On docking, scoring and assessing protein-DNA complexes in a rigid-body framework

PLoS ONE

Volumn 7, Issue 2, 2012, Pages

  Parisien, Marc ^a   Freed, Karl F ^a   Sosnick, Tobin R ^a,b  

^a UNIVERSITY OF CHICAGO   (United States)

^b UNIVERSITY OF CHICAGO   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DNA; PROTEIN;

ACCURACY; ARTICLE; BASE PAIRING; CHEMICAL CONTEXT DISCREPANCY; CHEMICAL CONTEXT PROFILE; CHEMICAL MODEL; CONTROLLED STUDY; DNA CONFORMATION; DNA DETERMINATION; DNA PROTEIN COMPLEX; FALSE NEGATIVE RESULT; FALSE POSITIVE RESULT; MACHINE LEARNING; MOLECULAR DOCKING; PROTEIN ANALYSIS; PROTEIN CONFORMATION; PROTEIN DNA BINDING; PROTEIN DNA INTERACTION; RIGID BODY DOCKING; ROOT MEAN SQUARED DEVIATION; SCORING SYSTEM; STATISTICAL PARAMETERS; ALGORITHM; ARTIFICIAL INTELLIGENCE; BIOLOGY; CHEMISTRY; CONFORMATION; GENE VECTOR; GENETICS; HYDROGEN BOND; METHODOLOGY; PROTEIN BINDING; PROTEIN DATABASE; REPRODUCIBILITY; STATISTICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTATIONAL BIOLOGY; DATABASES, PROTEIN; DNA; GENETIC VECTORS; HYDROGEN BONDING; MODELS, STATISTICAL; NUCLEIC ACID CONFORMATION; PROTEIN BINDING; PROTEINS; REPRODUCIBILITY OF RESULTS;

EID: 84857675809     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0032647     Document Type: Article

References (55)

