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Analyzing Thiol-Dependent Redox Networks in the Presence of Methylene Blue and Other Antimalarial Agents with RT-PCR-Supported in silico Modeling

Please always quote using this URN: urn:nbn:de:bvb:20-opus-123751
  • BACKGROUND: In the face of growing resistance in malaria parasites to drugs, pharmacological combination therapies are important. There is accumulating evidence that methylene blue (MB) is an effective drug against malaria. Here we explore the biological effects of both MB alone and in combination therapy using modeling and experimental data. RESULTS: We built a model of the central metabolic pathways in P. falciparum. Metabolic flux modes and their changes under MB were calculated by integrating experimental data (RT-PCR data on mRNAs forBACKGROUND: In the face of growing resistance in malaria parasites to drugs, pharmacological combination therapies are important. There is accumulating evidence that methylene blue (MB) is an effective drug against malaria. Here we explore the biological effects of both MB alone and in combination therapy using modeling and experimental data. RESULTS: We built a model of the central metabolic pathways in P. falciparum. Metabolic flux modes and their changes under MB were calculated by integrating experimental data (RT-PCR data on mRNAs for redox enzymes) as constraints and results from the YANA software package for metabolic pathway calculations. Several different lines of MB attack on Plasmodium redox defense were identified by analysis of the network effects. Next, chloroquine resistance based on pfmdr/and pfcrt transporters, as well as pyrimethamine/sulfadoxine resistance (by mutations in DHF/DHPS), were modeled in silico. Further modeling shows that MB has a favorable synergism on antimalarial network effects with these commonly used antimalarial drugs. CONCLUSIONS: Theoretical and experimental results support that methylene blue should, because of its resistance-breaking potential, be further tested as a key component in drug combination therapy efforts in holoendemic areas.show moreshow less

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Metadaten
Author: J. Zirkel, A. Cecil, F. Schäfer, S. Rahlfs, A. Ouedraogo, K. Xiao, S. Sawadogo, B. Coulibaly, K. Becker, T. Dandekar
URN:urn:nbn:de:bvb:20-opus-123751
Document Type:Journal article
Faculties:Fakultät für Biologie / Theodor-Boveri-Institut für Biowissenschaften
Language:English
Parent Title (English):Bioinformatics and Biology Insights
Year of Completion:2012
Volume:6
Pagenumber:287-302
Source:Bioinformatics and Biology Insights 2012:6 287–302. doi: 10.4137/BBI.S10193
DOI:https://doi.org/10.4137/BBI.S10193
Pubmed Id:http://www.ncbi.nlm.nih.gov/pubmed?term=PMC3516044
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie
Tag:combination therapy; drug; elementary mode analysis; malaria; metabolic flux; methylene blue; pathway; resistance
Release Date:2015/12/23
Note:
This is an open access article. Unrestricted non-commercial use is permitted provided the original work is properly cited.