The Cannabis Sativa Genetics and Therapeutics Relationship Network: Automatically Associating Cannabis-related Genes to Therapeutic Properties Through Chemicals from Cannabis Literature

Overview

Journal J Cannabis Res

Date 2023 May 30

PMID 37254213

Authors

Trever J Jackson

Sunandan Chakraborty

Affiliations

Soon will be listed here.

Abstract

Background: Understanding the genome of Cannabis sativa holds significant scientific value due to the multi-faceted therapeutic nature of the plant. Links from cannabis gene to therapeutic property are important to establish gene targets for the optimization of specific therapeutic properties through selective breeding of cannabis strains. Our work establishes a resource for quickly obtaining a complete set of therapeutic properties and genes associated with any known cannabis chemical constituent, as well as relevant literature.

Methods: State-of-the-art natural language processing (NLP) was used to automatically extract information from many cannabis-related publications, thus producing an undirected multipartite weighted-edge paragraph co-occurrence relationship network composed of two relationship types, gene-chemical and chemical property. We also developed an interactive application to visualize sub-graphs of manageable size.

Results: Two hundred thirty-four cannabis constituent chemicals, 352 therapeutic properties, and 124 genes from the Cannabis sativa genome form a multipartite network graph which transforms 29,817 cannabis-related research documents from PubMed Central into an easy to visualize and explore network format.

Conclusion: Use of our network replaces time-consuming and labor intensive manual extraction of information from the large amount of available cannabis literature. This streamlined information retrieval process will enhance the activities of cannabis breeders, cannabis researchers, organic biochemists, pharmaceutical researchers and scientists in many other disciplines.

References

Linher-Melville K, Zhu Y, Sidhu J, Parzei N, Shahid A, Seesankar G . Evaluation of the preclinical analgesic efficacy of naturally derived, orally administered oil forms of Δ9-tetrahydrocannabinol (THC), cannabidiol (CBD), and their 1:1 combination. PLoS One. 2020; 15(6):e0234176. PMC: 7272035. DOI: 10.1371/journal.pone.0234176. View

He Y, Zhou C, Yu L, Wang L, Deng J, Tao Y . Natural product derived phytochemicals in managing acute lung injury by multiple mechanisms. Pharmacol Res. 2020; 163:105224. PMC: 7522693. DOI: 10.1016/j.phrs.2020.105224. View

Zhou D, Zhong D, He Y . Event trigger identification for biomedical events extraction using domain knowledge. Bioinformatics. 2014; 30(11):1587-94. DOI: 10.1093/bioinformatics/btu061. View

Pellati F, Brighenti V, Sperlea J, Marchetti L, Bertelli D, Benvenuti S . New Methods for the Comprehensive Analysis of Bioactive Compounds in L. (hemp). Molecules. 2018; 23(10). PMC: 6222702. DOI: 10.3390/molecules23102639. View

Tsuchiya H . Anesthetic Agents of Plant Origin: A Review of Phytochemicals with Anesthetic Activity. Molecules. 2017; 22(8). PMC: 6152143. DOI: 10.3390/molecules22081369. View

Hardy K . Paleomedicine and the Evolutionary Context of Medicinal Plant Use. Rev Bras Farmacogn. 2020; 31(1):1-15. PMC: 7546135. DOI: 10.1007/s43450-020-00107-4. View

Cai S, Zhang Z, Huang S, Bai X, Huang Z, Zhang Y . CannabisGDB: a comprehensive genomic database for Cannabis Sativa L. Plant Biotechnol J. 2021; 19(5):857-859. PMC: 8131054. DOI: 10.1111/pbi.13548. View

Jagannathan R . Identification of Psychoactive Metabolites from , Its Smoke, and Other Phytocannabinoids Using Machine Learning and Multivariate Methods. ACS Omega. 2020; 5(1):281-295. PMC: 6964292. DOI: 10.1021/acsomega.9b02663. View

van Bakel H, Stout J, Cote A, Tallon C, Sharpe A, Hughes T . The draft genome and transcriptome of Cannabis sativa. Genome Biol. 2011; 12(10):R102. PMC: 3359589. DOI: 10.1186/gb-2011-12-10-r102. View

10.

Raj V, Park J, Cho K, Choi P, Kim T, Ham J . Assessment of antiviral potencies of cannabinoids against SARS-CoV-2 using computational and in vitro approaches. Int J Biol Macromol. 2020; 168:474-485. PMC: 7836687. DOI: 10.1016/j.ijbiomac.2020.12.020. View

11.

Zager J, Lange I, Srividya N, Smith A, Lange B . Gene Networks Underlying Cannabinoid and Terpenoid Accumulation in Cannabis. Plant Physiol. 2019; 180(4):1877-1897. PMC: 6670104. DOI: 10.1104/pp.18.01506. View

12.

Rodriguez-Esteban R . Biomedical text mining and its applications. PLoS Comput Biol. 2009; 5(12):e1000597. PMC: 2791166. DOI: 10.1371/journal.pcbi.1000597. View