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Design and application of a knowledge network for automatic prioritization of drug mechanisms
- Source :
- Bioinformatics
- Publication Year :
- 2022
- Publisher :
- Oxford University Press (OUP), 2022.
-
Abstract
- Motivation Drug repositioning is an attractive alternative to de novo drug discovery due to reduced time and costs to bring drugs to market. Computational repositioning methods, particularly non-black-box methods that can account for and predict a drug’s mechanism, may provide great benefit for directing future development. By tuning both data and algorithm to utilize relationships important to drug mechanisms, a computational repositioning algorithm can be trained to both predict and explain mechanistically novel indications. Results In this work, we examined the 123 curated drug mechanism paths found in the drug mechanism database (DrugMechDB) and after identifying the most important relationships, we integrated 18 data sources to produce a heterogeneous knowledge graph, MechRepoNet, capable of capturing the information in these paths. We applied the Rephetio repurposing algorithm to MechRepoNet using only a subset of relationships known to be mechanistic in nature and found adequate predictive ability on an evaluation set with AUROC value of 0.83. The resulting repurposing model allowed us to prioritize paths in our knowledge graph to produce a predicted treatment mechanism. We found that DrugMechDB paths, when present in the network were rated highly among predicted mechanisms. We then demonstrated MechRepoNet’s ability to use mechanistic insight to identify a drug’s mechanistic target, with a mean reciprocal rank of 0.525 on a test set of known drug–target interactions. Finally, we walked through repurposing examples of the anti-cancer drug imatinib for use in the treatment of asthma, and metolazone for use in the treatment of osteoporosis, to demonstrate this method’s utility in providing mechanistic insight into repurposing predictions it provides. Availability and implementation The Python code to reproduce the entirety of this analysis is available at: https://github.com/SuLab/MechRepoNet (archived at https://doi.org/10.5281/zenodo.6456335). Supplementary information Supplementary data are available at Bioinformatics online.
- Subjects :
- Statistics and Probability
Databases, Pharmaceutical
Computer science
Machine learning
computer.software_genre
Biochemistry
Code (cryptography)
Mean reciprocal rank
Set (psychology)
Molecular Biology
Repurposing
computer.programming_language
Drug discovery
business.industry
Drug Repositioning
Python (programming language)
Original Papers
Computer Science Applications
Drug repositioning
Computational Mathematics
Computational Theory and Mathematics
Test set
Artificial intelligence
business
computer
Algorithms
Subjects
Details
- ISSN :
- 13674811 and 13674803
- Volume :
- 38
- Database :
- OpenAIRE
- Journal :
- Bioinformatics
- Accession number :
- edsair.doi.dedup.....bea2a77382b247570a75fa39b3807fc6