Developing a Knowledge Graph Framework for Pharmacokinetic Natural Product-Drug Interactions

• Main Authors: Taneja, Sanya B, Callahan, Tiffany J, Paine, Mary F, Kane-Gill, Sandra L, Kilicoglu, Halil, Joachimiak, Marcin P, Boyce, Richard D
• Format: Journal Article
• Language: English
• Published: 24-09-2022
• Subjects: Computer Science - Artificial Intelligence; Quantitative Biology - Quantitative Methods
• DOI: 10.48550/arxiv.2209.11950

Journal of Biomedical Informatics 140 (2023) 104341 Pharmacokinetic natural product-drug interactions (NPDIs) occur when
botanical natural products are co-consumed with pharmaceutical drugs.
Understanding mechanisms of NPDIs is key to preventing adverse events. We
constructed a knowledge graph framework, NP-KG, as a step toward computational
discovery of pharmacokinetic NPDIs. NP-KG is a heterogeneous KG with biomedical
ontologies, linked data, and full texts of the scientific literature,
constructed with the Phenotype Knowledge Translator framework and the semantic
relation extraction systems, SemRep and Integrated Network and Dynamic
Reasoning Assembler. NP-KG was evaluated with case studies of pharmacokinetic
green tea- and kratom-drug interactions through path searches and meta-path
discovery to determine congruent and contradictory information compared to
ground truth data. The fully integrated NP-KG consisted of 745,512 nodes and
7,249,576 edges. Evaluation of NP-KG resulted in congruent (38.98% for green
tea, 50% for kratom), contradictory (15.25% for green tea, 21.43% for kratom),
and both congruent and contradictory (15.25% for green tea, 21.43% for kratom)
information. Potential pharmacokinetic mechanisms for several purported NPDIs,
including the green tea-raloxifene, green tea-nadolol, kratom-midazolam,
kratom-quetiapine, and kratom-venlafaxine interactions were congruent with the
published literature. NP-KG is the first KG to integrate biomedical ontologies
with full texts of the scientific literature focused on natural products. We
demonstrate the application of NP-KG to identify pharmacokinetic interactions
involving enzymes, transporters, and pharmaceutical drugs. We envision that
NP-KG will facilitate improved human-machine collaboration to guide researchers
in future studies of pharmacokinetic NPDIs. The NP-KG framework is publicly
available at https://doi.org/10.5281/zenodo.6814507 and
https://github.com/sanyabt/np-kg.