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Research Articles

Design of novel lead molecules against RhoG protein as cancer target – a computational study

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Pages 3119-3139 | Received 15 Dec 2015, Accepted 15 Sep 2016, Published online: 04 Nov 2016

References

  • Accelrys Software Inc. (2013). Discovery studio Visualizer 3.5 version, San Diego.
  • Altschul, S. F., Gish, W., Miller, W., Myers, E. W., & Lipman, D. J. (1990). Basic local alignment search tool. Journal of Molecular Biology, 215, 403–410.
  • Bhargavi, K., Kalyan Chaitanya, P., Ramasree, D., Vasavi, M., Murthy, D. K., & Uma, V. (2010). Homology modeling and docking studies of human Bcl-2L10 protein. Journal of Biomolecular Structure and Dynamics, 28, 379–391.
  • Boettner, B., & Van Aelst, L. (2002). The role of Rho GTPases in disease development. Gene, 286, 155–174.
  • Boureux, A., Vignal, E., Faure, S., & Fort, P. (2007). Evolution of the Rho family of ras-like GTPases in eukaryotes. Molecular Biology and Evolution, 24, 203–216.
  • Bray, F., & Moller, B. (2006). Predicting the future burden of cancer. Nature Reviews Cancer, 6, 63–74.
  • Cano, G., Garcia-Rodriguez, J., & Pirez-Sanchez, H. (2014). Improvement of virtual screening predictions using computational intelligence methods. Drug Design & Discovery, 11, 33–39.
  • Chimini, G., & Chavrier, P. (2000). Function of Rho family proteins in actin dynamics during phagocytosis and engulfment. Nature Cell Biology, 2, E191–E196.
  • Cole, C., Barber, J. D., & Barton, G. J. (2008). The Jpred3 secondary structure prediction server. Nucleic Acids Research, 36, W197–W201.
  • Cook, D. R., Rossman, K. L., & Der, C. J. (2013). Rho guanine nucleotide exchange factors: Regulators of Rho GTPase activity in development and disease. Oncogene, 33, 4021–4035.
  • da Silva Goncalves, A., Franca, T. C., Caetano, M. S., & Ramalho, T. C. (2014). Reactivation steps by 2PAM of tabuninhibited human acetylcholinesterase: Reducing the computational cost in hybrid QM/MM methods. Journal of Biomolecular Structure and Dynamics, 32, 301–307.
  • Dundas, J., Ouyang, Z., Tseng, J., Binkowski, A., Turpaz, Y., & Liang, J. (2006). CASTp computed atlas of surface topography of proteins with structural and topographical mapping of functionally annotated residues. Nucleic Acids Research, 34, W116–W118.
  • Empereur-Mot, C., Guillemain, H., Latouche, A., Zagury, J. F., Viallon, V., & Montes, M. (2015). Predictiveness curves in virtual screening. Journal of cheminformatics, 7, 1–17.
  • Essmann, U., Perera, L., Berkowitz, M. L., Darden, T. A., Lee, H., & Pedersen, L. G. (1995). A smooth particle mesh Ewald method. The Journal of Chemical Physics, 103, 8577–8593.
  • Feller, S. E., Zhang, Y., Pastor, R. W., & Brooks, B. R. (1995). Constant pressure molecular dynamics simulation: The Langevin piston method. The Journal of Chemical Physics, 103, 4613–4621.
  • Fiser, A., & Sali, A. (2003). Modeller: Generation and refinement of homology-based protein structure models. Methods in Enzymology, 374, 461–491.
  • Franca, T. C., Guimaraes, A. P., Cortopassi, W. A., Oliveira, W. A., & Ramalho, T. C. (2013). Applications of docking and molecular dynamic studies on the search for new drugs against the biological warfare agents Bacillus anthracis and Yersinia pestis. Current Computer Aided Drug Design, 9, 507–517.
  • Friesner, R. A., Murphy, R. B., Repasky, M. P., Frye, L. L., Greenwood, J. R., & Halgren, T. A. (2006). Extra precision glide docking and scoring incorporating a model of hydrophobic enclosure for protein–ligand complexes. Journal of Medicinal Chemistry, 49, 6177–6196.
