Recent advances in De Novo design strategy for practical lead identification

Medicinal Research Reviews

Volumn 23, Issue 5, 2003, Pages 606-632

  Honma, Teruki ^a  

^a TAIHO PHARMACEUTICAL CO LTD   (Japan)

Author keywords

Cdk4; De novo design; Lead identification; SEEDS; Synthetic accessibility

Indexed keywords

CYCLIN DEPENDENT KINASE 4; CYCLIN DEPENDENT KINASE 4 INHIBITOR; CYCLIN DEPENDENT KINASE INHIBITOR; UNCLASSIFIED DRUG;

BINDING AFFINITY; CHEMICAL ANALYSIS; COMPUTER PROGRAM; DE NOVO DESIGN; MASS SPECTROMETRY; NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY; NUCLEAR OVERHAUSER EFFECT; PROTEIN ANALYSIS; PROTEIN STRUCTURE; REVIEW; VALIDATION PROCESS; X RAY ANALYSIS;

BINDING SITES; COMPUTER-AIDED DESIGN; DRUG DESIGN; HUMANS; LIGANDS; MAGNETIC RESONANCE SPECTROSCOPY; MASS SPECTROMETRY; MODELS, CHEMICAL; MODELS, MOLECULAR; MOLECULAR STRUCTURE; PROTEIN BINDING; SOFTWARE; THERMODYNAMICS; X-RAYS;

EID: 0041418274     PISSN: 01986325     EISSN: None     Source Type: Journal    
DOI: 10.1002/med.10046     Document Type: Review

References (88)

