Structure-based target druggability assessment

Methods in Molecular Biology

Volumn 986, Issue , 2013, Pages 141-164

  Trosset, Jean Yves ^a   Vodovar, Nicolas ^a  

^a NONE

Author keywords

Drug targets; Druggability; Flo QXP; Hot spots; Pocketfinder; Protein cavity; Structure superimposition; Target promiscuity

Indexed keywords

ALGORITHM; ARTICLE; BINDING SITE; COMPUTER MODEL; CROSS REACTION; DRUG ANALYSIS; DRUG DETERMINATION; DRUG STRUCTURE; ENERGY; GEOMETRY; PHARMACOPHORE; PRIORITY JOURNAL; PROTEIN BINDING; PROTEIN PROTEIN INTERACTION; CHEMICAL STRUCTURE; CHEMISTRY; COMPUTER SIMULATION; DRUG DESIGN; DRUG DEVELOPMENT; DRUG EFFECT; METABOLISM; MOLECULARLY TARGETED THERAPY; PROTEIN TERTIARY STRUCTURE;

PROTEIN;

ALGORITHMS; BINDING SITES; COMPUTER SIMULATION; DRUG DESIGN; DRUG DISCOVERY; MODELS, MOLECULAR; MOLECULAR TARGETED THERAPY; PROTEIN BINDING; PROTEIN STRUCTURE, TERTIARY; PROTEINS;

MLCS; MLOWN;

EID: 84881251398     PISSN: 10643745     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-1-62703-311-4_10     Document Type: Article

References (109)

