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Genet."],"abstract":"<jats:p>Peptide\u2013protein complexes play important roles in multiple diseases such as cardiovascular diseases (CVDs) and metabolic syndrome (MetS). The peptides may be the key molecules in the designing of inhibitors or drug targets. Many Chinese traditional drugs are shown to play various roles in different diseases, and comprehensive analyses should be performed using networks which could offer more information than results generated from a single level. In this study, a network analysis pipeline was designed based on machine learning methods to quantify the effects of peptide\u2013protein complexes as drug targets. Three steps, namely, pathway filter, combined network construction, and biomarker prediction and validation based on peptides, were performed using cinnamon (CA) in CVDs and MetS as a case. Results showed that 17 peptide\u2013protein complexes including six peptides and four proteins were identified as CA targets. The expressions of AKT1, AKT2, and ENOS were tested using qRT-PCR in a mouse model that was constructed. AKT2 was shown to be a CA-indicating biomarker, while E2F1 and ENOS were CA treatment targets. AKT1 was considered a diabetic responsive biomarker because it was down-regulated in diabetic but not related to CA. Taken together, the pipeline could identify new drug targets based on biological function analyses. This may provide a deep understanding of the drugs\u2019 roles in different diseases which may foster the development of peptide\u2013protein complex\u2013based therapeutic approaches.<\/jats:p>","DOI":"10.3389\/fgene.2021.816131","type":"journal-article","created":{"date-parts":[[2021,12,24]],"date-time":"2021-12-24T09:20:03Z","timestamp":1640337603000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Network Analyses Based on Machine Learning Methods to Quantify Effects of Peptide\u2013Protein Complexes as Drug Targets Using Cinnamon in Cardiovascular Diseases and Metabolic Syndrome as a Case Study"],"prefix":"10.3389","volume":"12","author":[{"given":"Yingying","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lili","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yinhe","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Keshen","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Honglei","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2021,12,24]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"e83243","DOI":"10.1371\/journal.pone.0083243","article-title":"Cinnamon Counteracts the Negative Effects of a High Fat\/high Fructose Diet on Behavior, Brain Insulin Signaling and Alzheimer-Associated Changes","volume":"8","author":"Anderson","year":"2013","journal-title":"PLoS One"},{"key":"B2","doi-asserted-by":"publisher","first-page":"101012","DOI":"10.1016\/j.genrep.2020.101012","article-title":"Computationally Predicted SARS-COV-2 Encoded microRNAs Target NFKB, JAK\/STAT and TGFB Signaling Pathways","volume":"22","author":"Aydemir","year":"2021","journal-title":"Gene Rep."},{"key":"B3","doi-asserted-by":"publisher","first-page":"1027","DOI":"10.1016\/j.phymed.2010.03.023","article-title":"Cinnamon Extract Regulates Glucose Transporter and Insulin-Signaling Gene Expression in Mouse Adipocytes","volume":"17","author":"Cao","year":"2010","journal-title":"Phytomedicine"},{"key":"B4","doi-asserted-by":"publisher","first-page":"1188","DOI":"10.1101\/gr.849004","article-title":"WebLogo: A Sequence Logo Generator: Figure 1","volume":"14","author":"Crooks","year":"2004","journal-title":"Genome Res."},{"key":"B5","doi-asserted-by":"publisher","first-page":"e000062","DOI":"10.1161\/HCG.0000000000000062","article-title":"Noncoding RNAs in Cardiovascular Disease: Current Knowledge, Tools and Technologies for Investigation, and Future Directions: A Scientific Statement from the American Heart Association","volume":"13","author":"Das","year":"2020","journal-title":"Circ. 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