Computation in BioInformatics. Группа авторов
Чтение книги онлайн.

Читать онлайн книгу Computation in BioInformatics - Группа авторов страница 15

Название: Computation in BioInformatics

Автор: Группа авторов

Издательство: John Wiley & Sons Limited

Жанр: Базы данных

Серия:

isbn: 9781119654766

isbn:

СКАЧАТЬ 31, 13, 3352–3355, 2007.

      14. Wass, M.N., Kelley, L.A., Sternberg, M.J.E., 3DLigandSite: predicting ligand-binding sites using similar structures. Nucleic Acids Res., Jul 1, 38, Web Server issue, W469–W473, 2010.

      15. Berman, H.M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T.N., Weissig, H., Bourne, P.E., The Protein Data Bank. Nucleic Acids Res., 28, 235–242, 2000.

      16. Ramachandran, K.I., Deepa, G., Namboori, K., Computational Chemistry and Molecular Modeling Principles and Applications, Springer-Verlag GmbH, Berlin, 2008.

      17. Cavasotto, C.N. and Phatak, S.S., Homology modeling in drug discovery: current trends and applications. Drug Discovery Today, 676–683, 2009.

      19. Kim, S., Thiessen, P.A., Bolton, E.E., Chen, J., Fu, G., Gindulyte, A., Bryant, S.H., PubChem substance and compound databases. Nucleic Acids Res., 44, D1202–1213, 2016.

      20. Eswar, N., Marti-Renom, M.A., Webb, B., Madhusudhan, M.S., Eramian, D. et al., Comparative Protein Structure Modeling with MODELLER. Curr. Protoc. Bioinf., 15, 5.6.1–5.6.30, 2006.

      21. Lin, J., Okada, K., Raytchev, M., Smith, M.C., Nicastro, D., Structural mechanism of the dynein power stroke. Nat. Cell Biol., 16, 479–485, 2014.

      22. Johansson, M.U., Zoete, V., Michielin, O., Guex, N., Defining and searching for structural motifs using DeepView/Swiss-PdbViewer. BMC Bioinf., 13, 173, 2012.

      23. Combet, C., Jambon, M., Deléage, G., Geourjon, C., Geno3D: automatic comparative molecular modelling of protein. Bioinformatics, 18, 213–214, 2002.

      24. Schwede, T., Kopp, J., Guex, N., Peitsch, M.C., SWISS-MODEL: an automated protein homology-modeling server. Nucleic Acids Res., 31, 13, 3381–3385, 2003.

      25. Winn, M.D., Ballard, C.C., Cowtan, K.D., Dodson, E.J., Emsley, P. et al., Overview of the CCP4 suite and current developments. Acta Crystallogr. D Biol. Crystallogr., 67, 235–242, 2011.

      26. Qureshi, R.H. and Noman, B., SZABIST., Is Abalone, Bio designer and Fold it, the best software for Protein Structure Prediction of AIDS Virus? J. Indep. Stud. Res. – Comput., 9, 2, 36–43, 2011.

      27. Rackers, J.A., Wang, Z., Lu, C., Laury, M.L., Lagardère, L., Schnieders, M.J., Schnieders, M.J., Tinker 8: Software Tools for Molecular Design. J. Chem. Theory Comput., 14, 10, 5273–5289, 2018.

      28. Eswar, N., Webb, B., Marti-Renom, M.A., Madhusudhan, M.S., Eramian, D., Shen, M.-y., Pieper, U., Sali, A., Comparative Protein Structure Modeling Using Modeller. Curr. Protoc. Bioinf., 15, 1, 5.6.1–5.6.30, 2006.

      29. Kaplan, W. and Littlejohn, T.G., Swiss-PDB Viewer (Deep View). Brief Bioinform., 2, 2, 195–7, 2001.

      30. Rester, U., From virtuality to reality - Virtual screening in lead discovery and lead optimization: a medicinal chemistry perspective. Curr. Opin. Drug Discovery Devel., 11, 559–568, 2008.