  • Gasteiger, E., Gattiker, A., Hoogland, C., Ivanyi, I., Appel, R. D., & Bairoch, A. (2003). ExPASy proteomics server for in depth protein knowledge and analysis. Nucleic Acids Research, 31, 3784–3788.
  • Genheden, S., & Ryde, U. (2015). The MM/PBSA and MM/GBSA methods to estimate ligand-binding affinities. Expert Opinion on Drug Discovery, 10, 449–461.
  • Halgren, T. A. (2009). Identifying and characterizing binding sites and assessing druggability. Journal of Chemical Information and Modeling, 49, 377–389.
  • Halgren, T. A., Murphy, R. B., Friesner, R. A., Beard, H. S., Frye, L. L., Pollard, W. T., & Banks, J. L. (2004). Glide: A new approach for rapid, accurate docking and scoring. 2. Enrichment factors in database screening. Journal of Medicinal Chemistry, 47, 4750–4759.
  • Hamza, A., Wei, N. N., Hao, C., Xiu, Z., & Zhan, C. G. (2013). A novel and efficient ligand-based virtual screening approach using the HWZ scoring function and an enhanced shape-density model. Journal of Biomolecular Structure & Dynamics, 31, 1236–1250.
  • Hamza, A., Wei, N. N., & Zhan, C. G. (2012). Ligand-based virtual screening approach using a new scoring function. Journal of Chemical Information Modeling, 52, 963–974.
  • Harada, K., Hiramoto-Yamaki, N., Negishi, M., & Katoh, H. (2011). EphA4 and EphA2 mediate resistance to anoikis through RhoG and phosphatidylinositol 3-kinase. Experimental Cell Research, 317, 1701–1713.
  • Heasman, S. J., & Ridley, A. J. (2008). Mammalian Rho GTPases new insights into their functions from in vivo studies. Nature Reviews Molecular Cell Biology, 9, 690–701.
  • Hernandez, M., Ghersi, D., & Sanchez, R. (2009). SITEHOUND-web: A server for ligand binding site identification in protein structures. Nucleic Acids Research, 37, W413–W416.
  • Hiramoto, K., Negishi, M., & Katoh, H. (2006). Dock4 is regulated by RhoG and promotes Rac -dependent cell migration. Experimental Cell Research, 312, 4205–4216.
  • Hiramoto-Yamaki, N., Takeuchi, S., Ueda, S., Harada, K., Fujimoto, S., & Negishi, M. (2010). Ephexin4 and EphA2 mediate cell migration through a RhoG-dependent mechanism. The Journal of Cell Biology, 190, 461–477.
  • Hollingsworth, S. A., & Karplus, P. A. (2010). A fresh look at the Ramachandran plot and the occurrence of standard structures in proteins. Biomolecular Concepts, 1, 271–283.
  • Humphrey, W., Dalke, A., & Schulten, K. (1996). VMD: Visual molecular dynamics. Journal of Molecular Graphics, 14, 33–38.
  • Jaffe, A. B., & Hall, A. (2005). Rho GTPases: Biochemistry and biology. Annual Review of Cell and Developmental Biology, 21, 247–269.
  • Jorgensen, W. L., Maxwell, D. S., & Tirado-Rives, J. (1996). Development and testing of the OPLS all-atom force field on conformational energetics and properties of organic liquids. Journal of the American Chemical Society, 118, 11225–11236.
  • Kawai, H., Kobayashi, M., Hiramoto-Yamaki, N., Harada, K., Negishi, M., & Katoh, H. (2013). Ephexin4-mediated promotion of cell migration and anoikis resistance is regulated by serine 897 phosphorylation of EphA2. FEBS Open Bio, 3, 78–82.
  • Kitchen, D. B., Decornez, H., Furr, J. R., & Bajorath, J. (2004). Docking and scoring in virtual screening for drug discovery: Methods and applications. Nature Reviews Drug Discovery, 3, 935–949.
  • Larkin, M. A., Blackshields, G., Brown, N. P., Chenna, R., McGettigan, P. A., McWilliam, H., … Higgins, D. G. (2007). Clustal W and Clustal X version 2.0. Bioinformatics, 23, 2947–2948.
  • Laskowski, R. A., MacArthur, M. W., Moss, D. S., & Thornton, J. M. (1993). Procheck a program to check the stereochemical quality of protein structures. Journal of Applied Crystallography, 26, 283–291.