1. Jimenez G, Childs B, Valle D. Human disease genes. Nature 2001;409:853-855.
2. Drews J. Drug discovery today and tomorrow. Drug Discov Today 2000;5:2-4.
3. Drews J. Drug discovery: A historical perspective. Science 2000;287:1960-1964.
4. Campbell SF. Science, art and drug discovery: A personal perspective. Clin Sci 2000;99:255-260.
5. Carr R, Jhoti H. Structure-based screening of low affinity compounds. Drug Discov Today 2002;7:522-527.
6. Bohacek RS, Martin C, Guida WC. Med Res Rev 1996;16:3-50.
7. Murcko MA. An introduction to de novo ligand design. In: Charifson PS, editor. Practical application of computer-aided drug design. New York: Marcel Dekker; 1997. p 304-354.
8. Nishibata Y, Itai A. Automatic creation of drug candidate structures based on receptor structure. Starting point for artificial lead generation. Tetrahedron 1991;47:8985-8990.
9. Nishibata Y, Itai A. Confirmation of usefulness of a structure construction program based on three-dimensional receptor structure for rational lead generation. J Med Chem 1993;36:2921-2928.
10. Bohm HJ. The computer program LUDI: A new method for the de novo design of enzyme inhibitors. J Comput Aided Mol Design 1992;6:61-78.
11. Bohm HJ. LUDI: Rule-based automatic design of new substituents for enzyme inhibitor leads. J Comput Aided Mol Design 1992;6:593-606.
12. Gillet VJ, Johnson AP, Mata P, Sike S, Williams P. SPROUT: A program for structure generation. J Comput Aided Mol Design 1993;7:127-153.
13. Eisen MB, Wiley DC, Karplus M, Hubbard RE. HOOK: A program for finding novel molecular architectures that satisfy the chemical and steric requirements of a macromolecule binding site. Proteins Struct Funct Genet 1994;19:199-221.
14. Bohacek RS, McMartin C. Multiple highly diverse structures complementary to enzyme binding sites: Results of extensive application of de novo design method incorporating combinatorial growth. J Am Chem Soc 1994;116:5560-5571.
15. Clark DE, Frenkel D, Levy SA, Li J, Murray CW, Robson B, Waszkowycz B, Westhead DR. PRO-LIGAND: An approach to de novo molecular design. 1. Application to the design of organic molecules. J Comput Aided Mol Design 1995;9:13-32.
16. Pearlman DA, Murcko MA. CONCERTS - dynamic connection of fragments as an approach to de-novo ligand design. J Med Chem 1996;39:1651-1663.
17. LeapFrog Manual. SYBYL version 6.8, St. Louis, MO: Tripos, Inc.
18. Honma T, Hayashi K, Aoyama T, Hashimoto N, Machida T, Fukasawa K, Iwama T, Ikeura C, Ikuta M, Suzuki-Takahashi I, Iwasawa Y, Hayama T, Nishimura S, Morishima H. Structure-based generation of a new class of potent Cdk4 inhibitors: New de novo design strategy and library design. J Med Chem 2001;44:4615-4627.
19. Desjarlais RL. Generation and use of three-dimensional databases for drug discovery. In: Charifson PS, editor. Practical application of computer-aided drug design. New York: Marcel Dekker; 1997. p 75-90.
20. Good AC, Mason JS. Three-dimensional structure database searches. In: Lipkowitz KB, Boyd DB, editors. Reviews in computational chemistry. New York: VCH Publishers, Inc; 1996. p 67-117.
21. Babine RE, Bleckman TM, Kissinger CR, Showalter R, Pelletier LA, Lewis C, Tucker K, Moomaw E, Parge HE, Villafranca JE. Design, synthesis and X-ray crystallographic studies of novel FKBP-12 ligands. Bioorg Med Chem Lett 1995;5:1719-1724.
22. Iwata Y, Naito S, Itai A, Miyamoto S. Protein structure-based de novo design and synthesis of aldose reductase inhibitors. Drug Des Discov 2001;17:349-359.
23. Murcko A, Murcko MA, Stouten PF. Recent advances in the prediction of binding free energy. In: Charifson PS, editor. Practical application of computer-aided drug design. New York: Marcel Dekker; 1997. p 355-410.
24. Kollman PA. Free energy calculations - Applications to chemical and biochemical phenomena. Chem Rev 1993;93:2395-2417.
25. Kollman PA. Calculating structures and free energies of complex molecules: Combining molecular mechanics and continuum models. Acc Chem Res 2000;33:889-897.
26. Zou X, Sun Y, Kuntz ID. Inclusion of solvation in ligand binding free energy calculations using the generalized-Born mdoel. J Am Chem Soc 1999;121:8033-8043.
