iStable: Off-the-shelf predictor integration for predicting protein stability changes

BMC Bioinformatics

Volumn 14, Issue , 2013, Pages

  Chen, Chi Wei ^a   Lin, Jerome ^a   Chu, Yen Wei ^a  

^a NATIONAL CHUNG HSING UNIVERSITY   (Taiwan)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER ARCHITECTURE; FORECASTING; GRID COMPUTING; LEARNING SYSTEMS;

AMINO ACID RESIDUES; EXPERIMENTAL CONDITIONS; GRID COMPUTING ARCHITECTURES; MACHINE LEARNING METHODS; PROTEIN STABILITY; SECONDARY STRUCTURES; SEQUENCE INFORMATIONS; SOLVENT ACCESSIBILITY;

PROTEINS;

AMINO ACID; PROTEIN;

ARTICLE; CHEMISTRY; COMPUTER PROGRAM; GENETICS; MUTATION; PROTEIN SECONDARY STRUCTURE; PROTEIN STABILITY; SUPPORT VECTOR MACHINE;

AMINO ACIDS; MUTATION; PROTEIN STABILITY; PROTEIN STRUCTURE, SECONDARY; PROTEINS; SOFTWARE; SUPPORT VECTOR MACHINES;

EID: 84884189591     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-14-S2-S5     Document Type: Article

References (35)