1. Sakharkar MK, Sakharkar KR (2007) Targetability of human disease genes. Curr Drug Disc Technol 4:48-58
2. Wyatt PG, Gilbert IH, Read KD et al (2011) Target validation: linking target and chemical properties to desired product profile. Curr Topics Med Chem 11:1275-1283
3. Taboureau O, Nielsen SK, Audouze K et al (2011) ChemProt: a disease chemical biology database. Nucleic Acids Res 39:D367-D372
4. Bender A, Young DW, Jenkins JL et al (2007) Chemogenomic data analysis: prediction of small-molecule targets and the advent of biologicalfingerprint. Comb Chem High Throughput Screen 10:719-731
5. Dixon SJ, Stockwell BR (2009) Identifying druggable disease-modifying gene products. Curr Opinion Chem Biol 13:549-555
6. Caffrey CR, Rohwer A, Oellien F et al (2009) A comparative chemogenomics strategy to predict potential drug targets in the metazoan pathogen, Schistosomamansoni. PloS One 4:e4413
7. Bredel M, Jacoby E (2004) Chemogenomics: an emerging strategy for rapid target and drug discovery. Nat Rev Gen 5:262-275
8. Li Q, Cheng T, Wang Y et al (2010) PubChem as a public resource for drug discovery. Drug Discov Today 15:1052-1057
9. Fauman EB, Rai BK, Huang ES (2011) Structure-based druggability assessment-identifying suitable targets for small molecule therapeutics. Curr Opin Chem Biol 15:463-468
10. Schmidtke P, Barril X (2010) Understanding and predicting druggability. A high-throughput method for detection of drug binding sites. J Med Chem 53:5858-5867
11. Huang N, Jacobson MP (2010) Binding-site assessment by virtual fragment screening. PloS One 5:e10109
12. Fuller JC, Burgoyne NJ, Jackson RM (2009) Predicting druggable binding sites at the protein- protein interface. Drug Discov Today 14:155-161
13. Sugaya N, Furuya T (2011) Dr. PIAS: an integrative system for assessing the druggability of protein-protein interactions. BMC Bioinformatics 9:12-50
14. Villoutreix BO, Bastard K, Sperandio O et al (2008) In silico-in vitro screening of protein- protein interactions: towards the next generation of therapeutics. Curr Pharm Biotechnol 9:103-122
15. Sperandio O, Reynès CH, Camproux AC et al (2010) Rationalizing the chemical space of protein-protein interaction inhibitors. Drug Discov Today 15:220-229
16. Panjkovich A, Daura X (2010) Assessing the structural conservation of protein pockets to study functional and allosteric sites: implications for drug discovery. BMC Struct Biol 10:9-33
17. Chène P (2008) Challenges in design of biochemical assays for the identification of small molecules to target multiple conformations of protein kinases. Drug Discov Today 13: 522-529
18. Pérot S, Sperandio O, Miteva MA et al (2010) Druggable pockets and binding site centric chemical space: a paradigm shift in drug discovery. Drug Discov Today 15:656-667
19. Morris RRJ, Najmanovich RRJ, Kahraman A et al (2005) Real spherical harmonic expansion coefficients as 3D shape descriptors for protein binding pocket and ligand comparisons. Bioinformatics (Oxford, England) 21: 2347-2355
20. Mak L, Grandison S, Morris RJ (2008) An extension of spherical harmonics to regionbased rotationally invariant descriptors for molecular shape description and comparison. J Mol Graph Model 26:1035-1045
21. Kleywegt GJ, Jones TA (1994) Detection, delineation, measurement and display of cavities in macromolecular structures. Acta Crystallogr D Biol Crystallogr 50:178-185
22. Poy F, Lepourcelet M, Shivdasani RA et al (2001) Structure of a human Tcf4-betacatenin complex. Nat Struct Biol 8: 1053-1057
23. Tagami S, Sekine S-I, Kumarevel T et al (2010) Crystal structure of bacterial RNA polymerase bound with a transcription inhibitor protein. Nature 468:978-982
24. Liang J, Edelsbrunner H, Woodward C (1998) Anatomy of protein pockets and cavities: measurement of binding site geometry and implications for ligand design. Protein Sci 7:1884-1897
25. Kawabata T, Go N (2007) Detection of pockets on protein surfaces using small and large probe spheres tofind putative ligand binding sites. Bioinformatics 529:516-529
26. Kawabata T (2010) Detection of multiscale pockets on protein surfaces using mathematical morphology. Proteins 78:1195-1211
27. Goodford PJ (1985) A computational procedure for determining energetically favorable binding sites on biologically important macromolecules. J Med Chem 28:849-857