27. Hansson T, Marelius J, Aqvist J. Ligand binding affinity prediction by linear interaction energy methods. J Comput Aided Mol Des 1998;12:27-35.
28. Kuntz ID, Blaney JM, Oatley SJ, Langridge R, Ferrin TE. A geometric approach to macromolecule-ligand interactions. J Mol Biol 1982;161:269-288.
29. Gohlke H, Klebe G. Statistical potentials and scoring functions applied to protein-ligand binding. Curr Opin Struct Biol 2001;11:231-235.
30. Morris GM, Goodsell DS, Halliday RS, Huey R, Hart WE, Belew RK, Olson AJ. Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function. J Comput Chem 1998;19:1639-1662.
31. Boehm HJ. The development of a simple empirical scoring function to estimate the binding constant for a protein-ligand complex of known three-dimensional structure. J Comput Aided Mol Design 1994;8:243-256.
32. Boehm HJ. Prediction of binding constants of protein ligands: A fast method for the prioritization of hits obtained from de novo desgn or 3D database search program. J Comput Aided Mol Design 1998;12:309-323.
33. Rarey M, Kramer B, Lengauer T, Klebe G. A fast flexible docking method using an incremental construction algorithm. J Mol Biol 1996;261:470-489.
34. Eldridge MD, Murray CW, Auton TR, Paolini GV, Mee RP. Empirical scoring functions: I. The development of a fast empirical scoring function to estimate the binding affinity of ligands in receptor complexes. J Comput Aided Mol Design 1997;11:425-445.
35. Muegge I, Martin YC. A general and fast scoring function for protein-ligand interactions: A simplified potential approach. J Med Chem 1999;42:791-804.
36. Gohlke H, Hendlich M, Klebe G. Predicting biding modes, binding affinities and 'hot spots' for protein-ligand complexes using a knowledge-based scoring function. Perspect Drug Discov Des 2000;20:115-144.
37. Holloway MK, Wai JM, Halgren TA, Fitzgerald PM, Vacca JP, Dorsey BD, Levin RB, Thompson WJ, Chen LJ, de-Solms SJ, Gaffin N, Ghosh AK, Giuliani EA, Graham SL, Guare JP, Hungate RW, Lyle TA, Sanders WM, Tucker TJ, Wiggins M, Wiscount CM, Woltersdorf OW, Young SD, Darke PL, Zugay JA. A priori prediction of activity for HIV-1 protease inhibitors employing energy minimization in the active site. J Med Chem 1995;38:305-317.
38. Wang T, Wade RC. Comparative binding energy (COMBINE) analysis of influenza neuraminidase-inhibitor complexes. J Med Chem 2001;44:961-971.
39. Gohlke H, Klebe G. Drug score meets CoMFA: Adaptation of fields for molecular comparison (AFMoC) or how to tailor knowledge-based pair-potentials to a particular protein. J Med Chem 2002;45:4153-4170.
40. Wyss DF, McCoy MA, Senior MM. NMR-based approaches for drug discovery. Curr Opin Drug Discov Dev 2002;5:630-647.
41. Shuker SB, Hajduk PJ, Meadows RP, Fesik SW. Discovering high-affinity ligands for proteins: SAR by NMR. Science 1996;274:1531-1534.
42. Hajduk PJ, Dinges J, Miknis GF, Merlock M, Middleton T, Kempf DJ, Egan DA, Walter KA, Robins TS, Shuker SB, Holtzman TF, Fesik SW. NMR-based discovery of lead inhibitors that block DNA binding of the human papillomavirus E2 protein. J Med Chem 1997;40:3144-3150.
43. Hajduk PJ, Sheppard G, Nettesheim DG, Olejniczak ET, Shuker SB, Meadows RP, Steinman DH, Carrera GM, Marcotte PA, Severin J, Walter K, Smith H, Gubbins E, Simmer R, Hotzman TF, Morgan DW, Davidsen SK, Summers JB, Fesik SW. Discovery of potent nonpeptide inhibitors of stromelysin using SAR by NMR. J Am Chem Soc 1997;119:5818-5827.
44. Hajduk PJ, Dinges J, Schkeryantz JM, Janowick D, Kaminski M, Tufano M, Augeri DJ, Petros A, Nienaber V, Zhong P, Hammond R, Coen M, Beutel B, Katz L, Fesik SW. Novel inhibitors of Erm methyltransferases from NMR and paralles synthesis. J Med Chem 1999;42:3852-3859.
45. Hajduk PJ, Boyd S, Nettesheim D, Nienaber V, Severin J, Smith R, Davidson D, Rockway T, Fesik SW. Identification of novel inhibitors of Urokinase via NMR-based screening. J Med Chem 2000;43:3862-3866.
46. Hajduk PJ, Gomtsyan A, Didomenico S, Cowart M, Bayburt EK, Solomon L, Severin J, Smith R, Walter K, Holtzman TF, Stewart A, McGaraughty S, Jarvis MF, Kowaluk EA, Fesik SW. Design of adenosine kinase inhibitors from the NMR-based screening of fragments. J Med Chem 2000;43:4781-4786.
