Successful applications of in silico approaches for lead/drug discovery

In silico Lead Discovery

Volumn , Issue , 2011, Pages 163-175

  Bortolato, Andrea ^a   Perruccio, Francesca ^a   Moro, Stefano ^b  

^a SYNGENTA CROP PROTECTION AG   (Switzerland)

^b UNIVERSITY OF PADOVA   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84884429366     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.2174/978160805142711101010163     Document Type: Chapter

References (68)

1. Dobson, C.M. Chemical space and biology. Nature 2004, 432, 824-8.
2. Lipinski, C.; Hopkins, A. Navigating chemical space for biology and medicine. Nature 2004, 432(7019), 855-861.
3. Couzin, J. Cancer drugs. Smart weapons prove tough to design. Science 2002, 298(5593), 522-525.
4. Fishman, M.C.; Porter, J.A. Pharmaceuticals: a new grammar for drug discovery. Nature 2005, 437(7058), 491-493.
5. Flower, R.J. The development of COX2 inhibitors. Nat. Rev. Drug Discov. 2003, 2(3), 179-191.
6. Picot, D.; Loll, P.J.; Garavito, R.M. The X-ray crystal structure of the membrane protein prostaglandin H2 synthase-1. Nature 1994, 367(6460), 243-249.
7. Kurumbail, R.G.; Stevens, A.M.; Gierse, J.K.; McDonald, J.J.; Stegeman, R.A.; Pak, J.Y.; Gildehaus, D.; Miyashiro, J.M.; Penning, T.D.; Seibert, K.; Isakson, P.C.; Stallings, W.C. Structural basis for selective inhibition of cyclooxygenase-2 by anti-inflammatory agents. Nature 1996, 384(6610), 644-648.
8. Chavatte, P.; Farce, A. A computational view of COX-2 inhibition. Anticancer Agents Med. Chem. 2006, 6(3), 239-249.
9. Mitchell, J.A.; Warner, T.D. COX isoforms in the cardiovascular system: understanding the activities of non-steroidal antiinflammatory drugs. Nat. Rev. Drug Discov. 2006, 5(1), 75-86.
10. Topol, E.J. Failing the public health--rofecoxib, Merck, and the FDA. N. Engl. J. Med. 2004, 351(17), 1707-1709.
11. Okie, S. Raising the safety bar--the FDA's coxib meeting. N. Engl. J. Med. 2005, 352 (13), 1283-1285.
12. Cowan-Jacob, S.W.; Mobitz, H.; Fabbro, D. Structural biology contributions to tyrosine kinase drug discovery. Curr. Opin. Cell Biol. 2009, 21(2), 280-287.
13. Zhang, J.; Yang, P.L.; Gray, N.S. Targeting cancer with small molecule kinase inhibitors. Nat Rev Cancer 2009, 9(1), 28-39.
14. Bortolato, A.; Cozza, G.; Moro, S. Protein kinase CK2 inhibitors: emerging anticancer therapeutic agents? Anticancer Agents Med. Chem. 2008, 8(7), 798-806.
15. Cozza, G.; Bortolato, A.; Moro, S. How druggable is protein kinase CK2? Med. Res. Rev. 2010, 30(3), 419-462.
16. Battistutta, R.; De Moliner, E.; Sarno, S.; Zanotti, G.; Pinna, L.A. Structural features underlying selective inhibition of protein kinase CK2 by ATP site-directed tetrabromo-2-benzotriazole. Protein Sci. 2001, 10(11), 2200-2206.
17. Pagano, M.A.; Bain, J.; Kazimierczuk, Z.; Sarno, S.; Ruzzene, M.; Di Maira, G.; Elliott, M.; Orzeszko, A.; Cozza, G.; Meggio, F.; Pinna, L.A. The selectivity of inhibitors of protein kinase CK2: an update. Biochem. J. 2008, 415, (3), 353-365.
18. Battistutta, R.; Mazzorana, M.; Cendron, L.; Bortolato, A.; Sarno, S.; Kazimierczuk, Z.; Zanotti, G.; Moro, S.; Pinna, L.A. The ATP-binding site of protein kinase CK2 holds a positive electrostatic area and conserved water molecules. Chembiochem 2007, 8(15), 1804-1809.
19. Richter, S.; Wenzel, A.; Stein, M.; Gabdoulline, R.R.; Wade, R.C. webPIPSA: a web server for the comparison of protein interaction properties. Nucleic Acids Res. 2008, 36(Web Server issue), W276-80.