28. Weisel M, Proschak E, Schneider G (2007) PocketPicker: analysis of ligand binding-sites with shape descriptors. Chem Central J 1:7-24
29. Tripathi A, Kellogg GE (2010) A novel and efficient tool for locating and characterizing protein cavities and binding sites. Proteins 78:825-842
30. Peters KP, Fauck J, Frömmel C (1996) The automatic search for ligand binding sites in proteins of known three-dimensional structure using only geometric criteria. J Mol Biol 256:201-213
31. Zhong S, MacKerell AD (2007) Binding response: a descriptor for selecting ligand binding site on protein surfaces. J Chem Inf Model 47:2303-2315
32. Binkowski TA, Naghibzadeh S, Liang J (2003) CASTp: computed atlas of surface topography of proteins. Bioinformatics 31:3352-3355
33. Petrek M, Otyepka M, Banás P et al (2006) CAVER: a new tool to explore routes from protein clefts, pockets and cavities. BMC Bioinformatics 7:316-325
34. Guilloux VL, Schmidtke P, Tuffery P (2009) Fpocket: an open source platform for ligand pocket detection. BMC Bioinformatics 11:1-11
35. Till MS, Ullmann GM (2010) McVol-a program for calculating protein volumes and identifying cavities by a Monte Carlo algorithm. J Mol Modeling 16:419-429
36. Brady GP, Stouten PF (2000) Fast prediction and visualization of protein binding pockets with PASS. J Comput Aided Mol Des 14: 383-401
37. Kalidas Y, Chandra N (2008) PocketDepth: a new depth based algorithm for identification of ligand binding sites in proteins. J Struct Biol 161:31-42
38. Nayal M, Honig B (2006) On the nature of cavities on protein surfaces: application to the identification of drug-binding sites. Proteins: Struct Funct Bioinformatics 63:892-906
39. Tseng YY, Dupree C, Chen ZJ et al (2009) SplitPocket: identification of protein functional surfaces and characterization of their spatial patterns. Nucleic Acids Res 37:W384-W389
40. Laskowski RA (1995) SURFNET: a program for visualizing molecular surfaces, cavities, and intermolecular interactions. J Mol Graphics 13:307-308
41. Huang B, Schroeder M (2006) LIGSITE csc: predicting ligand binding sites using the Connolly surface and degree of conservation. BMC Structural Biol 11:1-11
42. Kitchen DB, Decornez H, Furr JR et al (2004) Docking and scoring in virtual screening for drug discovery: methods and applications. Nat Rev Drug Discov 3:935-949
43. Harris R, Olson AJ, Goodsell DS (2008) Automated prediction of ligand-binding sites in proteins. Proteins 70:1506-1517
44. Halgren T (2007) New method for fast and accurate binding-site identification and analysis. Chem Biol Drug Design 69:146-148
45. An J, Totrov M, Abagyan R et al (2005) Pocketome via comprehensive identification and classification of ligand binding envelopes. Mol Cell Proteomics 4:752-761
46. Laurie ATR, Jackson RM (2005) Structural bioinformatics Q-SiteFinder: an energy-based method for the prediction of protein-ligand binding sites. Bioinformatics 21:1908-1916
47. Hernandez M, Ghersi D, Sanchez R (2009) SITEHOUND-web: a server for ligand binding site identification in protein structures. Nucleic Acids Res 37:W413-W416
48. Ruppert J, Welch W, Jain AN (1997) Automatic identification and representation of protein binding sites for molecular docking. Protein Sci 6:524-533
49. Lipinski C (2004) Lead- and drug-like compounds: the rule-of-five revolution. Drug Discov Today: Technologies 1:337-341
50. Zhang M-Q, Wilkinson B (2007) Drug discovery beyond the "rule-of-five". Curr Opinion Biotech 18:478-488
51. Hopkins AL, Groom CR (2002) The druggable genome. Nat Rev Drug Discov 1:727-730
52. Costa PR, Acencio ML, Lemke N (2010) A machine learning approach for genome-wide prediction of morbid and druggable human genes based on systems-level data. BMC Genomics 5(Suppl 11):S9
53. Lesburg CA, Cable MB, Ferrari E et al (1999) Crystal structure of the RNA-dependent RNA polymerase from hepatitis C virus reveals a fully encircled active site. Nat Struct Mol Biol 6:937-943
54. Salah E, Ugochukwu E, Barr AJ et al (2011) Crystal structures of ABL-related gene (ABL2) in complex with imatinib, tozasertib (VX-680), and a type I inhibitor of the triazolecarbothioamide class. J Med Chem 54:2359-2367
55. Abad-Zapatero C, Metz JT (2005) Ligand efficiency indices as guideposts for drug discovery. Drug Discov Today 10:464-469
56. Ghersi D, Sanchez R (2009) Improving accuracy and efficiency of blind protein-ligand docking by focusing on predicted binding sites. Proteins 74:417-24
