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Systemic Analysis of Antibacterial and Pharmacological Functions of Anisi Stellati Fructus

대회향의 시스템 약리학적 분석과 항균작용

  • Han, Jeong A (School of Korean Medicine, Pusan National University) ;
  • Choo, Ji Eun (School of Korean Medicine, Pusan National University) ;
  • Shon, Jee Won (School of Korean Medicine, Pusan National University) ;
  • Kim, Youn Sook (School of Medicine, Pusan National University) ;
  • Suh, Su Yeon (Okpo Korean Medicine Clinic) ;
  • An, Won Gun (School of Korean Medicine, Pusan National University)
  • 한정아 (부산대학교 한의학전문대학원) ;
  • 추지은 (부산대학교 한의학전문대학원) ;
  • 손지원 (부산대학교 한의학전문대학원) ;
  • 김윤숙 (부산대학교 의학전문대학원 의과학과) ;
  • 서수연 (옥포한의원) ;
  • 안원근 (부산대학교 한의학전문대학원)
  • Received : 2019.01.15
  • Accepted : 2019.02.13
  • Published : 2019.02.28

Abstract

The purpose of this study was to acquire the active compounds of Anisi stellati fructus (ASF) and to analyze the genes and diseases it targets, focusing on its antibacterial effects using a system pharmacological analysis approach. Active compounds of ASF were obtained through the Traditional Chinese Medicine Systems Pharmacology (TCMSP) Database and Analysis Platform. This contains the pharmacokinetic properties of active compounds and related drug-target-disease networks, which is a breakthrough in silico approach possible at the network level. Gene information of targets was gathered from the UnitProt Database, and gene ontology analysis was performed using the David 6.8 Gene Functional Classification Tool. A total of 201 target genes were collected, which corresponded to the nine screened active compounds, and 47 genes were found to act on biological processes related to antimicrobial activity. The representative active compounds involved in antibacterial action were luteolin, kaempferol, and quercetin. Among their targets, Chemokine ligand2, Interleukin-10, Interleukin-6, and Tumor Necrosis Factor were associated with more than three antimicrobial biological processes. This study has provided accurate evidence while saving time and effort to select future laboratory research materials. The data obtained has provided important data for infection prevention and treatment strategies.

시스템 약리학적 분석을 통해 대회향(Anisi Stellati Fructus)의 활성성분 스크리닝, 표적유전자 확보 및 관련 질병과의 네트워크를 구축한 후 대회향의 항균작용을 중점적으로 분석하였다. Traditional Chinese Medicine Systems Pharmacology (TCMSP) Database 와 Analysis Platform을 통해 대회향의 잠재적 활성성분 49개를 확보하였으며, 그 중 설정한 조건에 부합하는 9개 활성성분을 스크리닝 하였다. TCMSP Database는 활성성분의 약물 동태학적 특성 및 약물-표적-질병 간의 관련성을 네트워크 수준에서 파악할 수 있는 획기적인 in silico적 접근을 가능하게 해준다. 활성성분과 반응하는 201개의 유전자 정보를 UniProt database를 통해 확인하고, 취합한 유전자들이 관여하는 348개의 생물학적 과정을 David 6.8 Gene Functional Classification Tool에서 확보하였다. Chemokine ligand 2, Interleukin-10, Interleukin-6, Tumor Necrosis Factor를 포함한 총 47개의 유전자가 항균작용에 관여하였고 이들을 표적으로 하는 luteolin, kaempferol, quercetin 등이 대표적 항균 관련 활성성분이었다. 이와 같이 확보된 데이터는 연구 재료 선정에 정확성과 시간, 노력, 비용 절감의 효과를 제공함과 더불어 추후 실험적 증명으로 이어져 감염병의 예방과 치료 전략에 과학적인 근거를 제시할 수 있을 것이다.

Keywords

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Fig. 1. Workflow: the performance of systems pharmacological network analysis of Anisi Stellati Fructus (ASF), active compounds screening, target fishing, gene ontology analysis, and network constructions.

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Fig. 2. Gene Ontology analysis shows 7 biological processes. The y-axis represents the terms of biological processes, and the x-axis represents counts of target genes ( P value <0.01).

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Fig. 3. The network of Anisi Stellati Fructus,. (A) compound-target network, blue nodes ; active compounds, grey nodes ; target genes. (B) pathway-target network, red nodes ; pathway, grey nodes ; target genes.

Table 1. 9 Active compounds of Anisi Stellati Fructus (OB≧35%, caco-2≧-0.4, DL≧0.10) including additionally added anethole and SKM

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Table 2. Related targets of Anisi Stellati Fructus

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Table 2. Continued

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Table 2. Continued

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Table 2. Continued

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