Abstract
Three-dimensional (3D) pharmacophore modelling is a modern approach used to elucidate the intermolecular interaction of ligands with the target of interest. In the past few years, pharmacophore models have been developed with chemical features and are intuitively understandable and broadly employed successfully in computational drug discovery by the researchers. The concert and utility of pharmacophore modelling are demarcated by the two major factors; (i) definition and placement of pharmacophoric features and (ii) the arrangement approaches used to overlay the 3D pharmacophore models and small molecules. This chapter provides a brief account of the recent technologies and developed model used in pharmacophores-based drug design.
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References
G. Wolber, T. Seidel, F. Bendix, T. Langer, Molecule-pharmacophore superpositioning and pattern matching in computational drug design. Drug Discov. Today 13, 23–29 (2008)
Y. Patel, V.J. Gillet, G. Bravi, A.R. Leach, A comparison of the pharmacophore identification programs: catalyst, DISCO and GASP. J. Comput. Aided Mol. Des. 16, 653–681 (2002)
G. Wolber, A.A. Dornhofer, T. Langer, Efficient overlay of small organic molecules using 3D pharmacophores. J. Comput. Aided Mol. Des. 20, 773–788 (2006)
G. Wolber, R. Kosara, Pharmacophores from macromolecular complexes with LigandScout. Pharmacophores Pharmacophore Searches 32, 131–150 (2006)
J. Kirchmair, C. Laggner, G. Wolber, T. Langer, Comparative analysis of protein-bound ligand conformations with respect to catalyst’s conformational space subsampling algorithms. J. Chem. Inf. Model. 45, 422–430 (2005)
J. Kirchmair, G. Wolber, C. Laggner, T. Langer, Comparative performance assessment of the conformational model generators omega and catalyst: a large-scale survey on the retrieval of protein-bound ligand conformations. J. Chem. Inf. Model. 46, 1848–1861 (2006)
S.-Y. Yang, Pharmacophore modeling and applications in drug discovery: challenges and recent advances. Drug Discov. Today 15, 444–450 (2010)
G. Wolber, T. Langer, LigandScout: 3-D pharmacophores derived from protein-bound ligands and their use as virtual screening filters. J. Chem. Inf. Model. 45, 160–169 (2005)
D.S.H. Chan, H.M. Lee, F. Yang, C.M. Che, C.C. Wong, R. Abagyan, C.H. Leung, D.L. Ma, Structure-based discovery of natural-product-like TNF-α inhibitors. Angew. Chem. Int. Ed. 49, 2860–2864 (2010)
M. Brvar, A. Perdih, M. Oblak, L.P. Mašič, T. Solmajer, In silico discovery of 2-amino-4-(2, 4-dihydroxyphenyl) thiazoles as novel inhibitors of DNA gyrase B. Bioorg. Med. Chem. Lett. 20, 958–962 (2010)
D. Wei, X. Jiang, L. Zhou, J. Chen, Z. Chen, C. He, K. Yang, Y. Liu, J. Pei, L. Lai, Discovery of multitarget inhibitors by combining molecular docking with common pharmacophore matching. J. Med. Chem. 51, 7882–7888 (2008)
A.L. Bowman, Z. Nikolovska-Coleska, H. Zhong, S. Wang, H.A. Carlson, Small molecule inhibitors of the MDM2-p53 interaction discovered by ensemble-based receptor models. J. Am. Chem. Soc. 129, 12809–12814 (2007)
S.B. Shuker, P.J. Hajduk, R.P. Meadows, S.W. Fesik, Discovering high-affinity ligands for proteins: SAR by NMR. Science, 274(5292), 1531–1534 (1996)
R. Wang, X. Fang, Y. Lu, S. Wang, The PDBbind database: collection of binding affinities for protein–ligand complexes with known three-dimensional structures. J. Med. Chem. 47, 2977–2980 (2004)
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Kaushik, A.C., Kumar, A., Bharadwaj, S., Chaudhary, R., Sahi, S. (2018). Three-Dimensional (3D) Pharmacophore Modelling-Based Drug Designing by Computational Technique. In: Bioinformatics Techniques for Drug Discovery. SpringerBriefs in Computer Science. Springer, Cham. https://doi.org/10.1007/978-3-319-75732-2_4
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DOI: https://doi.org/10.1007/978-3-319-75732-2_4
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