56
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      A Network-Based Multi-Target Computational Estimation Scheme for Anticoagulant Activities of Compounds

      research-article

      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

          Traditional virtual screening method pays more attention on predicted binding affinity between drug molecule and target related to a certain disease instead of phenotypic data of drug molecule against disease system, as is often less effective on discovery of the drug which is used to treat many types of complex diseases. Virtual screening against a complex disease by general network estimation has become feasible with the development of network biology and system biology. More effective methods of computational estimation for the whole efficacy of a compound in a complex disease system are needed, given the distinct weightiness of the different target in a biological process and the standpoint that partial inhibition of several targets can be more efficient than the complete inhibition of a single target.

          Methodology

          We developed a novel approach by integrating the affinity predictions from multi-target docking studies with biological network efficiency analysis to estimate the anticoagulant activities of compounds. From results of network efficiency calculation for human clotting cascade, factor Xa and thrombin were identified as the two most fragile enzymes, while the catalytic reaction mediated by complex IXa:VIIIa and the formation of the complex VIIIa:IXa were recognized as the two most fragile biological matter in the human clotting cascade system. Furthermore, the method which combined network efficiency with molecular docking scores was applied to estimate the anticoagulant activities of a serial of argatroban intermediates and eight natural products respectively. The better correlation (r = 0.671) between the experimental data and the decrease of the network deficiency suggests that the approach could be a promising computational systems biology tool to aid identification of anticoagulant activities of compounds in drug discovery.

          Conclusions

          This article proposes a network-based multi-target computational estimation method for anticoagulant activities of compounds by combining network efficiency analysis with scoring function from molecular docking.

          Related collections

          Most cited references59

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

          Efficient Behavior of Small-World Networks

          We introduce the concept of efficiency of a network as a measure of how efficiently it exchanges information. By using this simple measure, small-world networks are seen as systems that are both globally and locally efficient. This gives a clear physical meaning to the concept of "small world," and also a precise quantitative analysis of both weighted and unweighted networks. We study neural networks and man-made communication and transportation systems and we show that the underlying general principle of their construction is in fact a small-world principle of high efficiency.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Virtual screening of chemical libraries.

            Virtual screening uses computer-based methods to discover new ligands on the basis of biological structures. Although widely heralded in the 1970s and 1980s, the technique has since struggled to meet its initial promise, and drug discovery remains dominated by empirical screening. Recent successes in predicting new ligands and their receptor-bound structures, and better rates of ligand discovery compared to empirical screening, have re-ignited interest in virtual screening, which is now widely used in drug discovery, albeit on a more limited scale than empirical screening.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Global mapping of pharmacological space.

              We present the global mapping of pharmacological space by the integration of several vast sources of medicinal chemistry structure-activity relationships (SAR) data. Our comprehensive mapping of pharmacological space enables us to identify confidently the human targets for which chemical tools and drugs have been discovered to date. The integration of SAR data from diverse sources by unique canonical chemical structure, protein sequence and disease indication enables the construction of a ligand-target matrix to explore the global relationships between chemical structure and biological targets. Using the data matrix, we are able to catalog the links between proteins in chemical space as a polypharmacology interaction network. We demonstrate that probabilistic models can be used to predict pharmacology from a large knowledge base. The relationships between proteins, chemical structures and drug-like properties provide a framework for developing a probabilistic approach to drug discovery that can be exploited to increase research productivity.
                Bookmark

                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2011
                22 March 2011
                : 6
                : 3
                : e14774
                Affiliations
                [1 ]Beijing National Laboratory for Molecular Sciences, State Key Lab of Rare Earth Material Chemistry and Applications, College of Chemistry and Molecular Engineering, Peking University, Beijing, People's Republic of China
                [2 ]Beijing National Laboratory for Molecular Sciences, Center for Molecular Sciences, State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Institute of Chemistry Chinese Academy of Sciences, Beijing, People's Republic of China
                [3 ]Experimental Research Center, China Academy of Chinese Medical Sciences, Beijing, People's Republic of China
                [4 ]Graduate University of Chinese Academy of Sciences, Beijing, People's Republic of China
                German Cancer Research Center, Germany
                Author notes

                Conceived and designed the experiments: QL LC YT XX. Performed the experiments: QL XL CL. Analyzed the data: QL XL. Contributed reagents/materials/analysis tools: QL CL JS. Wrote the paper: QL.

                Article
                09-PONE-RA-14324R2
                10.1371/journal.pone.0014774
                3062543
                21445339
                54609a19-b4ca-4087-a0fa-8900f749857e
                Li et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 18 November 2009
                : 19 February 2011
                Page count
                Pages: 9
                Categories
                Research Article
                Biochemistry/Bioinformatics
                Chemistry/Physical, Inorganic, and Analytical Chemistry
                Computational Biology/Systems Biology

                Uncategorized
                Uncategorized

                Comments

                Comment on this article