  • Lee, B., & Richards, F. M. (1971). The interpretation of protein structures: Estimation of static accessibility. Journal of Molecular Biology, 55, 379–400.
  • LigPrep. (2010). Version 2.4, Schrödinger, LLC, New York.
  • Luthy, R., Bowie, J. U., & Eisenberg, D. (1992). Assessment of protein models with three-dimensional profiles. Nature, 356, 83–85.
  • Maheshwari, S., & Brylinski, M. (2015). Prediction of protein–protein interaction sites from weakly homologous template structures using meta-threading and machine learning. Journal of Molecular Recognition, 28, 35–48.
  • Malkhed, V., Mustyala, K. K., Potlapally, S. R., & Vuruputuri, U. (2013). Identification of novel leads applying in silico studies for Mycobacterium multidrug resistant (MMR) protein. Journal of Bio molecular Structure and Dynamics, 32, 1889–1906.
  • Murga, C., Zohar, M., Teramoto, H., & Gutkind, J. S. (2002). Rac1 and RhoG promote cell survival by the activation of PI3K and Akt independently of their ability to stimulate JNK and NF-kB. Oncogene, 21, 207–216.
  • Mysinger, M. M., Carchia, M., Irwin, J. J., & Shoichet, B. K. (2012). Directory of useful decoys, enhanced (DUD-E): Better ligands and decoys for better benchmarking. Journal of Medicinal Chemistry, 55, 6582–6594.
  • Patel, M., Chiang, T. C., Tran, V., Lee, F. J., & Cote, J. F. (2011). The arf family GTPase Arl4A complexes with ELMO proteins to promote actin cytoskeleton remodeling and reveals a versatile ras-binding domain in the ELMO proteins family. Journal of Biological Chemistry, 286, 38969–38979.
  • Phillips, J. C., Braun, R., Wang, W., Gumbart, J., Tajkhorshid, E., Villa, E., … Schulten, K. (2005). Scalable molecular dynamics with NAMD. Journal of Computational Chemistry, 26, 1781–1802.
  • Powers, R., Copeland, J. C., Germer, K., Mercier, K. A., Ramanathan, V., & Revesz, P. (2006). Comparison of protein active site structures for functional annotation of proteins and drug design. Proteins, 65, 124–135.
  • Protein Preparation Wizard. (2010). Epik version 2.1, Schrödinger, LLC, New York.
  • PyMOL Molecular Graphics System. (2010). Version 1.3, Schrödinger, LLC, New York.
  • QikProp. (2010). Version 3.3, Schrödinger, LLC, New York.
  • Ramakrishna, D., Ramasree, D., Bhargavi, K., Vishwanath, R., Santhiprada, V., Rajender, V., & Uma, V. (2016). Suppressor of cytokine signalling-3 as a drug target for type 2 diabetes mellitus: A structure-guided approach. ChemistrySelect, 1, 2502–2514.
  • Ramatenki, V., Potlapally, S. R., Dumpati, R. K., Vadija, R., & Vuruputuri, Uma (2015). Homology modeling and virtual screening of ubiquitin conjugation enzyme E2A for designing a novel selective antagonist against cancer. Journal of Receptors and Signal Transduction, 35, 536–549.
  • Ruiz-Lafuente, N., Alcaraz-Garcia, M. J., Garcia-Serna, A. M., Sebastian-Ruiz, Silvia, Moya-Quiles, M. R., Garcia-Alonso, A. M., & Parrado, A. (2015). Dock10, a Cdc42 and Rac1 GEF, induces loss of elongation, filopodia, and ruffles in cervical cancer epithelial HeLa cells. Journal of Biology Open, 4, 627–635.
  • Schachter, M. (2004). Chemical, pharmacokinetic and pharmacodynamics properties of statins an updates. Fundamental & Clinical Pharmacology, 19, 117–125.
  • Schneidman-Duhovny, D., Inbar, Y., Nussinov, R., & Wolfson, H. J. (2005). PatchDock and SymmDock servers for rigid and symmetric docking. Nucleic Acids Research, 33, 363–367.
  • Siegel, R., Ma, J., Zou, Z., & Jemal, A. (2014). Cancer statistics 2014. Cancer Journal for Clinicians, 64, 9–29.
