Putting engineering back into protein engineering: Bioinformatic approaches to catalyst design

Current Opinion in Biotechnology

Volumn 14, Issue 4, 2003, Pages 366-370

  Gustafsson, Claes ^a   Govindarajan, Sridhar ^a   Minshull, Jeremy ^a  

^a DNA20 Inc   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

PEPTIDE; PROTEIN;

AMINO ACID SEQUENCE; BIOINFORMATICS; CATALYST; DNA SEQUENCE; MATHEMATICAL MODEL; PRIORITY JOURNAL; PROTEIN BINDING; PROTEIN ENGINEERING; PROTEIN FUNCTION; PROTEIN INTERACTION; PROTEIN STRUCTURE; PROTEIN SYNTHESIS; REVIEW;

EID: 0042433113     PISSN: 09581669     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0958-1669(03)00101-0     Document Type: Review

References (54)

1. Tobin M.B., Gustafsson C., Huisman G.W. Directed evolution: the 'rational' basis for 'irrational' design. Curr Opin Struct Biol. 10:2000;421-427.
2. van Regenmortel M.H. Are there two distinct research strategies for developing biologically active molecules: rational design and empirical selection? J Mol Recognit. 13:2000;1-4.
3. Ryu D.D., Nam D.H. Recent progress in biomolecular engineering. Biotechnol Prog. 16:2000;2-16.
4. Nambiar K.P., Stackhouse J., Stauffer D.M., Kennedy W.P., Eldredge J.K., Benner S.A. Total synthesis and cloning of a gene coding for the ribonuclease S protein. Science. 223:1984;1299-1301.
5. Hellberg S: A Multivariate Approach to QSAR. PhD thesis. Umea, Sweden: University of Umea: 1986.
6. Hellberg S., Sjostrom M., Skagerberg B., Wold S. Peptide quantitative structure-activity relationships, a multivariate approach. J Med Chem. 30:1987;1126-1135.
7. Gustafsson C., Govindarajan S., Emig R. Exploration of sequence space for protein engineering. J Mol Recognit. 14:2001;308-314.
8. Sandberg M., Eriksson L., Jonsson J., Sjostrom M., Wold S. New chemical descriptors relevant for the design of biologically active peptides. A multivariate characterization of 87 amino acids. J Med Chem. 41:1998;2481-2491.
9. Lin Z., Thorsen T., Arnold F.H. Functional expression of horseradish peroxidase in E. coli by directed evolution. Biotechnol Prog. 15:1999;467-471.
10. Glieder A., Farinas E.T., Arnold F.H. Laboratory evolution of a soluble, self-sufficient, highly active alkane hydroxylase. Nat Biotechnol. 20:2002;1135-1139.
11. Lehmann M., Lopez-Ulibarri R., Loch C., Viarouge C., Wyss M., van Loon A.P. Exchanging the active site between phytases for altering the functional properties of the enzyme. Protein Sci. 9:2000;1866-1872 Demonstration that residues identified as functionally important (in this case the entire active site) can be moved from one protein backbone to another, leading to functionally novel catalysts.
12. Looger L.L., Dwyer M.A., Smith J.J., Hellinga H.W. Computational design of receptor and sensor proteins with novel functions. Nature. 423:2003;185-190.
13. Kwasigroch J.M., Gilis D., Dehouck Y., Rooman M. PoPMuSiC, rationally designing point mutations in protein structures. Bioinformatics. 18:2002;1701-1702.
14. Tangri S., LiCalsi C., Sidney J., Sette A. Rationally engineered proteins or antibodies with absent or reduced immunogenicity. Curr Med Chem. 9:2002;2191-2199.
15. Pierce N.A., Winfree E. Protein design is NP-hard. Protein Eng. 15:2002;779-782.
16. Lathrop R.H. The protein threading problem with sequence amino acid interaction preferences is NP-complete. Protein Eng. 7:1994;1059-1068.
17. Hanes J., Pluckthun A. In vitro selection and evolution of functional proteins by using ribosome display. Proc Natl Acad Sci USA. 94:1997;4937-4942.
18. Wells J.A., Lowman H.B. Rapid evolution of peptide and protein binding properties in vitro. Curr Opin Biotechnol. 3:1992;355-362.
19. Ness J.E., del Cardayre S.B., Minshull J., Stemmer W.P. Molecular breeding: the natural approach to protein design. Adv Protein Chem. 55:2000;261-292.
20. Johnson DS, McGeoch LA: The traveling salesman problem: a case study in local optimization. In Local Search in Combinatorial Optimization. Edited by Aarts EHL, Lenstra JK, Aarts EL: John Wiley & Sons Ltd; 1997:215-310.
21. Casari G., Sander C., Valencia A. A method to predict functional residues in proteins. Nat Struct Biol. 2:1995;171-178.