47. Hajduk PJ, Bures M, Praestgaard J, Fesik SW. Privileged molecules for protein binding identified from NMR-based screening. J Med Chem 2000;43:3443-3447.
48. 13C-labeled methyl groups. J Am Chem Soc 2000;122:7898-7904.
49. Hajduk PJ, Gerfin T, Boehlen JM, Haeberli M, Marek D, Fesik SW. High-throughput nuclear magnetic resonance-based screening. J Med Chem 1999;42:2315-2317.
50. Fejzo J, Lepre CA, Peng JW, Bemis GW, Murcko A, Murcko MA, Moore JM. The SHAPES strategy: An NMR-based approach for lead generation in drug discovery. Chem Biol 1999;6:755-769.
51. Moore JM, Fejzo J, Lepre CA, Peng JW, Abdul-Manan N. Applications of NMR SHAPES screening in drug discovery. Am Chem Soc 2001, 221st MEDI-217 (abstract paper).
52. Niimi T, Orita M, Okazawa-Igarashi M, Sakashita H, Kikuchi K, Ball E, Ichikawa A, Yamagiwa Y, Sakamoto S, Tanaka A, Tsukamoto S, Fujita S, Tatsuta K, Maeda Y, Chikauchi K. Design and synthesis of non-peptidic inhibitors for the Syk C-terminal SH2 domain based on structure-based in-silico screening. J Med Chem 2001;44:4737-4740.
53. Mayer M, Meyer B. Mapping the active site of angiotensin-converting enzyme by transferred NOE spectroscopy. J Med Chem 2000;43:2093-2099.
54. Boehm HJ, Boehringer M, Bur D, Gmuender H, Huber W, Klaus W, Kostrewa D, Kuehne H, Luebbers T, Meunier-Keller N, Mueller F. Novel inhibitors of DNA gyrase: 3D structure based biased needle screening, hit validation by biophysical methods, and 3D guided optimization. A promising alternative to random screening. J Med Chem 2000;43:2664-2674.
55. Nienaber VL, Richardson PL, Klighofer V, Bouska JJ, Giranda VL, Greer J. Discovering novel ligands for macromolecules using X-ray crystallographic screening. Nat Biotechnol 2000;18:1105-1108.
56. Swayze EE, Jefferson EA, Sannes-Lowery KA, Blyn LB, Risen LM, Arakawa S, Osgood SA, Hofstadler SA, Griffey RH. SAR by MS: A ligand based technique for drug lead discovery against structured RNA targets. J Med Chem 2002;45:3816-3819.
57. Gillet VJ, Myatt G, Zsoldos Z, Johnson AP. SPROUT, HIPPO and CAESA: Tools for de novo structure generation and estimation of synthetic accessibility. Perspect Drug Discov Desi 1995;3:34-50.
58. Iwama T, Honma T, Ikeura C, Funabashi H, Morishima H. SEEDS: System for evaluation of availability of essential structures generated by de novo ligand design programs (unpublished results).
59. Database searches were carried out using ISIS/base. In ISIS/base, the author can assign the atom list, ring bond count, and substitution count to each atom, and also assign the bond list to each bond when he makes queries for searching compound databases. In addition, the reaction center can be assigned to each bond when he makes queries for searching reaction databases. The atom list and bond list indicate atomic species and bond orders that are allowed. The ring bond count shows numbers of additional rings that are allowed. The substitution count indicates numbers of additional substituents that are allowed. The reaction center is the changing pattern of the bond between the reactant and the product on searching reaction databases.
60. ISIS/base. MDL Information Systems, San Leandro CA.
61. Honma T, Yoshizumi T, Hashimoto N, Hayashi K, Kawanishi N, Fukasawa K, Takaki T, Ikeura C, Ikuta M, Suzuki-Takahashi I, Hayama T, Nishimura S, Morishima H. A novel approach for the development of selective Cdk4 inhibitors: Library design based on loactions of Cdk4 specific amino acid residues. J Med Chem 2001;44:4628-4640.
62. Pines J. Cyclins and cyclin dependent kinases: Take your partners. Trends Biochem Sci 1993;18:195-197.
63. Sherr CJ. D-type cyclins. Trends Biochem Sci 1995;20:187-190.
64. Taya Y. Cell cycle-dependent phosphorylation of the tumor suppressor RB protein. Mol Cells 1995;5:191-195.
65. Kamb A. Cell-cycle regulators and cancer. Trends Genet 1995;11:136-140.
66. Russo AA, Tong L, Lee JO, Jeffrey PD, Pavletich NP. Structural basis for inhibition of the cyclin dependent kinase Cdk6 by the tumor suppressor p16INK4a. Nature 1998;395:237-243.
