the chemical repertory of an organism and its biology. Protein sequence profiles are very successful in capturing the main structural and functional features of a protein family, and can...

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Bibliographic Details
Published in:BMC bioinformatics 2021-06, Vol.22 (1), p.320-14, Article 320
Main Authors: Lopez-Ibañez, Javier, Pazos, Florencio, Chagoyen, Monica
Format: Article
Language:English
Subjects:
Amino Acid Sequence
Cells
Chemical compounds
Databases, Factual
Internet
Machine learning
Metabolism
Metabolites
Methodology
Methods
Proteins
Representations
Software
Structure
Structure-function relationships
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Summary:Assignment of chemical compounds to biological pathways is a crucial step to understand the relationship between the chemical repertory of an organism and its biology. Protein sequence profiles are very successful in capturing the main structural and functional features of a protein family, and can be used to assign new members to it based on matching of their sequences against these profiles. In this work, we extend this idea to chemical compounds, constructing a profile-inspired model for a set of related metabolites (those in the same biological pathway), based on a fragment-based vectorial representation of their chemical structures. We use this representation to predict the biological pathway of a chemical compound with good overall accuracy (AUC 0.74-0.90 depending on the database tested), and analyzed some factors that affect performance. The approach, which is compared with equivalent methods, can in addition detect those molecular fragments characteristic of a pathway. The method is available as a graphical interactive web server http://csbg.cnb.csic.es/iFragMent .
ISSN:1471-2105
1471-2105
DOI:10.1186/s12859-021-04252-y