22. del Sol Mesa A., Pazos F., Valencia A. Automatic methods for predicting functionally important residues. J Mol Biol. 326:2003;1289-1302 Excellent comparison of methods available to identify residues that contribute to protein function.
23. Gogos A., Jantz D., Senturker S., Richardson D., Dizdaroglu M., Clarke N.D. Assignment of enzyme substrate specificity by principal component analysis of aligned protein sequences: an experimental test using DNA glycosylase homologs. Proteins. 40:2000;98-105 Principal component analysis of small numbers of proteins used to identify residues likely to be involved in substrate specificity determination.
24. Suzuki Y., Gojobori T. A method for detecting positive selection at single amino acid sites. Mol Biol Evol. 16:1999;1315-1328.
25. Jonsson J., Norberg T., Carlsson L., Gustafsson C., Wold S. Quantitative sequence-activity models (QSAM) - tools for sequence design. Nucleic Acids Res. 21:1993;733-739.
26. Govindarajan S., Ness J.E., Kim S., Mundorff E.C., Minshull J., Gustafsson C. Systematic variation of amino acid substitutions for stringent assessment of pairwise covariation. J Mol Biol. 328:2003;1061-1069 Fifty-two phylogenetically identified substitutions in subtilisins are accepted into one enzyme backbone, modifying its activity. Most natural changes that occur together are shown to be a result of descent from a common ancestor and not a result of functional constraints.
27. Lehmann M., Loch C., Middendorf A., Studer D., Lassen S.F., Pasamontes L., van Loon A.P., Wyss M. The consensus concept for thermostability engineering of proteins: further proof of concept. Protein Eng. 15:2002;403-411.
28. Benner S.A., Cohen M.A., Gonnet G.H. Amino acid substitution during functionally constrained divergent evolution of protein sequences. Protein Eng. 7:1994;1323-1332.
29. Wu T.D., Brutlag D.L. Discovering empirically conserved amino acid substitution groups in databases of protein families. Proc Int Conf Intell Syst Mol Biol. 4:1996;230-240.
30. Adenot M., Sarrauste de Menthiere C., Chavanieu A., Calas B., Grassy G. Peptides quantitative structure-function relationships: an automated mutation strategy to design peptides and pseudopeptides from substitution matrices. J Mol Graph Model. 17:1999;292-309.
31. Dimmic M.W., Rest J.S., Mindell D.P., Goldstein R.A. rtREV: an amino acid substitution matrix for inference of retrovirus and reverse transcriptase phylogeny. J Mol Evol. 55:2002;65-73 A substitution matrix for maximum likelihood phylogenetic analysis is developed that is optimized on a subset of sequences. Substitution matrices are unique for each sequence subset.
32. Norinder U., Rivera C., Unden A. A quantitative structure-activity relationship study of some substance P-related peptides. A multivariate approach using PLS and variable selection. J Pept Res. 49:1997;155-162.
33. Sandberg M: Deciphering Sequence Data, a Multivariate Approach. PhD thesis. Umea: Umea University: 1997.
34. Geladi P., Kowalski B.R. Partial least squares regression: a tutorial. Anal Chim Acta. 186:1986;1-17.
35. Bucht G., Wikstrom P., Hjalmarsson K. Optimising the signal peptide for glycosyl phosphatidylinositol modification of human acetylcholinesterase using mutational analysis and peptide-quantitative structure-activity relationships. Biochim Biophys Acta. 1431:1999;471-482 PLS and experimental design are used to optimize acetylcholinesterase, increasing its surface expression on cells threefold.
36. Aita T., Iwakura M., Husimi Y. A cross-section of the fitness landscape of dihydrofolate reductase. Protein Eng. 14:2001;633-638.
37. Aita T., Uchiyama H., Inaoka T., Nakajima M., Kokubo T., Husimi Y. Analysis of a local fitness landscape with a model of the rough Mt. Fuji-type landscape: application to prolyl endopeptidase and thermolysin. Biopolymers. 54:2000;64-79.
38. Strom M.B., Haug B.E., Rekdal O., Skar M.L., Stensen W., Svendsen J.S. Important structural features of 15-residue lactoferricin derivatives and methods for improvement of antimicrobial activity. Biochem Cell Biol. 80:2002;65-74.