20. Bortolato, A.; Moro, S. In silico binding free energy predictability by using the linear interaction energy (LIE) method: bromobenzimidazole CK2 inhibitors as a case study. J. Chem. Inf. Model. 2007, 47(2), 572-582.
21. Aqvist, J.; Medina, C.; Samuelsson, J.E. A new method for predicting binding affinity in computer-aided drug design. Protein Eng. 1994, 7, (3), 385-391.
22. Chilin, A.; Battistutta, R.; Bortolato, A.; Cozza, G.; Zanatta, S.; Poletto, G.; Mazzorana, M.; Zagotto, G.; Uriarte, E.; Guiotto, A.; Pinna, L. A.; Meggio, F.; Moro, S. Coumarin as attractive casein kinase 2 (CK2) inhibitor scaffold: an integrate approach to elucidate the putative binding motif and explain structure-activity relationships. J. Med. Chem. 2008, 51(4), 752-759.
23. Cozza, G.; Bonvini, P.; Zorzi, E.; Poletto, G.; Pagano, M. A.; Sarno, S.; Donella-Deana, A.; Zagotto, G.; Rosolen, A.; Pinna, L. A.; Meggio, F.; Moro, S. Identification of ellagic acid as potent inhibitor of protein kinase CK2: a successful example of a virtual screening application. J. Med. Chem. 2006, 49(8), 2363-2366.
24. Miteva, M.A.; Lee, W.H.; Montes, M.O.; Villoutreix, B.O. Fast structure-based virtual ligand screening combining FRED, DOCK, and Surflex. J. Med. Chem. 2005, 48(19), 6012-6022.
25. Weisberg, E.; Manley, P.W.; Cowan-Jacob, S.W.; Hochhaus, A.; Griffin, J.D. Second generation inhibitors of BCR-ABL for the treatment of imatinib-resistant chronic myeloid leukaemia. Nat. Rev. Cancer. 2007, 7(5), 345-356.
26. Gambacorti-Passerini, C.B.; Gunby, R.H.; Piazza, R.; Galietta, A.; Rostagno, R.; Scapozza, L. Molecular mechanisms of resistance to imatinib in Philadelphia-chromosome-positive leukaemias. Lancet Oncol. 2003, 4(2), 75-85.
27. Yang, S.; Banavali, N.K.; Roux, B. Mapping the conformational transition in Src activation by cumulating the information from multiple molecular dynamics trajectories. Proc. Natl. Acad. Sci U S A 2009, 106(10), 3776-3781.
28. Berteotti, A.; Cavalli, A.; Branduardi, D.; Gervasio, F.L.; Recanatini, M.; Parrinello, M. Protein conformational transitions: the closure mechanism of a kinase explored by atomistic simulations. J. Am. Chem. Soc. 2009, 131(1), 244-250.
29. Berman, H.M.; Westbrook, J.; Feng, Z.; Gilliland, G.; Bhat, T.N.; Weissig, H.; Shindyalov, I.N.; Bourne, P.E. The Protein Data Bank. Nucleic Acids Res. 2000, 28(1), 235-242.
30. Angelo, M.; Plattner, F.; Giese, K.P. Cyclin-dependent kinase 5 in synaptic plasticity, learning and memory. J. Neurochem. 2006, 99(2), 353-370.
31. Branduardi, D.; Gervasio, F.L.; Parrinello, M. From A to B in free energy space. J. Chem. Phys. 2007, 126(5), 054103.
32. Laio, A.; Parrinello, M. Escaping free-energy minima. Proc. Natl. Acad. Sci. USA 2002, 99(20), 12562-12566.
33. Gloriam, D.E.; Fredriksson, R.; Schioth, H.B. The G protein-coupled receptor subset of the rat genome. BMC Genomics 2007, 8, 338.
34. Marinissen, M.J.; Gutkind, J.S. G-protein-coupled receptors and signaling networks: emerging paradigms. Trends Pharmacol. Sci. 2001, 22(7), 368-376.
35. Overington, J.P.; Al-Lazikani, B.; Hopkins, A.L. How many drug targets are there? Nat. Rev. Drug Discov. 2006, 5(12), 993-996.
36. Strange, P.G. Signaling mechanisms of GPCR ligands. Curr. Opin. Drug Discov. Devel. 2008, 11(2), 196-202.
37. Fishman, P.; Bar-Yehuda, S. Pharmacology and therapeutic applications of A3 receptor subtype. Curr. Top. Med. Chem. 2003, 3(4), 463-469.