1. Das R, Andre I, Shen Y, Wu Y, Lemak A, et al. (2009) Simultaneous prediction of protein folding and docking at high resolution. Proc Natl Acad Sci U S A 106: 18978-18983.
2. Farwer J, Packer MJ, Hunter CA, (2006) Prediction of atomic structure from sequence for double helical DNA oligomers. Biopolymers 81: 51-61.
3. Parisien M, Major F, (2008) The MC-Fold and MC-Sym pipeline infers RNA structure from sequence data. Nature 452: 51-55.
4. Ding F, Sharma S, Chalasani P, Demidov VV, Broude NE, et al. (2008) Ab initio RNA folding by discrete molecular dynamics: from structure prediction to folding mechanisms. RNA 14: 1164-1173.
5. Jonikas MA, Radmer RJ, Laederach A, Das R, Pearlman S, et al. (2009) Coarse-grained modeling of large RNA molecules with knowledge-based potentials and structural filters. RNA 15: 189-199.
6. DeBartolo J, Colubri A, Jha AK, Fitzgerald JE, Freed KF, et al. (2009) Mimicking the folding pathway to improve homology-free protein structure prediction. Proc Natl Acad Sci U S A 106: 3734-3739.
7. MacCallum JL, Perez A, Schnieders MJ, Hua L, Jacobson MP, et al. (2011) Assessment of protein structure refinement in CASP9. pp. n/a-n/a Proteins: Structure, Function, and Bioinformatics.
8. Vitkup D, Melamud E, Moult J, Sander C, (2001) Completeness in structural genomics. Nat Struct Biol 8: 559-566.
9. Lee D, de Beer TA, Laskowski RA, Thornton JM, Orengo CA, (2011) 1,000 structures and more from the MCSG. BMC Struct Biol 11: 2.
10. Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, et al. (2000) The Protein Data Bank. Nucleic Acids Res 28: 235-242.
11. Glaser F, Steinberg DM, Vakser IA, Ben-Tal N, (2001) Residue frequencies and pairing preferences at protein-protein interfaces. Proteins 43: 89-102.
12. Luscombe NM, Laskowski RA, Thornton JM, (2001) Amino acid-base interactions: a three-dimensional analysis of protein-DNA interactions at an atomic level. Nucleic Acids Res 29: 2860-2874.
13. Lejeune D, Delsaux N, Charloteaux B, Thomas A, Brasseur R, (2005) Protein-nucleic acid recognition: statistical analysis of atomic interactions and influence of DNA structure. Proteins 61: 258-271.
14. Ritchie DW, (2008) Recent progress and future directions in protein-protein docking. Curr Protein Pept Sci 9: 1-15.
15. Lensink MF, Mendez R, Wodak SJ, (2007) Docking and scoring protein complexes: CAPRI 3rd Edition. Proteins 69: 704-718.
16. Gray JJ, (2006) High-resolution protein-protein docking. Curr Opin Struct Biol 16: 183-193.
17. Nie Y, Viola C, Bieniossek C, Trowitzsch S, Vijay-Achandran LS, et al. (2009) Getting a grip on complexes. Curr Genomics 10: 558-572.
18. van Dijk M, Bonvin AM, (2010) Pushing the limits of what is achievable in protein-DNA docking: benchmarking HADDOCK's performance. Nucleic Acids Res.
19. Perez-Cano L, Solernou A, Pons C, Fernandez-Recio J, (2010) Structural prediction of protein-RNA interaction by computational docking with propensity-based statistical potentials. Pac Symp Biocomput pp. 293-301.
20. Knegtel RM, Antoon J, Rullmann C, Boelens R, Kaptein R, (1994) MONTY: a Monte Carlo approach to protein-DNA recognition. J Mol Biol 235: 318-324.
21. Poulain P, Saladin A, Hartmann B, Prevost C, (2008) Insights on protein-DNA recognition by coarse grain modelling. J Comput Chem 29: 2582-2592.
22. Chen Y, Kortemme T, Robertson T, Baker D, Varani G, (2004) A new hydrogen-bonding potential for the design of protein-RNA interactions predicts specific contacts and discriminates decoys. Nucleic Acids Res 32: 5147-5162.
23. Liu Z, Mao F, Guo JT, Yan B, Wang P, et al. (2005) Quantitative evaluation of protein-DNA interactions using an optimized knowledge-based potential. Nucleic Acids Res 33: 546-558.
24. van Dijk M, Bonvin AM, (2008) A protein-DNA docking benchmark. Nucleic Acids Res 36: e88.
25. Katchalski-Katzir E, Shariv I, Eisenstein M, Friesem AA, Aflalo C, et al. (1992) Molecular surface recognition: determination of geometric fit between proteins and their ligands by correlation techniques. Proc Natl Acad Sci U S A 89: 2195-2199.
26. Gabb HA, Jackson RM, Sternberg MJ, (1997) Modelling protein docking using shape complementarity, electrostatics and biochemical information. J Mol Biol 272: 106-120.
27. Sternberg MJ, Gabb HA, Jackson RM, Moont G, (2000) Protein-protein docking. Generation and filtering of complexes. Methods Mol Biol 143: 399-415.
