Prediction of protein interaction hot spots using rough set-based multiple criteria linear programming

Journal of Theoretical Biology

Volumn 269, Issue 1, 2011, Pages 174-180

  Chen, Ruoying ^a,b   Zhang, Zhiwang ^c   Wu, Di ^d   Zhang, Peng ^e   Zhang, Xinyang ^b   Wang, Yong ^f   Shi, Yong ^b,g  

^a UNIVERSITY OF CHINESE ACADEMY OF SCIENCES   (China)

^b INSTITUTE OF GEOLOGY AND GEOPHYSICS   (China)

^c LUDONG UNIVERSITY   (China)

^d TONGJI UNIVERSITY   (China)

^e INSTITUTE OF COMPUTING TECHNOLOGY   (China)

^f CHINESE ACADEMY OF SCIENCES   (China)

^g UNIVERSITY OF NEBRASKA AT OMAHA   (United States)

Author keywords

Alanine mutation; Binding free energy; Combined model; Predictive performance; Residue's features

Indexed keywords

ALANINE; ANGIOGENIN; BETA CATENIN; BLOOD CLOTTING FACTOR 7A; CHYMOTRYPSIN; COLICIN; GA BINDING PROTEIN; GROWTH HORMONE; GUANINE NUCLEOTIDE EXCHANGE FACTOR; INTERLEUKIN 4; NEUROTROPHIN; PHENYLALANINE; THROMBIN; TRYPTOPHAN; TYROSINE; UBIQUITIN PROTEIN LIGASE E3; UROKINASE;

AMINO ACID; BENCHMARKING; BIOLOGY; DATA SET; EXPERIMENTAL STUDY; LINEAR PROGRAMING; MODELING; MUTATION; PROTEIN;

ARTICLE; BAYES THEOREM; DECISION TREE; MATHEMATICAL COMPUTING; PREDICTION; PRIORITY JOURNAL; PROTEIN PROTEIN INTERACTION; SYSTEM ANALYSIS;

AMINO ACIDS; ANIMALS; BAYES THEOREM; DATABASES, PROTEIN; DECISION TREES; HUMANS; MUTATION; PROGRAMMING, LINEAR; PROTEIN BINDING; PROTEIN INTERACTION MAPPING;

EID: 78049476225     PISSN: 00225193     EISSN: 10958541     Source Type: Journal    
DOI: 10.1016/j.jtbi.2010.10.021     Document Type: Article

References (57)