57. Hopkins AL, Groom CR, Alex A (2004) Ligand efficiency: a useful metric for lead selection. Drug Discov Today 9:430-431
58. Bohacek RS, McMartin C (1992) Definition and display of steric, hydrophobic, and hydrogen bonding properties of ligand binding sites in proteins using Lee and Richards accessible surface: validation of a high-resolution graphical tool for drug design. J Med Chem 35: 1671-1684
59. Licata L, Briganti L, Peluso D et al (2011) MINT, the molecular interaction database: 2012 update. Nucleic Acids Res 40: D857-D861
60. Bourgeas R, Basse M-J, Morelli X et al (2010) Atomic analysis of protein-protein interfaces with known inhibitors: the 2P2I database. PloS One 5:e9598
61. Kozakov D, Hall DR, Chuang GY et al (2011) Structural conservation of druggable hot spots in protein-protein interfaces. Proc Natl Acad Sci USA 108:13528-13533
62. Trosset J-Y, Dalvit C, Knapp S et al (2006) Inhibition of protein-protein interactions: the discovery of druglike beta-catenin inhibitors by combining virtual and biophysical screening. Proteins 64:60-67
63. Fasolini M, Wu X, Flocco M et al (2003) Hot spots in Tcf4 for the interaction with betacatenin. J Biol Chem 278:21092-21098
64. Clackson T, Wells JA (1995) A hot spot of binding energy in a hormone-receptor interface. Science 267:383-386
65. Kuttner YY, Engel S (2011) Protein hot spots-the islands of stability. J Mol Biol 415:419-428
66. Wanner J, Fry DC, Peng Z et al (2011) Druggability assessment of protein-protein interfaces. Future Med Chem 3:2021-2038
67. Metz A, P fleger C, Kopitz H et al (2011) Hot spots and transient pockets: predicting the determinants of small-molecule binding to a protein-protein interface. J Chem Inf Model 52:120-133
68. Henrich S, Salo-Ahen OMH, Huang B et al. (2010) Computational approaches to identifying and characterizing protein binding sites for ligand design. J Mol Recognit 23:209-219.
69. McMartin C (2012) A geometry forcefield which converts low-resolution X-ray models to structures with properties found at ultra high resolution. Protein Sci 21:75-83
70. Knight ZA, Lin H, Shokat KM (2010) Targeting the cancer kinome through polypharmacology. Nat Rev Cancer 10:130-137
71. Hopkins AL (2008) Network pharmacology: the next paradigm in drug discovery. Nat Chem Biol 4:682-690
72. Chikhi R, Sael L, Kihara D (2010) Real-time ligand binding pocket database search using local surface descriptors. Proteins 78: 2007-2028
73. Das S, Kokardekar A, Breneman CM (2009) Rapid comparison of protein binding site surfaces with property encoded shape distributions. J Chem Inf Model 49:2863-2872
74. Ivanisenko VA, Pintus SS, Grigorovich DA et al (2004) PDBSiteScan: a program for searching for active, binding and posttranslational modification sites in the 3D structures of proteins. Nucleic Acids Res 32:W549-W554
75. Totrov M (2011) Ligand binding site superposition and comparison based on Atomic Property Fields: identification of distant homologues, convergent evolution and PDBwide clustering of binding sites. BMC Bioinformatics 12:S35
76. Gold ND, Jackson RM (2005) A searchable database for comparing protein-ligand binding sites for the analysis of structure-function relationships. J Chem Inf Model 46:736-742
77. Schmidtke P, Souaille C, Estienne F et al (2010) Large-scale comparison of four binding site detection algorithms. J Chem Inf Model 50:2191-2200
78. Feldman HJ, Labute P (2010) Pocket similarity: are alpha carbons enough? J Chem Inf Model 50:1466-1475
79. Fontaine F, Pastor M, Zamora I et al (2005) Anchor-GRIND:filling the gap between standard 3D QSAR and the GRid- INdependentdescriptors. J Med Chem 48: 2687-2694
80. Crivori P, Zamora I, Speed B et al (2004) Model based on GRID-derived descriptors for estimating CYP3A4 enzyme stability of potential drug candidates. J Comput Aided Mol Des 18:155-166
81. Baroni M, Cruciani G, Sciabola S et al (2007) A common reference framework for analyzing/ comparing proteins and ligands. Fingerprints for ligands and proteins (FLAP): theory and application. J Chem Inf Model 47:279-294
82. Ritchie DW, Venkatraman V (2010) Ultrafast FFT protein docking on graphics processors. Bioinformatics 26:2398-2405
83. Katchalski-Katzir E (1992) Molecular surface recognition: determination of geometricfit between proteins and their ligands by correlation techniques. Proc Natl Acad Sci 89:2195-2199
