A holistic approach for integration of biological systems and usage in drug discovery

被引:8
|
作者
Gupta M.K. [1 ,2 ]
Misra K. [3 ]
机构
[1] Department of Bioinformatics, University Institute of Engineering and Technology, Chhatrapati Shahu Ji Maharaj University, Kanpur, 208024, Uttar Pradesh
[2] Dr. A.P.J. Abdul Kalam Technical University, Lucknow, Uttar Pradesh
[3] Centre of Biomedical Research, Sanjay Gandhi Post-Graduate Institute of Medical Sciences Campus, Raebareli Road, Lucknow, 226014, Uttar Pradesh
关键词
Big data; Biological networks; Drug discovery; Network biology; Network pharmacology; Pathways modeling; Systems biology; Translational research;
D O I
10.1007/s13721-015-0111-4
中图分类号
学科分类号
摘要
A system can be defined as an organized, interconnected structure consisting of interrelated and interdependent elements (e.g., components, factors, members, parts). These parts and processes are connected by structural and/or behavioral relationships and continually influence one another directly or indirectly to maintain a balance essential for the existence of the system, and for achieving its goal. With increasing inflow of biological data, serious efforts to empathize biological systems as true systems are nowadays almost practicable. Handling high-throughput data places stress mainly on in silico approach comprising database handling, modeling, simulation and analysis, resulting in dramatic progress in system-level analysis. The databases and methods in bioinformatics are now moving in the direction of implementation of integrative dataset systems to represent genes, proteins and metabolic pathways in combination with simulated environment which is dynamic. For understanding the complex biological disorders and normal pathways of system it is significant to integrate the reductionist data which comes from transcriptomics, genomics, proteomics, lipidomics, glycomics, fluxomics and metabolomics. Numerous bioinformatics approaches are being exploited to integrate the molecular information from the biological databases and assist in simulation of metabolic networks. High-throughput experimental data set systems are, however, established on the static representation of the molecular data and existing knowledge. Various biological tools have been developed for understanding the mechanism of several diseases for drug discovery process. Study of dynamic nature of genetic, biochemical and signal transduction pathways can be done by simulating reactions with the help of integrative tools. Rising usage of rational drug designing approach is significant for identification of target in disease polluted network and evaluating ligand interaction for enhanced efficacy. How in-depth investigation of the whole system (a holistic approach) leads to emergence of systems biology is the crux of this review. © 2016, Springer-Verlag Wien.
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