1. Mehanna AS: Sickle cell anemia and antisickling agents then and now. Curr Med Chem 2001, 8(2):79-88.
2. Tokuriki N, Stricher F, Serrano L, Tawfik DS: How Protein Stability and NewFunctions Trade Off. Plos Computational Biology 2008, 4(2):e1000002.
3. Daggett V, Fersht AR: Is there a unifying mechanism for protein folding? Trends Biochem Sci 2003, 28(1):18-25.
4. Gromiha MM, Sarai A: Thermodynamic database for proteins: features and applications. Methods Mol Biol 2010, 609:97-112.
5. Bash PA, Singh UC, Langridge R, Kollman PA: Free energy calculations by computer simulation. Science 1987, 236(4801):564-568.
6. Lee C, Levitt M: Accurate prediction of the stability and activity effects of site-directed mutagenesis on a protein core. Nature 1991, 352(6334):448-451.
7. Pitera JW, Kollman PA: Exhaustive mutagenesis in silico: Multicoordinate free energy calculations on proteins and peptides. Proteins-Structure Function and Genetics 2000, 41(3):385-397.
8. Carter CW Jr, LeFebvre BC, Cammer SA, Tropsha A, Edgell MH: Four-body potentials reveal protein-specific correlations to stability changes caused by hydrophobic core mutations. J Mol Biol 2001, 311(4):625-638.
9. Gilis D, Rooman M: Predicting protein stability changes upon mutation using database-derived potentials: solvent accessibility determines the importance of local versus non-local interactions along the sequence. J Mol Biol 1997, 272(2):276-290.
10. Parthiban V, Gromiha MM, Schomburg D: CUPSAT: prediction of protein stability upon point mutations. Nucleic Acids Research 2006, 34(Web Server):W239-W242.
11. Sippl MJ: Knowledge-based potentials for proteins. Curr Opin Struct Biol 1995, 5(2):229-235.
12. Topham CM, Srinivasan N, Blundell TL: Prediction of the stability of protein mutants based on structural environment-dependent amino acid substitution and propensity tables. Protein Engineering 1997, 10(1):7-21.
13. Zhou HY, Zhou YQ: Distance-scaled, finite ideal-gas reference state improves structure-derived potentials of mean force for structure selection and stability prediction. Protein Science 2002, 11(11):2714-2726.
14. Guerois R, Nielsen JE, Serrano L: Predicting changes in the stability of proteins and protein complexes: a study of more than 1000 mutations. J Mol Biol 2002, 320(2):369-387.
15. Munoz V, Serrano L: Development of the multiple sequence approximation within the AGADIR model of alpha-helix formation: Comparison with Zimm-Bragg and Lifson-Roig formalisms. Biopolymers 1997, 41(5):495-509.
16. Takano K, Ota M, Ogasahara K, Yamagata Y, Nishikawa K, et al: Experimental verification of the 'stability profile of mutant protein' (SPMP) data using mutant human lysozymes. Protein Engineering 1999, 12(8):663-672.
17. Villegas V, Viguera AR, Aviles FX, Serrano L: Stabilization of proteins by rational design of alpha-helix stability using helix/coil transition theory. Folding & Design 1996, 1(1):29-34.
18. Yin S, Ding F, Dokholyan NV: Modeling backbone flexibility improves protein stability estimation. Structure 2007, 15(12):1567-1576.
19. Capriotti E, Fariselli P, Casadio R: A neural-network-based method for predicting protein stability changes upon single point mutations. Bioinformatics 2004, 20(Suppl 1):i63-68.
20. Capriotti E, Fariselli P, Casadio R: I-Mutant2.0: predicting stability changes upon mutation from the protein sequence or structure. Nucleic Acids Res 2005, 33(Web Server):W306-310.
21. Casadio R, Compiani M, Fariselli P, Vivarelli F: Predicting free energy contributions to the conformational stability of folded proteins from the residue sequence with radial basis function networks. Proc Int Conf Intell Syst Mol Biol 1995, 3:81-88.
22. Cheng J, Randall A, Baldi P: Prediction of protein stability changes for single-site mutations using support vector machines. Proteins 2006, 62(4):1125-1132.
23. Frenz CM: Neural network-based prediction of mutation-induced protein stability changes in Staphylococcal nuclease at 20 residue positions. Proteins 2005, 59(2):147-151.
24. Huang LT, Gromiha MM: Reliable prediction of protein thermostability change upon double mutation from amino acid sequence. Bioinformatics 2009, 25(17):2181-2187.
25. Huang LT, Gromiha MM, Ho SY: iPTREE-STAB: interpretable decision tree based method for predicting protein stability changes upon mutations. Bioinformatics 2007, 23(10):1292-1293.
26. Huang LT, Gromiha MM, Ho SY: Sequence analysis and rule development of predicting protein stability change upon mutation using decision tree model. J Mol Model 2007, 13(8):879-890.
27. Wan J, Kang SL, Tang CN, Yan JH, Ren YL, et al: Meta-prediction of phosphorylation sites with weighted voting and restricted grid search parameter selection. Nucleic Acids Res 2008, 36(4):e22.
28. Bordner AJ, Abagyan RA: Large-scale prediction of protein geometry and stability changes for arbitrary single point mutations. Proteins 2004, 57(2):400-413.
29. Capriotti E, Fariselli P, Rossi I, Casadio R: A three-state prediction of single point mutations on protein stability changes. BMC Bioinformatics 2008, 9(Suppl 2):S6.
30. Masso M, Vaisman II: Accurate prediction of stability changes in protein mutants by combining machine learning with structure based computational mutagenesis. Bioinformatics 2008, 24(18):2002-2009.
31. Dehouck Y, et al: Fast and accurate predictions of protein stability changes upon mutations using statistical potentials and neural networks: PoPMuSiC-2.0. Bioinformatics 2009, 25(19):2537-2543.
32. Chang CC, Hsu CW, Lin CJ: The analysis of decomposition methods for support vector machines. IEEE Trans Neural Netw 2000, 11(4):1003-1008.
33. Witten IH, Frank E: Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations. 2 edition. San Francisco: Morgan Kaufmann Publishers; 2005.
34. Gromiha MM, Selvaraj S: Inter-residue interactions in protein folding and stability. Prog Biophys Mol Biol 2004, 86(2):235-277.
35. Gromiha MM, et al: Role of structural and sequence information in the prediction of protein stability changes: comparison between buried and partially buried mutations. Protein Eng 1999, 12(7):549-555.