      31. Walters, W.P., Stahl, M.T., Murcko, M.A., Virtual screening – an overview. Drug Discovery Today, 3, 160–178, 1998.

      32. Laurie, A.T. and Jackson, R.M., Q-SiteFinder: An energy-based method for the prediction of protein-ligand binding sites. Bioinformatics, 21, 1908–1916, 2005.

      34. Forli, S., Huey, R., Pique, M.E., Sanner, M., Goodsell, D.S., Olson, A.J., Computational protein-ligand docking and virtual drug screening with the AutoDock suite. Nat. Protoc., 11, 5, 905–919, 2016.

      35. Hart, T.N. and Read, R.J., A multiple-start Monte Carlo docking method. Proteins, 13, 206–22, 1992.

      36. Hart, T.N., Ness, S.R., Read, R.J., Critical evaluation of the research docking program for the CASP2 challenge. Proteins, Suppl 1, 29, 205–9, 1997.

      37. Pagadala, N.S., Syed, K., Tuszynski, J., Software for molecular docking: a review. Biophys. Rev., 9, 2, 91–102, 2017.

      38. Bikadi, Z. and Hazai, E., Application of the PM6 semi-empirical method to modeling proteins enhances docking accuracy of AutoDock. J. Cheminform., 1, 15, 2009.

      39. Grosdidier, A., Zoete, V., Michielin, O., SwissDock, a protein-small molecule docking web service based on EADock DSS. Nucleic Acids Res., 39, Web Server issue, W270–W277, 2011.

      40. Singh, K.D. and Muthusamy, K., Molecular modeling, quantum polarized ligand docking and structure-based 3D-QSAR analysis of the imidazole series as dual AT1 and ETA receptor antagonists. Acta Pharmacol. Sin., 34, 12, 1592–1606, 2013.

      41. Rizvi, S.M.D., Shakil, S., Haneef, M., A simple click by click protocol to perform docking: Autodock 4.2 made easy for non- Bioinformaticians. Excli J., 12, 831–857, 2013.

      42. Schuttelkopf, A.W. and van Aalten, D.M., PRODRG: A tool for high-throughput crystallography of protein-ligand complexes. Acta Crystallogr. Sect. D: Biol. Crystallogr., 60, 1355–1363, 2004.

      43. Alder, B.J. and Wainwright, T.E., Studies in Molecular Dynamics. I. General Method. J. Chem. Phys., 27, 1208, 1957.

      44. Van der Spoel, D., Lindahl, E., Hess, B., Groenhof, G., Mark, A.E., Berendsen, H.J., GROMACS: Fast, flexible, and free. J. Comput. Chem., 26, 1701–1718, 2005.

      45. Gimenez, B.G., Santos, M.S., Ferrarini, M., Fernandes, J.P., Evaluation of blockbuster drugs under the rule-of-five. Pharmazie, 65, 148–152, 2010.

      46. Cheng, F., Li, W., Zhou, Y., Shen, J., Wu, Z., Liu, G., Tang, Y., AdmetSAR: A comprehensive source and free tool for assessment of chemical ADMET properties. J. Chem. Inf. Model., 52, 3099–3105, 2012.

      47. Lagunin, A., Stepanchikova, A., Filimonov, D., Poroikov, V., PASS: Prediction of activity spectra for biologically active substances. Bioinformatics, 16, 747–748, 2000.

      48. Mychaleckyj, J.C., Genome Mapping Statistics and Bioinformatics. Methods Mol. Biol., 404, 461–488, 2007.

      50. Kumar, K.M., Lavanya, P., Anbarasu, A., Ramaiah, S., Molecular dynamics and molecular docking studies on E166A point mutant, R274N/R276N double mutant, and E166A/R274N/R276N triple mutant forms of class A β-lactamases. J. Biomol. Struct. Dyn., 32, 12, 1953–1968, 2014.

      51. Joshi, S.D., More, U.A., Dixit, S.R., Korat, H.H., Aminabhavi, T.M., Badiger, A.M., Synthesis, characterization, biological activity, and 3D-QSAR studies on some novel class of pyrrole derivatives as antitubercular agents. Med. Chem. Res., 23, 3, 1123–1147, 2013.

      52. Malathi, K. and Ramaiah, S., Molecular Docking and Molecular Dynamics Studies СКАЧАТЬ