{"title":"小檗生物碱的系统分析揭示了它们的功能协同作用和药物潜力。","authors":"Chinenyenwa Fortune Chukwuneme , Samantha Gildenhuys","doi":"10.1016/j.compbiolchem.2025.108698","DOIUrl":null,"url":null,"abstract":"<div><div><em>Berberis</em> species are rich in isoquinoline alkaloids with promising therapeutic properties for various diseases, including SARS-CoV-2. Despite their known medicinal attributes, the potential for combining them at suitable doses remains underexplored. This study investigated the compound–target interactions, functional enrichment, and pharmacokinetic profiles of seven <em>B. vulgaris</em> alkaloids (berberine, palmatine, berberrubine, lambertine, obamegine, berbidine, and berbamine) using an in-silico approach. Compound–target interactions were identified using SwissTargetPrediction. Protein-protein interaction (PPI) networks were constructed using STRING in Cytoscape, and an UpSet plot was generated in Python to visualize overlapping targets and potential synergy. Functional enrichment analysis was performed in DAVID using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, followed by compound-gene-pathway network construction in Cytoscape. Pharmacokinetic profiles of compounds were assessed using ADMET-AI. A total of 42 genes were shared by at least two compounds. Genes associated with neurotransmission (DRD, ADRA, and ADRB) were identified as hubs mediating key functional interactions. Berbamine and obamegine shared the highest number of targets (10). Functional enrichment by KEGG and GO identified 16 and 20 significantly enriched pathways and biological processes, respectively, and formed networks consisting of distinct nodes (pathway = 67, GOBP = 69) and edges (pathway = 228, GOBP = 229). Favorable drug-likeness was identified for all alkaloids, excluding berbamine and obamegine (0.3), and low clinical toxicity (0.0–0.3). The results highlight the therapeutic potential of B. vulgaris alkaloids to provide complementary and synergistic effects across different disease pathways and support their development in botanical medicine.</div></div>","PeriodicalId":10616,"journal":{"name":"Computational Biology and Chemistry","volume":"120 ","pages":"Article 108698"},"PeriodicalIF":3.1000,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Systems analysis of Berberis vulgaris alkaloids unveils their functional synergy and drug-like potential\",\"authors\":\"Chinenyenwa Fortune Chukwuneme , Samantha Gildenhuys\",\"doi\":\"10.1016/j.compbiolchem.2025.108698\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div><em>Berberis</em> species are rich in isoquinoline alkaloids with promising therapeutic properties for various diseases, including SARS-CoV-2. Despite their known medicinal attributes, the potential for combining them at suitable doses remains underexplored. This study investigated the compound–target interactions, functional enrichment, and pharmacokinetic profiles of seven <em>B. vulgaris</em> alkaloids (berberine, palmatine, berberrubine, lambertine, obamegine, berbidine, and berbamine) using an in-silico approach. Compound–target interactions were identified using SwissTargetPrediction. Protein-protein interaction (PPI) networks were constructed using STRING in Cytoscape, and an UpSet plot was generated in Python to visualize overlapping targets and potential synergy. Functional enrichment analysis was performed in DAVID using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, followed by compound-gene-pathway network construction in Cytoscape. Pharmacokinetic profiles of compounds were assessed using ADMET-AI. A total of 42 genes were shared by at least two compounds. Genes associated with neurotransmission (DRD, ADRA, and ADRB) were identified as hubs mediating key functional interactions. Berbamine and obamegine shared the highest number of targets (10). Functional enrichment by KEGG and GO identified 16 and 20 significantly enriched pathways and biological processes, respectively, and formed networks consisting of distinct nodes (pathway = 67, GOBP = 69) and edges (pathway = 228, GOBP = 229). Favorable drug-likeness was identified for all alkaloids, excluding berbamine and obamegine (0.3), and low clinical toxicity (0.0–0.3). The results highlight the therapeutic potential of B. vulgaris alkaloids to provide complementary and synergistic effects across different disease pathways and support their development in botanical medicine.</div></div>\",\"PeriodicalId\":10616,\"journal\":{\"name\":\"Computational Biology and Chemistry\",\"volume\":\"120 \",\"pages\":\"Article 108698\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2025-09-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computational Biology and Chemistry\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1476927125003597\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational Biology and Chemistry","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1476927125003597","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOLOGY","Score":null,"Total":0}
Systems analysis of Berberis vulgaris alkaloids unveils their functional synergy and drug-like potential
Berberis species are rich in isoquinoline alkaloids with promising therapeutic properties for various diseases, including SARS-CoV-2. Despite their known medicinal attributes, the potential for combining them at suitable doses remains underexplored. This study investigated the compound–target interactions, functional enrichment, and pharmacokinetic profiles of seven B. vulgaris alkaloids (berberine, palmatine, berberrubine, lambertine, obamegine, berbidine, and berbamine) using an in-silico approach. Compound–target interactions were identified using SwissTargetPrediction. Protein-protein interaction (PPI) networks were constructed using STRING in Cytoscape, and an UpSet plot was generated in Python to visualize overlapping targets and potential synergy. Functional enrichment analysis was performed in DAVID using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, followed by compound-gene-pathway network construction in Cytoscape. Pharmacokinetic profiles of compounds were assessed using ADMET-AI. A total of 42 genes were shared by at least two compounds. Genes associated with neurotransmission (DRD, ADRA, and ADRB) were identified as hubs mediating key functional interactions. Berbamine and obamegine shared the highest number of targets (10). Functional enrichment by KEGG and GO identified 16 and 20 significantly enriched pathways and biological processes, respectively, and formed networks consisting of distinct nodes (pathway = 67, GOBP = 69) and edges (pathway = 228, GOBP = 229). Favorable drug-likeness was identified for all alkaloids, excluding berbamine and obamegine (0.3), and low clinical toxicity (0.0–0.3). The results highlight the therapeutic potential of B. vulgaris alkaloids to provide complementary and synergistic effects across different disease pathways and support their development in botanical medicine.
期刊介绍:
Computational Biology and Chemistry publishes original research papers and review articles in all areas of computational life sciences. High quality research contributions with a major computational component in the areas of nucleic acid and protein sequence research, molecular evolution, molecular genetics (functional genomics and proteomics), theory and practice of either biology-specific or chemical-biology-specific modeling, and structural biology of nucleic acids and proteins are particularly welcome. Exceptionally high quality research work in bioinformatics, systems biology, ecology, computational pharmacology, metabolism, biomedical engineering, epidemiology, and statistical genetics will also be considered.
Given their inherent uncertainty, protein modeling and molecular docking studies should be thoroughly validated. In the absence of experimental results for validation, the use of molecular dynamics simulations along with detailed free energy calculations, for example, should be used as complementary techniques to support the major conclusions. Submissions of premature modeling exercises without additional biological insights will not be considered.
Review articles will generally be commissioned by the editors and should not be submitted to the journal without explicit invitation. However prospective authors are welcome to send a brief (one to three pages) synopsis, which will be evaluated by the editors.