271
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Network target for screening synergistic drug combinations with application to traditional Chinese medicine

      research-article
      1 , , 1 , 1
      BMC Systems Biology
      BioMed Central
      The 4th International Conference on Computational Systems Biology (ISB 2010)
      9-11 September 2010

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Multicomponent therapeutics offer bright prospects for the control of complex diseases in a synergistic manner. However, finding ways to screen the synergistic combinations from numerous pharmacological agents is still an ongoing challenge.

          Results

          In this work, we proposed for the first time a “network target”-based paradigm instead of the traditional "single target"-based paradigm for virtual screening and established an algorithm termed NIMS (Network target-based Identification of Multicomponent Synergy) to prioritize synergistic agent combinations in a high throughput way. NIMS treats a disease-specific biological network as a therapeutic target and assumes that the relationship among agents can be transferred to network interactions among the molecular level entities (targets or responsive gene products) of agents. Then, two parameters in NIMS, Topology Score and Agent Score, are created to evaluate the synergistic relationship between each given agent combinations. Taking the empirical multicomponent system traditional Chinese medicine (TCM) as an illustrative case, we applied NIMS to prioritize synergistic agent pairs from 63 agents on a pathological process instanced by angiogenesis. The NIMS outputs can not only recover five known synergistic agent pairs, but also obtain experimental verification for synergistic candidates combined with, for example, a herbal ingredient Sinomenine, which outperforms the meet/min method. The robustness of NIMS was also showed regarding the background networks, agent genes and topological parameters, respectively. Finally, we characterized the potential mechanisms of multicomponent synergy from a network target perspective.

          Conclusions

          NIMS is a first-step computational approach towards identification of synergistic drug combinations at the molecular level. The network target-based approaches may adjust current virtual screen mode and provide a systematic paradigm for facilitating the development of multicomponent therapeutics as well as the modernization of TCM.

          Related collections

          Most cited references51

          • Record: found
          • Abstract: found
          • Article: not found

          Gene Ontology: tool for the unification of biology

          Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            Statistical mechanics of complex networks

            Complex networks describe a wide range of systems in nature and society, much quoted examples including the cell, a network of chemicals linked by chemical reactions, or the Internet, a network of routers and computers connected by physical links. While traditionally these systems were modeled as random graphs, it is increasingly recognized that the topology and evolution of real networks is governed by robust organizing principles. Here we review the recent advances in the field of complex networks, focusing on the statistical mechanics of network topology and dynamics. After reviewing the empirical data that motivated the recent interest in networks, we discuss the main models and analytical tools, covering random graphs, small-world and scale-free networks, as well as the interplay between topology and the network's robustness against failures and attacks.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Angiogenesis in cancer, vascular, rheumatoid and other disease.

              J Folkman (1995)
              Recent discoveries of endogenous negative regulators of angiogenesis, thrombospondin, angiostatin and glioma-derived angiogenesis inhibitory factor, all associated with neovascularized tumours, suggest a new paradigm of tumorigenesis. It is now helpful to think of the switch to the angiogenic phenotype as a net balance of positive and negative regulators of blood vessel growth. The extent to which the negative regulators are decreased during this switch may dictate whether a primary tumour grows rapidly or slowly and whether metastases grow at all.
                Bookmark

                Author and article information

                Conference
                BMC Syst Biol
                BMC Systems Biology
                BioMed Central
                1752-0509
                2011
                20 June 2011
                : 5
                : Suppl 1
                : S10
                Affiliations
                [1 ]MOE Key Laboratory of Bioinformatics and Bioinformatics Division, TNLIST / Department of Automation, Tsinghua University, Beijing 100084, China
                Article
                1752-0509-5-S1-S10
                10.1186/1752-0509-5-S1-S10
                3121110
                21689469
                845976a2-2936-4753-94bb-d7bafc1879f8
                Copyright ©2011 Li et al; licensee BioMed Central Ltd.

                This is an open access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                The 4th International Conference on Computational Systems Biology (ISB 2010)
                Suzhou, P. R. China
                9-11 September 2010
                History
                Categories
                Report

                Quantitative & Systems biology
                Quantitative & Systems biology

                Comments

                Comment on this article