39. Eriksson L., Jonsson J., Hellberg S., Lindgren F., Skagerberg B., Sjostrom M., Wold S. Peptide QSAR on substance P analogues, enkephalins and bradykinins containing L- and D-amino acids. Acta Chem Scand A. 44:1990;50-55.
40. Choulier L., Andersson K., Hamalainen M.D., van Regenmortel M.H., Malmqvist M., Altschuh D. QSAR studies applied to the prediction of antigen-antibody interaction kinetics as measured by BIAcore. Protein Eng. 15:2002;373-382 Multivariate analysis applied to sequence optimization and reaction conditions.
41. Hoover D.M., Lubkowski J. DNAWorks: an automated method for designing oligonucleotides for PCR-based gene synthesis. Nucleic Acids Res. 30:2002;e43 The shape of things to come. Gene synthesis gets cheaper and easier.
42. Holowachuk E.W., Ruhoff M.S. Efficient gene synthesis by Klenow assembly/extension-Pfu polymerase amplification (KAPPA) of overlapping oligonucleotides. PCR Methods Appl. 4:1995;299-302.
43. Abecassis V., Pompon D., Truan G. High efficiency family shuffling based on multi-step PCR and in vivo DNA recombination in yeast: statistical and functional analysis of a combinatorial library between human cytochrome P450 1A1 and 1A2. Nucleic Acids Res. 28:2000;E88 One of many library synthesis methods. Interesting analysis of variants in which hybridization signals instead of known sequence changes are used as input variables for modeling.
44. Hellberg S., Eriksson L., Jonsson J., Lindgren F., Sjöström M., Skagerberg B., Wold S., Andrews P. Minimum analogue peptide sets (MAPS) for quantitative structure-activity relationships. Int J Pept Protein Res. 37:1991;414-424.
45. Mee R.P., Auton T.R., Morgan P.J. Design of active analogues of a 15-residue peptide using D-optimal design, QSAR and a combinatorial search algorithm. J Pept Res. 49:1997;89-102.
46. Aita T., Hamamatsu N., Nomiya Y., Uchiyama H., Shibanaka Y., Husimi Y. Surveying a local fitness landscape of a protein with epistatic sites for the study of directed evolution. Biopolymers. 64:2002;95-105 A model of only 45 prolyl endopeptidase variants accurately predicts the activities of combinations of 14 different mutations. Only one interaction term in required in the model.
47. Prusis P., Lundstedt T., Wikberg J.E. Proteo-chemometrics analysis of MSH peptide binding to melanocortin receptors. Protein Eng. 15:2002;305-311 Statistically representative sets of melanocortin peptide and chimeric receptors were analyzed. Models incorporated linear and interaction terms; predictions were externally validated.
48. Schneider G., Schrödl W., Wallukat G., Muller J., Nissen E., Rönspeck W., Wrede P., Kunze R. Peptide design by artificial neural networks and computer-based evolutionary search. Proc Natl Acad Sci USA. 95:1998;12179-12184.
49. Lu S.M., Lu W., Qasim M.A., Anderson S., Apostol I., Ardelt W., Bigler T., Chiang Y.W., Cook J., James M.N.et al. Predicting the reactivity of proteins from their sequence alone: Kazal family of protein inhibitors of serine proteinases. Proc Natl Acad Sci USA. 98:2001;1410-1415 The conclusion of an heroic 20 year study. By synthesizing and testing <200 variants, activities of many natural proteinases can be accurately predicted.
50. Sjöström M., Wold S., Wieslander A., Rilfors L. Signal peptide amino acid sequences in Escherichia coli contain information related to final protein localization. A multivariate data analysis. EMBO. 6:1987;823-831.
51. Schein A.I., Kissinger J.C., Ungar L.H. Chloroplast transit peptide prediction: a peek inside the black box. Nucleic Acids Res. 29:2001;E82.
52. Fariselli P., Pazos F., Valencia A., Casadio R. Prediction of protein-protein interaction sites in heterocomplexes with neural networks. Eur J Biochem. 269:2002;1356-1361.
53. Damborsky J. Quantitative structure-function and structure-stability relationships of purposely modified proteins. Protein Eng. 11:1998;21-30.
54. Marvanova S., Nagata Y., Wimmerova M., Sykorova J., Hynkova K., Damborsky J. Biochemical characterization of broad-specificity enzymes using multivariate experimental design and a colorimetric microplate assay: characterization of the haloalkane dehalogenase mutants. J Microbiol Methods. 44:2001;149-157.