Predicting experimental properties of integral membrane proteins by a naive Bayes approach

Proteins: Structure, Function and Genetics

Volumn 70, Issue 4, 2008, Pages 1243-1256

  Martin Galiano, Antonio J ^a   Smialowski, Pawel ^a   Frishman, Dmitrij ^a  

^a TECHNICAL UNIVERSITY OF MUNICH   (Germany)

Author keywords

Machine learning; Protein expression; Protein solubility; Structural genomics; Target selection

Indexed keywords

ISOLEUCINE; MEMBRANE PROTEIN; VALINE;

AMINO ACID SEQUENCE; ARTICLE; BAYES THEOREM; DATA BASE; MEMBRANE STRUCTURE; MOLECULAR CLONING; PREDICTION; PRIORITY JOURNAL; SOLUBILIZATION; STRUCTURAL GENOMICS;

AMINO ACID SEQUENCE; AMINO ACIDS, BASIC; BAYES THEOREM; CLASSIFICATION; CLONING, MOLECULAR; GENE EXPRESSION; HYDROPHOBICITY; MEMBRANE PROTEINS; SOLUBILITY;

EID: 39749094371     PISSN: 08873585     EISSN: 10970134     Source Type: Journal    
DOI: 10.1002/prot.21605     Document Type: Article

References (46)

1. Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Shindyalov IN, Bourne PE. The protein data bank. Nucleic Acids Res 2000;28:235-242.
2. Murzin AG, Brenner SE, Hubbard T, Chothia C. SCOP: a structural classification of proteins database for the investigation of sequences and structures. J Mol Biol 1995;247:536-540.
3. Orengo CA, Michie AD, Jones S, Jones DT, Swindells MB, Thornton JM. CATH - a hierarchic classification of protein domain structures. Structure 1997;5:1093-1108.
4. Sali A. 100,000 protein structures for the biologist. Nat Struct Biol 1998;5:1029-1032.
5. Brenner SE. Target selection for structural genomics. Nat Struct Biol 2000;7(Suppl):967-969.
6. Vitkup D, Melamud E, Moult J, Sander C. Completeness in structural genomics. Nat Struct Biol 2001;8:559-566.
7. Stevens RC, Yokoyama S, Wilson IA. Global efforts in structural genomics. Science 2001;294:89-92.
8. Frishman D, Mewes HW. Protein structural classes in five complete genomes. Nat Struct Biol 1997;4:626-628.
9. Drews J. Drug discovery: a historical perspective. Science 2000;287: 1960-1964.
10. Deisenhofer J, Epp O, Miki K, Huber R, Michel H. X-ray structure analysis of a membrane protein complex. Electron density map at 3 A resolution and a model of the chromophores of the photosynthetic reaction center from Rhodopseudomonas viridis. J Mol Biol 1984;180:385-398.
11. White SH. The progress of membrane protein structure determination. Protein Sci 2004;13:1948-1949.
12. Miroux B, Walker JE. Over-production of proteins in Escherichia coli: mutant hosts that allow synthesis of some membrane proteins and globular proteins at high levels. J Mol Biol 1996;260:289-298.
13. Eshaghi S, Hedren M, Nasser MI, Hammarberg T, Thornell A, Nordlund P. An efficient strategy for high-throughput expression screening of recombinant integral membrane proteins. Protein Sci 2005;14:676-683.
14. Dobrovetsky E, Lu ML, Andorn-Broza R, Khutoreskaya G, Bray JE, Savchenko A, Arrowsmith CH, Edwards AM, Koth CM. High-throughput production of prokaryotic membrane proteins. J Struct Funct Genomics 2005;6:33-50.
15. Bowie JU. Are we destined to repeat history? Curr Opin Struct Biol 2000;10:435-437.
16. Walian P, Cross TA, Jap BK. Structural genomics of membrane proteins. Genome Biol 2004;5:215.
17. Essen L-O. Structural genomics of "non-standard" proteins: a chance for membrane proteins? Gene Funct Dis 2002;3:39-48.
18. Chen L, Oughtred R, Berman HM, Westbrook J. TargetDB: a target registration database for structural genomics projects. Bioinformatics 2004;20:2860-2862.
19. Christendat D, Yee A, Dharamsi A, Kluger Y, Savchenko A, Cort JR, Booth V, Mackereth CD, Saridakis V, Ekiel I, Kozlov G, Maxwell KL, Wu N, McIntosh LP, Gehring K, Kennedy MA, Davidson AR, Pai EF, Gerstein M, Edwards AM, Arrowsmith CH. Structural proteomics of an archaeon. Nat Struct Biol 2000;7:903-909.
20. Goh CS, Lan N, Douglas SM, Wu B, Echols N, Smith A, Milburn D, Montelione GT, Zhao H, Gerstein M. Mining the structural genomics pipeline: identification of protein properties that affect high-throughput experimental analysis. J Mol Biol 2004;336:115-130.
21. Idicula-Thomas S, Kulkarni AJ, Kulkarni BD, Jayaraman VK, Balaji PV. A support vector machine-based method for predicting the propensity of a protein to be soluble or to form inclusion body on over-expression in Escherichia coli. Bioinformatics 2006;22:278-284.
22. Smialowski P, Schmidt T, Cox J, Kirschner A, Frishman D. Will my protein crystallize? A sequence-based predictor. Proteins 2006;62: 343-355.
23. Korepanova A, Gao FP, Hua Y, Qin H, Nakamoto RK, Cross TA. Cloning and expression of multiple integral membrane proteins from Mycobacterium tuberculosis in Escherichia coli. Protein Sci 2005;14:148-158.
24. Daley DO, Rapp M, Granseth E, Melen K, Drew D, von Heijne G. Global topology analysis of the Escherichia coli inner membrane proteome. Science 2005;308:1321-1323.
25. Savchenko A, Yee A, Khachatryan A, Skarina T, Evdokimova E, Pavlova M, Semesi A, Northey J, Beasley S, Lan N, Das R, Gerstein M, Arrowmith CH, Edwards AM. Strategies for structural proteomics of prokaryotes: quantifying the advantages of studying orthologous proteins and of using both NMR and X-ray crystallography approaches. Proteins 2003;50:392-399.
26. Surade S, Klein M, Stolt-Bergner PC, Muenke C, Roy A, Michel H. Comparative analysis and "expression space" coverage of the production of prokaryotic membrane proteins for structural genomics. Protein Sci 2006;15:2178-2189.
27. Krogh A, Larsson B, von Heijne G, Sonnhammer EL. Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes. J Mol Biol 2001;305:567-580.
28. Jaenicke R, Bohm G. The stability of proteins in extreme environments. Curr Opin Struct Biol 1998;8:738-748.
29. Das R, Gerstein M. The stability of thermophilic proteins: a study based on comprehensive genome comparison. Funct Integr Genomics 2000;1:76-88.
30. Liu J, Hegyi H, Acton TB, Montelione GT, Rost B. Automatic target selection for structural genomics on eukaryotes. Proteins 2004;56: 188-200.
31. Gerstein M. How representative are the known structures of the proteins in a complete genome? A comprehensive structural census. Fold Des 1998;3:497-512.
32. Senes A, Engel DE, DeGrado WF. Folding of helical membrane proteins: the role of polar, GxxxG-like and proline motifs. Curr Opin Struct Biol 2004;14:465-479.
33. Reiersen H, Rees AR. The hunchback and its neighbours: proline as an environmental modulator. Trends Biochem Sci 2001;26:679-684.
34. Krigbaum WR, Komoriya A. Local interactions as a structure determinant for protein molecules: II. Biochim Biophys Acta 1979; 576:204-248.
35. Kyte J, Doolittle RF. A simple method for displaying the hydropathic character of a protein. J Mol Biol 1982;157:105-132.
36. Adamian L, Liang J. Interhelical hydrogen bonds and spatial motifs in membrane proteins: polar clamps and serine zippers. Proteins 2002;47:209-218.
37. Fauchere JL, Charton M, Kier LB, Verloop A, Pliska V. Amino acid side chain parameters for correlation studies in biology and pharmacology. Int J Pept Protein Res 1988;32:269-278.
38. Klein P, Kanehisa M, DeLisi C. Prediction of protein function from sequence properties. Discriminant analysis of a data base. Biochim Biophys Acta 1984;787:221-226.
39. Taylor WR. The classification of amino acid conservation. J Theor Biol 1986;119:205-218.
40. John GH, Langley P. Estimating continuous distributions in Bayesian classifiers. In: Besnard P, Hanks S, editors. Proceedings of the eleventh conference on uncertainty in artificial intelligence. San Mateo, CA: Morgan Kaufmann; 1995. pp 338-345.
41. Witten IH, Frank E. Data mining. Practical machine learning tools and techniques, 2nd ed. San Mateo, CA: Morgan Kaufmann; 2005. 525 pp.
42. Matthews BW. Comparison of the predicted and observed secondary structure of T4 phage lysozyme. Biochim Biophys Acta 1975; 405:442-451.
43. Frank E, Hall M, Trigg L, Holmes G, Witten IH. Data mining in bioinformatics using Weka. Bioinformatics 2004;20:2479-2481.
44. Kohavi R, John GH. Wrappers for feature subset selection. Artif Intell I 1997;97:273-324.
45. Canaves JM, Page R, Wilson IA, Stevens RC. Protein biophysical properties that correlate with crystallization success in Thermotoga maritima: maximum clustering strategy for structural genomics. J Mol Biol 2004;344:977-991.
46. Domingos P, Pazzani M. Beyond independence: conditions for the optimality of the simple Bayesian classifier. In: Saitta L, editor. Machine learning: proceedings of the thirteenth international conference. San Francisco, CA: Morgan Kaufmann; 1995. pp 105-112.