A Frame Work for Learning Drug Designing through Molecular Modelling Software Techniques and Biological Databases for Protein-Ligand Interactions

Article Preview

Abstract:

Applications of computer and information technology are indispensable in various fields especially in the field of biology. The use of computer aided tools plays a key role in solving biological problems. The spontaneous process of molecular docking is important for finding potentially strong candidate of drug for various viruses. The binding of protein receptors with ligand molecules is essential in drug discovery process. The aim of molecular docking tools is to predict the interaction between protein and ligand. This review outlines the major tools for protein - ligand docking which in turn emphasize the importance of molecular docking in modern drug discovery process.

You might also be interested in these eBooks

Info:

Pages:

111-118

Citation:

Online since:

December 2016

Export:

Price:

* - Corresponding Author

[1] T. Nanda, K. Tripathy, P. Ashwin, Integration of Bioinformatics Tools for Proteomics Research, J Comput Sci Syst Biol S. 1(2011) 13-2.

Google Scholar

[2] F. E. Koehn, G. T. Carter, The Evolving Role of Natural Products in Drug Discovery, Nat Rev Drug Discov. 4(2005) 206-220.

DOI: 10.1038/nrd1657

Google Scholar

[3] G. Bao, S. Suresh, Cell And Molecular Mechanics Of Biological Materials, Nat Mater. 2. 11(2003) 715-725.

Google Scholar

[4] G. M. Morris, R. Huey, A. J. Olson, Using AutoDock for Ligand‐Receptor Docking, Curr Protoc Bioinformatics. 3(2008) 8-14.

Google Scholar

[5] Inc, Discover tutorials, Materials Studio. Version, 4. 4 (2008).

Google Scholar

[6] Z. J. Xiao, Y. L. Huang, X. K. Zhu, S. L. Qiao, Functional Study of AcoX, an Unknown Protein Involved in Acetoin Catabolism, Advanced Materials Research, Vols. 393-395, pp.776-779, (2012).

DOI: 10.4028/www.scientific.net/amr.393-395.776

Google Scholar

[7] E. Yuriev, P. A. Ramsland, Latest Developments in Molecular Docking: 2010–2011 in review, J Mol Recognit. 26. 5(2013) 215-239.

DOI: 10.1002/jmr.2266

Google Scholar

[8] J. H. Yu, T. Qi, L. Xiong, Q. Li, J. L. Wang, Y. Z. Yuan, H. Geng, D. L. Liu, Fungicides Inhibition Analysis by Molecular Docking and Sensitivity Testing of Penicillium italicum, Applied Mechanics and Materials, Vols. 380-384, pp.4170-4174, (2013).

DOI: 10.4028/www.scientific.net/amm.380-384.4170

Google Scholar

[9] C.A. Lipinski, F. Lombardo, B.W. Dominy, P.J. Feeney, Experimental and Computational Approaches to Estimate Solubility and Permeability in Drug Discovery and Development Settings. Adv Drug Delivery Rev, 23(1997) 23-25.

DOI: 10.1016/s0169-409x(96)00423-1

Google Scholar

[10] S. Cosconati, S. Forli, A. L. Perryman, R. Harris, D.S. Goodsell, A.J. Olson, Virtual Screening with AutoDock: Theory and Practice, Expert Opin Drug Discov. 5. 6(2010) 597-607.

DOI: 10.1517/17460441.2010.484460

Google Scholar

[11] J. Payne, Beginning Python: Using Python 2. 6 and Python 3. 1., Wrox Press Ltd, (2010).

Google Scholar

[12] D. Seeliger, B. L. de Groot, Ligand Docking and Binding Site Analysis with PyMOL and Autodock/Vina, J. Comput. Aided Mol. Des. 24. 5(2010) 417-422.

DOI: 10.1007/s10822-010-9352-6

Google Scholar

[13] N. Prabakaran, R. J. Kannan, Sustainable Life-Span of WSN Nodes Using Participatory Devices in Pervasive Environment, Microsyst Technol. 1(2016) 1-7.

DOI: 10.1007/s00542-016-3117-7

Google Scholar

[14] Z.Q. Xie, G. Liang, L. Zhang , Molecular Mechanisms Underlying the Cholesterol-Lowering Effect of Ginkgo Biloba Extract in Hepatocytes: A Comparative Study With Lovastatin, Acta Pharmacol Sin. 30 (2009) 1262-1275.

DOI: 10.1038/aps.2009.126

Google Scholar

[15] L. K. Shawver, K. E. Lipson, T. A. T. Fong, G. McMahon, G. D. Plowman and L. M. Strawn, Drug. Discovery. 2 (1997) 50.

DOI: 10.1016/s1359-6446(96)10053-2

Google Scholar

[16] A.C. Wallace, R.A. Laskowski, J.M. Thornton, LIGPLOT: A Program to Generate Schematic Diagrams of Protein-Ligand Interactions, Protein Eng. 8(1995) 127-134.

DOI: 10.1093/protein/8.2.127

Google Scholar

[17] N. Guex, M.C. Peitsch, Swiss-Model and the Swiss-Pdb Viewer: An Environment for Comparative Protein Modeling, Electrophoresis. 18. 5(1997) 2714-2723.

DOI: 10.1002/elps.1150181505

Google Scholar

[18] M. Rebhan, V. Chalifa-Caspi, J. Prilusky, D. Lancet, GeneCards: Integrating Information about Genes, Proteins and Diseases, Trends Genet. 13(1997) 163.

DOI: 10.1016/s0168-9525(97)01103-7

Google Scholar

[19] UniProt Consortium, The Universal Protein Resource (UniProt), Nucleic Acids Res. 36(2008) 190-195.

DOI: 10.1093/nar/gkm895

Google Scholar

[20] A. Grosdidier, V. Zoete, and O. Michielin, SwissDock, a Protein-Small Molecule Docking Web Service Based on EADock DSS, Nucleic Acids Res. 39(2011) 270-277.

DOI: 10.1093/nar/gkr366

Google Scholar

[21] R. Periasamy, S. Kothainayaki, R. Rajamohan, K. Sivakumar, Spectral Investigation and Characterization of Host–Guest Inclusion Complex of 4, 4'-methylene-bis (2-chloroaniline) with beta-cyclodextrin, Carbohydr Polym. 114(2014) 558-566.

DOI: 10.1016/j.carbpol.2014.08.006

Google Scholar

[22] M.F. Sanner: The Python Interpreter as a Framework for Integrating Scientific Computing Software-Components (2007).

Google Scholar

[23] Information on http http: /www. ncbi. nlm. nih. gov.

Google Scholar