67. Jeffrey PD, Tong L, Pavletich NP. Structural basis of inhibition of CDK-cyclin complexes by INK4 inhibitors. Genes Dev 2000;14:3115-3125.
68. Brotherton DH, Dhanaraj V, Wick S, Leonardo B, Domaille PJ, Volyanik E, Xu X, Parisini E, Smith BO, Archher SJ, Serrano M, Brenner SL, Blundell TL, Laue ED. Crystal structure of the complex of the cyclin D-dependent kinase Cdk6 bound to the cell-cycle inhibitor p19INK4d. Nature 1998;395:244-250.
69. De Bondt HL, Rosenblatt J, Jancarik J, Jones HD, Morgan DO, Kim SH. Crystal structure of cyclin dependent kinase 2. Nature 1993;363:595-602.
70. Jeffrey PD, Russo AA, Polyak K, Gibbs E, Hurwitz J, Massague J, Pavletich NP. Mechanism of CDK activation revealed by the structure of a cyclin A-CDK2 complex. Nature 1995;376:313-320.
71. Russo AA, Jeffrey PD, Pavletich NP. Structural basis of cyclin dependent kinase activation by phosphorylation. Nat Struct Biol 1996;3:696-700.
72. Pavletich NP. Mechanism of cyclin dependent kinase regulation: Structures of Cdks, their cyclin activators, and cip and ink4 inhibitors. J Mol Biol 1999;287:821-828.
73. http://www.nih.go.jp/mirror/Kinases/pkr/pk_catalytic/ pk_hanks_seq_align_long.html/
74. Hanks SK, Quinn AM, Hunter T. The protein kinase family: Conserved features and deduced phylogeny of the catalytic domains. Science 1988;241:42-52.
75. Hanks SK, Quinn AM. Protein kinase catalytic domain sequence database: Identification of conserved features of primary structure and classification of family members. Methods Enzymol 1991;200:38-62.
76. Hanks SK, Hunter T. Protein kinases 6. The eukaryotic protein kinase superfamily: Kinase (catalytic) domain structure and classification. FASEB J 1995;9:576-596.
77. BIOCES[E] developed by NEC Co., Tokyo, Japan.
78. Brooks BR, Bruccoleri RE, Olafson BD, States DJ, Swaminathan S, Karplus M. CHARMM: A program for macromolecular energy, minimization, and dynamic calculation. J Comput Chem 1983;4:187-217.
79. de Azevedo WF, Mueller-Dieckmann HJ, Schulze-Gahmen U, Worland PJ, Sausville E, Kim SH. Structural basis for specificity and potency of a flavonoid inhibitor of human CDK2, a cell cycle kinase. Proc Natl Acad Sci USA 1996;93:2735-2740.
80. Lawrie AM, Noble MEM, Tunnah P, Brown NR, Johnson LN, Endicott JA. Protein kinase inhibition by staurosporine revealed in details of the molecular interaction with CDK2. Nat Struct Biol 1997;4:796-801.
81. The available chemicals directory distributed by MDL Information Systems, San Leandro CA.
82. Ikuta M, Kamata K, Fukasawa K, Honma T, Machida T, Hirai H, Suzuki-Takahashi I, Hayama T, Nishimura S. Crystallographic approach to identification of cyclin dependent kinase 4 (CDK4) specific inhibitors by using CDK4 mimic CDK2 protein. J Biol Chem 2001;276:27548-27554.
83. Chen JM, Nelson FC, Levin JI, Mobilio D, Moy FJ, Nilakantan R, Zask A, Powers R. Structure-based design of a novel, potent, and selective inhibitor for MMP-13 utilizing NMR spectroscopy and computer-aided molecular design. J Am Chem Soc 2000;122:9648-9654.
84. Iversen LF, Andersen HS, Branner S, Mortensen SB, Peters GH, Norris K, Olsen OH, Jeppesen CB, Lundt BF, Ripka W, Moller KB, Moller NPH. Structure-based design of a low molecular weight, nonphosphorus, nonpeptide, and highly selective inhibitor of protein-tyrosine phosphatase 1B. J Biol Chem 2000;275:10300-10307.
85. Bayly CI, Black WC, Leger S, Ouimet N, Ouellet M, Percival MD. Structure-based design of COX-2 selectivity into flurbiprofen. Bioorg Med Chem Lett 1999;9:307-312.
86. Kurumbail RG, Stevens AM, Gierse JK, McDonald JJ, Stegeman RA, Pak JY, Gildehaus D, Miyashiro JM, Penning TD, Seibert K, Isakson PC, Stallings WC. Structural basis for selective inhibition of cyclooxygenase-2 by anti-inflammatory agents. Nature 1996;384:644-648.
87. Toledo LM, Lydon NB, Elbaum D. The structure-based design of ATP-site directed protein kinase inhibitors. Curr Med Chem 1999;6:775-805.
88. Medema RH, Herrera RE, Lam F, Weinberg RA. Growth suppression by p16ink4 requires functional retinoblastoma protein. Proc Natl Acad Sci USA 1995;92:6289-6293.