  • Sit, S.-T., & Manser, E. D. (2011). Rho GTPases and their role in organizing the actin cytoskeleton. Journal of Cell Science, 124, 679–683.
  • Stathis, A., & Moore, M. J. (2010). Advanced pancreatic carcinoma: Current treatment and future challenges. Nature Reviews Clinical Oncology, 7, 163–172.
  • Takeshi, K., Yusuke, S., Yoshifumi, F., & Haruki, N. (2013). LigandBox: A database for 3D structures of chemical compounds. Biophysics, 9, 113–121.
  • Ting, D., Wang, G., Shapovalov, M., Mitra, R., Jordan, M. I., & Dunbrack, R. L. (2010). Neighbor-dependent Ramachandran probability distributions of amino acids developed from a hierarchical Dirichlet process model. PLoS Computational Biology, 6, 1–21.
  • Ubersax, J. A., & Ferrell, J. E. (2007). Mechanisms of specificity in protein phosphorylation. Nature Reviews Molecular Cell Biology, 8, 530–541.
  • UniProt Consortium. (2011). Ongoing and future developments at the Universal Protein Resource. Nucleic Acids Research, 39, D214–D219.
  • Urruticoechea, A., Alemany, R., Balart, J., Villanueva, A., Vinals, F., & Capella, G. (2010). Recent advances in cancer therapy: An overview. Current Pharmaceutical Design, 16, 3–10.
  • Vadija, R., Mustyala, K. K., Nambigari, N., Dulapalli, R., Dumpati, R. K., Ramatenki, V., … Vuruputuri, U. (2016). Homology modeling and virtual screening studies of FGF-7 protein-a structure-based approach to design new molecules against tumor angiogenesis. Journal of Chemical Biology, 9, 69–78.
  • Vanommeslaeghe, K., Hatcher, E., Acharya, C., Kundu, S., Zhong, S., Shim, J., … Mackerell, A. D. (2010). CHARMM general force field: A force field for drug-like molecules compatable with the CHARMM all-atom additive biological force fields. Journal of Computational Chemistry, 31, 671–690.
  • Vignal, E., Blangy, A., Martin, M., Gauthier-Rouviere, C., & Fort, P. (2001). Kinectin is a key effector of RhoG microtubule dependent cellular activity. Molecular and Cellular Biology, 21, 8022–8034.
  • Vigorito, E., Billadeu, D. D., Savoy, D., McAdam, S., Doody, G., & Fort, P. (2003). RhoG regulates gene expression and the actin cytoskeleton in lymphocytes. Oncogene, 22, 330–342.
  • Vincent, S., Jeanteur, P., & Fort, P. (1992). Growth-regulated expression of rhoG, a new member of the ras homolog gene family. Molecular and Cellular Biology, 12, 3138–3148.
  • Wallach, I., & Lilien, R. (2011). Virtual decoy sets for molecular docking benchmarks. Journal of Chemical Information and Modeling, 51, 196–202.
  • Wang, Y., Xiao, J., Suzek, T. O., Zhang, J., Wang, J., & Bryant, S. H. (2009). PubChem: A public information system for analyzing bioactivities of small molecules. Nucleic Acids Research, 37, W623–W633.
  • Watts, K. S., Dalal, P., Murphy, R. B., Sherman, W., Friesner, R. A., & Shelley, J. C. (2010). ConfGen: A conformational search method for efficient generation of bioactive conformers. Journal of Chemical Information and Modeling, 50, 534–546.
  • Wei, Z., Kirk, E. H., Stephen, W. W., Richard, E. L., & James, M. B. (2009). A statistical framework to evaluate virtual screening. BMC Bioinformatics, 10, 1–13.
  • Wiederstein, M., & Sippl, M. J. (2007). ProSA-web interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Research, 35, W407–W410.
  • Wilson, K. F., Erickson, J. W., Antonyak, M. A., & Cerione, R. A. (2013). Rho GTPases and their roles in cancer metabolism. Trends in Molecular Medicine, 19, 74–82.
  • Yang, J., Roy, A., & Zhang, Y. (2013). Protein–ligand binding site recognition using complementary binding-specific substructure comparison and sequence profile alignment. Bioinformatics, 29, 2588–2595.

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