1. Almlof M., Aqvist J., Smalas A.O., Brandsdal B.O. Probing the effect of point mutations at protein-protein interfaces with free energy calculations. Biophys. J. 2006, 90:433-442.
2. Altschul S.F., Gish W., Miller W., Myers E.W., Lipman D.J. Basic local alignment search tool. J. Mol. Biol. 1990, 215:403-410.
3. Altschul S.F., Madden T.L., Schaffer A.A., Zhang J., Zhang Z., Miller W., Lipman D.J. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 1997, 25:3389-3402.
4. Bogan A.A., Thorn K.S. Anatomy of hot spots in protein interfaces. J. Mol. Biol. 1998, 280:1-9.
5. Bernstein F.C., Koetzle T.F., Williams G.J., Meyer E.F., Brice M.D., Rodgers J.R., Kennard O., Shimanouchi T., Tasumi M. The Protein Data Bank: a computer-based archival file for macromolecular structures. Arch. Biochem. Biophys. 1978, 185:584-591.
6. 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, 28:235-242.
7. Bhatt R.B., Gopal M. On fuzzy-rough sets approach to feature selection. Pattern Recognition Lett. 2005, 26:965-975.
8. Chakrabarti P., Janin J. Dissecting protein-protein recognition sites. Proteins 2002, 47:334-343.
9. Clackson T., Wells J.A. A hot spot of binding energy in a hormone-receptor interface. Science 1995, 267:383-386.
10. Cho K.I., Kim D., Lee D. A feature-based approach to modeling protein-protein interaction hot spots. Nucleic Acids Res. 2009, 37:2672-2687.
11. DeLano W.L. Unraveling hot spots in binding interfaces: progress and challenges. Curr. Opin. Struct. Biol. 2002, 12:14-20.
12. Darnell S.J., Page D., Mitchell J.C. An automated decision-tree approach to predicting protein interaction hot spots. Proteins 2007, 68:813-823.
13. Desrosiers D.C., Peng Z.Y. A binding free energy hot spot in the ankyrin repeat protein GABPbeta mediated protein-protein interaction. J. Mol. Biol. 2005, 354:375-384.
14. Eletr Z.M., Kuhlman B. Sequence determinants of E2-E6AP binding affinity and specificity. J. Mol. Biol. 2007, 369:419-428.
15. Fischer T.B., Arunachalam K.V., Bailey D., Mangual V., Bakhru S., Russo R., Huang D., Paczkowski M., Lalchandani V., Ramachandra C., Ellison B., Galer S., Shapley J., Fuentes E., Tsai J. The binding interface database (BID): a compilation of amino acid hot spots in protein interfaces. Bioinformatics 2003, 19:1453-1454.
16. Fasolini M., Wu X., Flocco M., Trosset J.Y., Oppermann U., Knapp S. Hot spots in Tcf4 for the interaction with beta-catenin. J. Biol. Chem. 2003, 278:21092-21098.
17. Freed N., Glover F. Simple but powerful goal programming models for discriminant problems. EUROP. J. OPER. RES. 1981, 7:44-60.
18. Freed N., Glover F. Evaluating alternative linear programming models to solve the two-group discriminant problem. Decision Sci. 1986, 17:1-62.
19. Guney E., Tuncbag N., Keskin O., Gursoy A. HotSprint: database of computational hot spots in protein interfaces. Nucleic Acids Res. 2008, 36:D662-D666.
20. Gardsvoll H., Gilquin B., Le M.H., Menez Du, A., Jorgensen T.J., Ploug M. Characterization of the functional epitope on the urokinase receptor. Complete alanine scanning mutagenesis supplemented by chemical cross-linking. J. Biol. Chem. 2006, 281:19260-19272.
21. Gelinas A.D., Toth J., Bethoney K.A., Stafford W.F., Harrison C.J. Mutational analysis of the energetics of the GrpE.DnaK binding interface: equilibrium association constants by sedimentation velocity analytical ultracentrifugation. J. Mol. Biol. 2004, 339:447-458.
22. Hubbard S.J.a.T., NACCESS J.M. Computer Program 1993, University of Manchester, UK.
23. Jones S., Thornton J.M. Analysis of protein-protein interaction sites using surface patches. J. Mol. Biol. 1997, 272:121-132.
24. Jensen F.V. An Introduction to Bayesian Networks 1996, UCL Press, London.
25. Keskin O., Ma B., Nussinov R. Hot regions in protein-protein interactions: the organization and contribution of structurally conserved hot spot residues. J. Mol. Biol. 2005, 345:1281-1294.
26. Kortemme T., Baker D. A simple physical model for binding energy hot spots in protein-protein complexes. Proc. Natl. Acad. Sci. USA 2002, 99:14116-14121.
27. Kou G., Liu X., Peng Y., Shi Y., Wise M., Xu W. Multiple criteria linear programming approach to data mining: models, algorithm designs and software development. Optim. Methods Software 2003, 18:453-473.
28. Kryszkiewicz M. Rough set approach to incomplete information systems. Inf. Sci. 1998, 112:39-49.
29. Komorowski J., Pawlak Z., Polkowski L., Skowron A. Rough sets: a tutorial. Rough Fuzzy Hybridization: New Trend Decision-Making 1999, 3-98.