28. Wass MN, Fuentes G, Pons C, Pazos F, Valencia A, (2011) Towards the prediction of protein interaction partners using physical docking. Mol Syst Biol 7: 469.
29. Chin K, Sharp KA, Honig B, Pyle AM, (1999) Calculating the electrostatic properties of RNA provides new insights into molecular interactions and function. Nat Struct Biol 6: 1055-1061.
30. Ohlendorf DH, Matthew JB, (1985) Electrostatics and flexibility in protein-DNA interactions. Adv Biophys 20: 137-151.
31. Kondo J, Westhof E, (2011) Classification of pseudo pairs between nucleotide bases and amino acids by analysis of nucleotide-protein complexes. Nucleic Acids Res.
32. Bahadur RP, Zacharias M, Janin J, (2008) Dissecting protein-RNA recognition sites. Nucleic Acids Res 36: 2705-2716.
33. Rohs R, Jin X, West SM, Joshi R, Honig B, et al. (2010) Origins of Specificity in Protein-DNA Recognition. Annu Rev Biochem.
34. Andrabi M, Mizuguchi K, Sarai A, Ahmad S, (2009) Prediction of mono- and di-nucleotide-specific DNA-binding sites in proteins using neural networks. BMC Struct Biol 9: 30.
35. Seeman NC, Rosenberg JM, Rich A, (1976) Sequence-specific recognition of double helical nucleic acids by proteins. Proc Natl Acad Sci U S A 73: 804-808.
36. Fitzgerald JE, Jha AK, Colubri A, Sosnick TR, Freed KF, (2007) Reduced C(beta) statistical potentials can outperform all-atom potentials in decoy identification. Protein Sci 16: 2123-2139.
37. Kabsch W, (1976) Solution for Best Rotation to Relate 2 Sets of Vectors. Acta Crystallographica Section A 32: 922-923.
38. Sanner MF, Olson AJ, Spehner JC, (1996) Reduced surface: An efficient way to compute molecular surfaces. Biopolymers 38: 305-320.
39. Gong H, Hocky G, Freed KF, (2008) Influence of nonlinear electrostatics on transfer energies between liquid phases: charge burial is far less expensive than Born model. Proc Natl Acad Sci U S A 105: 11146-11151.
40. Shen MY, Sali A, (2006) Statistical potential for assessment and prediction of protein structures. Protein Sci 15: 2507-2524.
41. Gao M, Skolnick J, (2008) DBD-Hunter: a knowledge-based method for the prediction of DNA-protein interactions. Nucleic Acids Res 36: 3978-3992.
42. Xu B, Yang Y, Liang H, Zhou Y, (2009) An all-atom knowledge-based energy function for protein-DNA threading, docking decoy discrimination, and prediction of transcription-factor binding profiles. Proteins 76: 718-730.
43. Feliu E, Oliva B, (2010) How different from random are docking predictions when ranked by scoring functions? Proteins 78: 3376-3385.
44. Ahmad M, Gu W, Geyer T, Helms V, (2011) Adhesive water networks facilitate binding of protein interfaces. Nat Commun 2: 261.
45. Temiz NA, Camacho CJ, (2009) Experimentally based contact energies decode interactions responsible for protein-DNA affinity and the role of molecular waters at the binding interface. Nucleic Acids Res 37: 4076-4088.
46. Chan SL, Labute P, (2010) Training a scoring function for the alignment of small molecules. J Chem Inf Model 50: 1724-1735.
47. Mereghetti P, Kokh D, McCammon JA, Wade RC, (2011) Diffusion and association processes in biological systems: theory, computation and experiment. BMC Biophys 4: 2.
48. Jones S, Shanahan HP, Berman HM, Thornton JM, (2003) Using electrostatic potentials to predict DNA-binding sites on DNA-binding proteins. Nucleic Acids Res 31: 7189-7198.
49. Lu XJ, Olson WK, (2003) 3DNA: a software package for the analysis, rebuilding and visualization of three-dimensional nucleic acid structures. Nucleic Acids Res 31: 5108-5121.
50. Chuang GY, Kozakov D, Brenke R, Comeau SR, Vajda S, (2008) DARS (Decoys As the Reference State) potentials for protein-protein docking. Biophys J 95: 4217-4227.
51. Wilde M, Hategan M, Wozniak J, Clifford B, Katz D, et al. (2011) Swift: A language for distributed parallel scripting. Parallel Computing 37: 633-652.
52. Romero E, Sopena JM, (2008) Performing feature selection with multilayer perceptrons. Ieee Transactions on Neural Networks 19: 431-441.
53. Kennedy J, Eberhart R, (1995) Particle swarm optimization. Proc IEEE Int'l Conf on Neural Networks 4: 1942-1948.
54. Zhao XC, (2010) A perturbed particle swarm algorithm for numerical optimization. Applied Soft Computing 10: 119-124.
55. 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.