Drug target identification in sphingolipid metabolism by computational systems biology tools: Metabolic control analysis and metabolic pathway analysis

被引:13
|
作者
Ozbayraktar, F. Betuel Kavun [1 ]
Ulgen, Kutlu O. [1 ]
机构
[1] Bogazici Univ, Dept Chem Engn, TR-34342 Istanbul, Turkey
关键词
Sphingolipid metabolism; Ceramide; Cancer; Systems biology; Metabolic control analysis; Metabolic pathway analysis; STEADY-STATE TREATMENT; SACCHAROMYCES-CEREVISIAE; PROSTATE-CANCER; BIOCHEMICAL NETWORKS; ENZYMATIC CHAINS; FLUX MODES; CERAMIDE; CELLS; APOPTOSIS; RECONSTRUCTION;
D O I
10.1016/j.jbi.2010.03.006
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Sphingolipids regulate cellular processes that are critically important in cell's fate and function in cancer development and progression. This fact underlies the basics of the novel cancer therapy approach. The pharmacological manipulation of the sphingolipid metabolism in cancer therapeutics necessitates the detailed understanding of the pathway. Two computational systems biology tools are used to identify potential drug target enzymes among sphingolipid pathway that can be further utilized in drug design studies for cancer therapy. The enzymes in sphingolipid pathway were ranked according to their roles in controlling the metabolic network by metabolic control analysis. The physiologically connected reactions, i.e. biologically significant and functional modules of network, were identified by metabolic pathway analysis. The final set of candidate drug target enzymes are selected such that their manipulation leads to ceramide accumulation and long chain base phosphates depletion. The mathematical tools' efficiency for drug target identification performed in this study is validated by clinically available drugs. (C) 2010 Elsevier Inc. All rights reserved.
引用
收藏
页码:537 / 549
页数:13
相关论文
共 50 条
  • [11] Drug Target Identification Based on Flux Balance Analysis of Metabolic Networks
    Li, Zhenping
    Wang, Rui-Sheng
    Zhang, Xiang-Sun
    COMPUTATIONAL SYSTEMS BIOLOGY, 2010, 13 : 331 - +
  • [12] Metabolic control analysis of the Trypanosoma cruzi peroxide detoxification pathway identifies tryparedoxin as a suitable drug target
    Gonzalez-Chavez, Zabdi
    Olin-Sandoval, Viridiana
    Salud Rodiguez-Zavala, Jose
    Moreno-Sanchez, Rafael
    Saavedra, Emma
    BIOCHIMICA ET BIOPHYSICA ACTA-GENERAL SUBJECTS, 2015, 1850 (02): : 263 - 273
  • [13] CONTROL ANALYSIS OF METABOLIC SYSTEMS
    BURNS, JA
    CORNISHBOWDEN, A
    GROEN, AK
    HEINRICH, R
    KACSER, H
    PORTEOUS, JW
    RAPOPORT, SM
    RAPOPORT, TA
    STUCKI, JW
    TAGER, JM
    WANDERS, RJA
    WESTERHOFF, HV
    TRENDS IN BIOCHEMICAL SCIENCES, 1985, 10 (01) : 16 - 16
  • [14] Computational Systems Biology Models for the Identification of Metabolic Vulnerabilities in Multiple Myeloma
    Valcarcel, Luis Vitores V.
    Ordonez, Raquel
    Apaolaza, Inigo
    Valcarcel, Ana
    Garate, Leire
    Meydan, Cem
    Paiva, Bruno
    Melnick, Ari M.
    San-Miguel, Jesus
    Planes, Francisco J.
    Agirre, Xabier
    Prosper, Felipe
    BLOOD, 2019, 134
  • [15] Increasing the flux in a metabolic pathway: a metabolic control analysis perspective
    Fell, DA
    Thomas, S
    REGULATION OF PRIMARY METABOLIC PATHWAYS IN PLANTS, 1999, 42 : 257 - 273
  • [16] Use of metabolic control analysis in lactation biology
    Wright, T. C.
    Cant, J. P.
    McBride, B. W.
    JOURNAL OF AGRICULTURAL SCIENCE, 2008, 146 : 267 - 273
  • [17] Computational Modeling, Formal Analysis, and Tools for Systems Biology
    Bartocci, Ezio
    Lio, Pietro
    PLOS COMPUTATIONAL BIOLOGY, 2016, 12 (01)
  • [18] Computational genome analyses of metabolic enzymes in Mycobacterium leprae for drug target identification
    Shanmugam, Anusuya
    Natarajan, Jeyakumar
    BIOINFORMATION, 2010, 4 (09) : 392 - 395
  • [19] Metabolic control analysis of biogeochemical systems
    Louca, Stilianos
    COMMUNICATIONS EARTH & ENVIRONMENT, 2025, 6 (01):
  • [20] METABOLIC CONTROL ANALYSIS OF MAMMALIAN SERINE METABOLISM
    SNELL, K
    FELL, DA
    ADVANCES IN ENZYME REGULATION, 1990, 30 : 13 - 32