84. Brenke R, Kozakov D, Chuang G-Y et al (2009) Fragment-based identification of druggable "hot spots" of proteins using Fourier domain correlation techniques. Bioinformatics 25:621-627
85. Doppelt-Azeroual O, Moriaud F, Adcock SA et al (2009) A review of MED-SuMo applications. Infect Disord Drug Targets 9:344-357
86. Jambon M, Andrieu O, Combet C et al (2005) The SuMo server: 3D search for protein functional sites. Bioinformatics 21: 3929-3930
87. Moriaud F, Doppelt-Azeroual O, Martin L et al (2009) Computational fragment-based approach at PDB scale by protein local similarity. J Chem Inf Model 49:280-294
88. Doppelt-Azeroual O, Delfaud F, Moriaud F et al (2010) Fast and automated functional classification with MED-SuMo: an application on purine-binding proteins. Protein Sci 19:847-867
89. Schmitt S, Kuhn D, Klebe G (2002) A new method to detect related function among proteins independent of sequence and fold homology. J Mol Biol 323:387-406
90. Bartlett S, Beddard GS, Jackson RM et al (2005) Comparison of the ATP binding sites of protein kinases using conformationally diverse bisindolylmaleimides. Methods 127:11699-11708
91. Powers R, Copeland JC, Germer K et al (2006) Comparison of protein active site structures for functional annotation of proteins and drug design. Proteins 65:124-135
92. Kinoshita K, Furui J, Nakamura H (2002) Identification of protein functions from a molecular surface database, eF-site. J Struct Funct Genomics 2:9-22
93. Skolnick J, Brylinski M (2009) FINDSITE: a combined evolution/structure- based approach to protein function prediction. Brief Bioinform 10:378-391
94. Shulman-Peleg A, Shatsky M, Nussinov R et al (2008) MultiBind and MAPPIS: webservers for multiple alignment of protein 3D-binding sites and their interactions. Nucleic Acids Res 36:W260
95. Minai R, Matsuo Y, Onuki H et al (2008) Method for comparing the structures of protein ligand-binding sites and application for predicting protein-drug interactions. Proteins: Struct Funct Bioinformatics 72: 367-381
96. Ausiello G, Via A, Helmer-Citterich M (2005) Query3d: a new method for high-throughput analysis of functional residues in protein structures. BMC Bioinformatics 4(Suppl 6):S5
97. Schalon C, Surgand JS, Kellenberger E et al (2008) A simple and fuzzy method to align and compare druggable ligand-binding sites. Proteins: Struct Funct Bioinformatics 71:1755-1778
98. Brakoulias A, Jackson RM (2004) Towards a structural classification of phosphate binding sites in protein-nucleotide complexes: an automated all-against-all structural comparison using geometric matching. Proteins: Struct Funct Bioinformatics 56:250-260
99. Tomei L, Roussel A, Incitti I et al (1999) Crystal structure of the RNA-dependent RNA polymerase of hepatitis C virus. Proc Natl Acad Sci 23:13034-13039
100. Pons J-L, Labesse G (2009) @TOME-2: a new pipeline for comparative modeling of protein-ligand complexes. Nucleic Acids Res 37:W485-W491
101. Shulman-Peleg A, Nussinov R, Wolfson HJ (2004) Recognition of functional sites in protein structures. J Mol Biol 339:607-633
102. Zorn J, Wells J (2010) Turning enzymes on with small molecules. Nat Chem Biol 6:179-188
103. Hantschel O, Grebien F, Superti-furga G (2011) Targeting allosteric regulatory "Drugging the Undruggable" modules in oncoproteins. Cancer Res 2:829-830
104. Oberlin D, Scheraga HA (1998) B-spline method for energy minimization in grid-based molecular mechanics calculations. J Comp Chem 19:71-85
105. Trosset J-Y, Scheraga HA (1999) Prodock: software package for protein modeling and docking. J Comp Chem 20:412-427
106. Trosset J-Y, Scheraga HA (1999) Flexible docking simulations: scaled collective variable Monte Carlo minimization approach using Bezier splines, and comparison with a standard Monte Carlo algorithm. J Comp Chem 20:244-252
107. Roisman LC, Piehler J, Trosset JY et al (2001) Structure of the interferon-receptor complex determined by distance constraints from double- mutant cycles and flexible docking. Proc Natl Acad Sci U S A 98:13231-13236
108. Trosset JY, Scheraga HA (1998) Reaching the global minimum in docking simulations: a Monte Carlo energy minimization approach using Bezier splines. Proc Natl Acad Sci USA 95:8011-8015
109. McMartin C, Bohacek RS (1997) QXP: powerful, rapid computer algorithms for structure- based drug design. J Comput Aided Mol Des 11:333-344