38. Gessi, S.; Merighi, S.; Varani, K.; Leung, E.; Mac Lennan, S.; Borea, P.A. The A3 adenosine receptor: an enigmatic player in cell biology. Pharmacol. Ther. 2008, 117(1), 123-140.
39. Hasko, G.; Linden, J.; Cronstein, B.; Pacher, P. Adenosine receptors: therapeutic aspects for inflammatory and immune diseases. Nat. Rev. Drug Discov. 2008, 7(9), 759-770.
40. Kobilka, B.K.; Deupi, X. Conformational complexity of G-protein-coupled receptors. Trends Pharmacol. Sci. 2007, 28(8), 397-406.
41. Moro, S.; Deflorian, F.; Bacilieri, M.; Spalluto, G. Ligand-based homology modeling as attractive tool to inspect GPCR structural plasticity. Curr. Pharm. Des. 2006, 12(17), 2175-2185.
42. Moro, S.; Deflorian, F.; Spalluto, G.; Pastorin, G.; Cacciari, B.; Kim, S.K.; Jacobson, K.A. Demystifying the three dimensional structure of G protein-coupled receptors (GPCRs) with the aid of molecular modeling. Chem. Commun. (Camb) 2003, (24), 2949-2956.
43. Maconi, A.; Pastorin, G.; Da Ros, T.; Spalluto, G.; Gao, Z. G.; Jacobson, K.A.; Baraldi, P.G.; Cacciari, B.; Varani, K.; Moro, S.; Borea, P.A. Synthesis, biological properties, and molecular modeling investigation of the first potent, selective, and water-soluble human A(3) adenosine receptor antagonist. J. Med. Chem. 2002, 45(17), 3579-3582.
44. Pastorin, G.; Da Ros, T.; Spalluto, G.; Deflorian, F.; Moro, S.; Cacciari, B.; Baraldi, P.G.; Gessi, S.; Varani, K.; Borea, P.A. Pyrazolo[4,3-e]-1,2,4-triazolo[1,5-c]pyrimidine derivatives as adenosine receptor antagonists. Influence of the N5 substituent on the affinity at the human A 3 and A 2B adenosine receptor subtypes: a molecular modeling investigation. J. Med. Chem. 2003, 46(20), 4287-4296.
45. Colotta, V.; Catarzi, D.; Varano, F.; Calabri, F.R.; Lenzi, O.; Filacchioni, G.; Martini, C.; Trincavelli, L.; Deflorian, F.; Moro, S. 1,2,4-triazolo[4,3-a]quinoxalin-1-one moiety as an attractive scaffold to develop new potent and selective human A3 adenosine receptor antagonists: synthesis, pharmacological, and ligand-receptor modeling studies. J. Med. Chem. 2004, 47(14), 3580-3590.
46. Moro, S.; Braiuca, P.; Deflorian, F.; Ferrari, C.; Pastorin, G.; Cacciari, B.; Baraldi, P.G.; Varani, K.; Borea, P.A.; Spalluto, G. Combined target-based and ligand-based drug design approach as a tool to define a novel 3D-pharmacophore model of human A3 adenosine receptor antagonists: pyrazolo[4,3-e]1,2,4-triazolo[1,5-c]pyrimidine derivatives as a key study. J. Med. Chem. 2005, 48(1), 152-162.
47. Gao, Z.G.; Chen, A.; Barak, D.; Kim, S.K.; Muller, C.E.; Jacobson, K.A. Identification by site-directed mutagenesis of residues involved in ligand recognition and activation of the human A3 adenosine receptor. J. Biol. Chem. 2002, 277(21), 19056-19063.
48. Moro, S.; Deflorian, F.; Bacilieri, M.; Spalluto, G. Novel strategies for the design of new potent and selective human A3 receptor antagonists: an update. Curr. Med. Chem. 2006, 13(6), 639-645.
49. Casanola-Martin, G.M.; Marrero-Ponce, Y.; Tareq Hassan Khan, M.; Torrens, F.; Perez-Gimenez, F.; Rescigno, A. Atomand bond-based 2D TOMOCOMD-CARDD approach and ligand-based virtual screening for the drug discovery of new tyrosinase inhibitors. J. Biomol. Screen. 2008, 13(10), 1014-1024.
50. Ewing, T.; Baber, J.C.; Feher, M. Novel 2D fingerprints for ligand-based virtual screening. J Chem Inf Model 2006, 46(6), 2423-2431.
51. Kinnings, S.L.; Jackson, R.M. LigMatch: a multiple structure-based ligand matching method for 3D virtual screening. J. Chem. Inf. Model. 2009, 49(9), 2056-2066.