30. Kou G., Peng Y., Shi Y., Wise M., Xu W. Discovering credit cardholders' behavior by multiple criteria linear programming. Ann. Oper. Res. 2005, 135:261-274.
31. Lafont V., Schaefer M., Stote R.H., Altschuh D., Dejaegere A. Protein-protein recognition and interaction hot spots in an antigen-antibody complex: free energy decomposition identifies "efficient amino acids". Proteins 2007, 67:418-434.
32. Lang S., Xu J., Stuart F., Thomas R.M., Vrijbloed J.W., Robinson J.A. Analysis of antibody A6 binding to the extracellular interferon gamma receptor alpha-chain by alanine-scanning mutagenesis and random mutagenesis with phage display. Biochemistry 2000, 39:15674-15685.
33. Lise S., Archambeau C., Pontil M., Jones D.T. Prediction of hot spot residues at protein-protein interfaces by combining machine learning and energy-based methods. BMC Bioinformatics 2009, 10:365. 10.1186/1471-2105-10-365.
34. McCoy A.J., Chandana Epa V., Colman P.M. Electrostatic complementarity at protein/protein interfaces. J. Mol. Biol. 1997, 268:570-584.
35. Moreira I.S., Fernandes P.A., Ramos M.J. Hot spots-a review of the protein-protein interface determinant amino-acid residues. Proteins 2007, 68:803-812.
36. Moreira I.S., Fernandes P.A., Ramos M.J. Computational alanine scanning mutagenesis-an improved methodological approach. J. Comput. Chem. 2007, 28:644-654.
37. Norel R., Petrey D., Wolfson H.J., Nussinov R. Examination of shape complementarity in docking of unbound proteins. Proteins 1999, 36:307-317.
38. Ofran Y., Rost B. Analysing six types of protein-protein interfaces. J. Mol. Biol. 2003, 325:377-387.
39. Ofran Y., Rost B. Protein-protein interaction hotspots carved into sequences. PLoS Comput. Biol. 2007, 3:e119.
40. Ofran Y., Rost B. Predicted protein-protein interaction sites from local sequence information. FEBS Lett. 2003, 544:236-239.
41. Pawlak Z. Rough sets. Int. J. Parallel Programming 1982, 11:341-356.
42. Piehler J., Schreiber G. Mutational and structural analysis of the binding interface between type I interferons and their receptor Ifnar2. J. Mol. Biol. 1999, 294:223-237.
43. Quinlan J.R. Induction of decision trees. Mach. Learn. 1986, 1:81-106.
44. Schueler O., Margalit H. Conservation of salt bridges in protein families. J. Mol. Biol. 1995, 248:125-135.
45. Sheinerman F.B., Norel R., Honig B. Electrostatic aspects of protein-protein interactions. Curr. Opin. Struct. Biol. 2000, 10:153-159.
46. Shi Y. Multiple Criteria and Multiple Constraint Levels Linear Programming: Concepts, Techniques and Applications 2001, World Scientific Publishing Co. Pte, Ltd., Singapore.
47. Swiniarski R.W., Skowron A. Rough set methods in feature selection and recognition. Pattern Recognition Lett. 2003, 24:833-849.
48. Shi Y., Yu P.L. Goal setting and compromise solutions. Multiple Criteria Decision Making and Risk Analysis Using Microcomputers 1989, 56:165-204.
49. Thorn K.S., Bogan A.A. ASEdb: a database of alanine mutations and their effects on the free energy of binding in protein interactions. Bioinformatics 2001, 17:284-285.
50. Tsai C.J., Lin S.L., Wolfson H.J., Nussinov R. A dataset of protein-protein interfaces generated with a sequence-order-independent comparison technique. J. Mol. Biol. 1996, 260:604-620.
51. Verkhivker G.M. Computational analysis of ligand binding dynamics at the intermolecular hot spots with the aid of simulated tempering and binding free energy calculations. J. Mol. Graph. Model 2004, 22:335-348.
52. Van Petegem F., Duderstadt K.E., Clark K.A., Wang M., Minor D.L. Alanine-scanning mutagenesis defines a conserved energetic hotspot in the CaValpha1 AID-CaVbeta interaction site that is critical for channel modulation. Structure 2008, 16:280-294.
53. Wells J.A. Systematic mutational analyses of protein-protein interfaces. Methods Enzymol. 1991, 202:390-411.
54. Xu D., Tsai C.J., Nussinov R. Hydrogen bonds and salt bridges across protein-protein interfaces. Protein Eng. 1997, 10:999-1012.
55. Zhang Z., Zhang P., Shi Y. A rough set-based multiple criteria linear programming approach for improving classification performance. Int. J. Oper. Quant. Manage. 2008, 14:221-235.
56. Zhang Z., Shi Y., Gao G. A rough set-based multiple criteria linear programming approach for the medical diagnosis and prognosis. Expert Syst. With Appl. 2009, 36:8932-8937.
57. Zheng J., Zhuang W., Yan N., Kou G., Peng H., McNally C., Erichsen D., Cheloha A., Herek S., Shi C. Classification of HIV-I-Mediated neuronal dendritic and synaptic damage using multiple criteria linear programming. Neuroinformatics 2004, 2:303-326.