52. Perez-Nueno, V.I.; Ritchie, D.W.; Rabal, O.; Pascual, R.; Borrell, J.I.; Teixido, J. Comparison of ligand-based and receptor-based virtual screening of HIV entry inhibitors for the CXCR4 and CCR5 receptors using 3D ligand shape matching and ligand-receptor docking. J. Chem. Inf. Model. 2008, 48(3), 509-533.
53. Allen, F.H. The Cambridge Structural Database: a quarter of a million crystal structures and rising. Acta Crystallogr. B 2002, 58(Pt 3 Pt 1), 380-388.
54. Grant, J.A.; Gallardo, M.A.; Pickup, B.T. A fast method of molecular shape comparison: A simple application of a Gaussian description of molecular shape. J. Comp. Chem. 1996, 17(14), 1653-1666.
55. Rush, T.S., 3rd; Grant, J.A.; Mosyak, L.; Nicholls, A. A shape-based 3-D scaffold hopping method and its application to a bacterial protein-protein interaction. J. Med. Chem. 2005, 48(5), 1489-1495.
56. Hawkins, P.C.; Skillman, A.G.; Nicholls, A. Comparison of shape-matching and docking as virtual screening tools. J. Med. Chem. 2007, 50(1), 74-82.
57. Venhorst, J.; Nunez, S.; Terpstra, J.W.; Kruse, C.G. Assessment of scaffold hopping efficiency by use of molecular interaction fingerprints. J. Med. Chem. 2008, 51(11), 3222-3229.
58. Sheridan, R.P.; McGaughey, G.B.; Cornell, W.D. Multiple protein structures and multiple ligands: effects on the apparent goodness of virtual screening results. J. Comput. Aided Mol. Des. 2008, 22(3-4), 257-265.
59. Fan, Y.; Lai, M.H.; Sullivan, K.; Popiolek, M.; Andree, T.H.; Dollings, P.; Pausch, M.H. The identification of neurotensin NTS1 receptor partial agonists through a ligand-based virtual screening approach. Bio. Med. Chem. Lett. 2008, 18(21), 5789-5791.
60. Carraway, R.; Leeman, S.E. The isolation of a new hypotensive peptide, neurotensin, from bovine hypothalami. J. Biol. Chem. 1973, 248(19), 6854-6861.
61. Boules, M.; Shaw, A.; Fredrickson, P.; Richelson, E. Neurotensin agonists: potential in the treatment of schizophrenia. CNS Drugs 2007, 21(1), 13-23.
62. Barroso, S.; Richard, F.; Nicolas-Etheve, D.; Reversat, J.L.; Bernassau, J.M.; Kitabgi, P.; Labbe-Jullie, C. Identification of residues involved in neurotensin binding and modeling of the agonist binding site in neurotensin receptor 1. J. Biol. Chem. 2000, 275(1), 328-336.
63. Labbe-Jullie, C.; Barroso, S.; Nicolas-Eteve, D.; Reversat, J. L.; Botto, J.M.; Mazella, J.; Bernassau, J.M.; Kitabgi, P. Mutagenesis and modeling of the neurotensin receptor NTR1. Identification of residues that are critical for binding SR 48692, a nonpeptide neurotensin antagonist. J. Biol. Chem. 1998, 273(26), 16351-16357.
64. Pang, Y.P.; Cusack, B.; Groshan, K.; Richelson, E. Proposed ligand binding site of the transmembrane receptor for neurotensin(8-13). J. Biol. Chem. 1996, 271(25), 15060-15068.
65. Halgren, T.A. Merck molecular force field. I. Basis, form, scope, parameterization, and performance of MMFF94. J. Comp. Chem. 1996, 17.
66. Bostrom, J.; Greenwood, J.R.; Gottfries, J. Assessing the performance of OMEGA with respect to retrieving bioactive conformations. J. Mol. Graph. Model. 2003, 21(5), 449-462.
67. Nilakantan, R.; Bauman, N.; Dixon, J.S.; Venkataraghavan, R. Topological torsion: a new molecular descriptor for SAR applications. Comparison with other descriptors. J. Chem. Inf. Comp. Sci. 1987, 27(2), 82-85.
68. Carhart, R.E.; Smith, D.H.; Venkataraghavan, R. Atom pairs as molecular features in structure-activity studies: definition and applications. J. Chem. Inf. Comp. Sci. 1985, 25(2), 64-73.