Prediction of protein folding rates from primary sequence by fusing multiple sequential features

We have developed a web-server for predicting the folding rate of a protein based on its amino acid sequence information alone. The web- server is called Pred-PFR (Predicting Protein Folding Rate). Pred-PFR is featured by fusing multiple individual predictors, each of which is established based on one special feature derived from the protein sequence. The ensemble pre-dictor thus formed is superior to the individual ones, as demonstrated by achieving higher correlation coefficient and lower root mean square deviation between the predicted and observed results when examined by the jack-knife cross-validation on a benchmark dataset constructed recently. As a user-friendly web- server, Pred-PFR is freely accessible to the public at www.csbio.sjtu.edu.cn/bioinf/Folding Rate/.

[1]  R. Jernigan,et al.  Understanding the recognition of protein structural classes by amino acid composition , 1997, Proteins.

[2]  Jie Liang,et al.  Predicting protein folding rates from geometric contact and amino acid sequence , 2008, Protein Science.

[3]  K. Chou,et al.  An optimization approach to predicting protein structural class from amino acid composition , 1992, Protein science : a publication of the Protein Society.

[4]  Motohisa Oobatake,et al.  Hydration and heat stability effects on protein unfolding , 1993 .

[5]  C. Anfinsen.  Principles that govern the folding of protein chains. , 1973, Science.

[6]  C. Kuo-chen,et al.  Graphical rules for non-steady state enzyme kinetics. , 1981, Journal of theoretical biology.

[7]  Kuo-Chen Chou,et al.  Ensemble classifier for protein fold pattern recognition , 2006, Bioinform..

[8]  J. Andraos.  Kinetic plasticity and the determination of product ratios for kinetic schemes leading to multiple products without rate laws — New methods based on directed graphs , 2008 .

[9]  P. Kuzmič,et al.  Mixtures of tight-binding enzyme inhibitors. Kinetic analysis by a recursive rate equation. , 1992, Analytical biochemistry.

[10]  K. Chou,et al.  Using Pair-Coupled Amino Acid Composition to Predict Protein Secondary Structure Content , 1999, Journal of protein chemistry.

[11]  Hao Lin,et al.  Predicting subcellular localization of mycobacterial proteins by using Chou's pseudo amino acid composition. , 2008, Protein and peptide letters.

[12]  G M Maggiora,et al.  Energetics of the structure of the four-alpha-helix bundle in proteins. , 1988, Proceedings of the National Academy of Sciences of the United States of America.

[13]  Parviz Abdolmaleki,et al.  Prediction of membrane protein types by means of wavelet analysis and cascaded neural networks. , 2008, Journal of theoretical biology.

[14]  K. Chou,et al.  A correlation-coefficient method to predicting protein-structural classes from amino acid compositions. , 1992, European journal of biochemistry.

[15]  K. Chou,et al.  Cell-PLoc: a package of Web servers for predicting subcellular localization of proteins in various organisms , 2008, Nature Protocols.

[16]  Harold A Scheraga,et al.  From helix-coil transitions to protein folding. , 2008, Biopolymers.

[17]  C. DeLisi,et al.  Prediction of protein structural class from the amino acid sequence , 1986, Biopolymers.

[18]  C. Zhang,et al.  Predicting protein folding types by distance functions that make allowances for amino acid interactions. , 1994, The Journal of biological chemistry.

[19]  D T Jones,et al.  Protein secondary structure prediction based on position-specific scoring matrices. , 1999, Journal of molecular biology.

[20]  Fengmin Li,et al.  Predicting protein subcellular location using Chou's pseudo amino acid composition and improved hybrid approach. , 2008, Protein and peptide letters.

[21]  I. Muchnik,et al.  Prediction of protein folding class using global description of amino acid sequence. , 1995, Proceedings of the National Academy of Sciences of the United States of America.

[22]  M. Manimekalai.  PREDICTION OF SECONDARY STRUCTURE OF PROTEINS , 2010 .

[23]  Lukasz A. Kurgan,et al.  PFRES: protein fold classification by using evolutionary information and predicted secondary structure , 2007, Bioinform..

[24]  S Sugai,et al.  An early immunoreactive folding intermediate of the tryptophan synthase β2 subunit is a ‘molten globule’ , 1990, FEBS letters.

[25]  Yongsheng Ding,et al.  Using Chou's pseudo amino acid composition to predict subcellular localization of apoptosis proteins: An approach with immune genetic algorithm-based ensemble classifier , 2008, Pattern Recognit. Lett..

[26]  Hao Lin.  The modified Mahalanobis Discriminant for predicting outer membrane proteins by using Chou's pseudo amino acid composition. , 2008, Journal of theoretical biology.

[27]  K. Chou.  Progress in protein structural class prediction and its impact to bioinformatics and proteomics. , 2005, Current protein & peptide science.

[28]  Kuo-Chen Chou,et al.  Prediction of protein structure classes with pseudo amino acid composition and fuzzy support vector machine network. , 2007, Protein and peptide letters.

[29]  H A Scheraga,et al.  Origin of the right-handed twist of beta-sheets of poly(LVal) chains. , 1982, Proceedings of the National Academy of Sciences of the United States of America.

[30]  G. Zhou,et al.  An extension of Chou's graphic rules for deriving enzyme kinetic equations to systems involving parallel reaction pathways. , 1984, The Biochemical journal.

[31]  K. Chou.  Applications of graph theory to enzyme kinetics and protein folding kinetics. Steady and non-steady-state systems. , 2020, Biophysical chemistry.

[32]  Guangya Zhang,et al.  Predicting the cofactors of oxidoreductases based on amino acid composition distribution and Chou's amphiphilic pseudo-amino acid composition. , 2008, Journal of theoretical biology.

[33]  Hongyi Zhou,et al.  Folding rate prediction using total contact distance. , 2002, Biophysical journal.

[34]  R. Verrall,et al.  Implications of protein folding. Additivity schemes for volumes and compressibilities. , 1988, The Journal of biological chemistry.

[35]  K. Chou,et al.  Recent progress in protein subcellular location prediction. , 2007, Analytical biochemistry.

[36]  Kuo-Chen Chou,et al.  Energetic approach to the packing of α-helices. II: General treatment of nonequivalent and nonregular helices , 1984 .

[37]  Guo-Ping Zhou,et al.  An Intriguing Controversy over Protein Structural Class Prediction , 1998, Journal of protein chemistry.

[38]  Kevin W Plaxco,et al.  Contact order revisited: Influence of protein size on the folding rate , 2003, Protein science : a publication of the Protein Society.

[39]  Zhanchao Li,et al.  Using Chou's amphiphilic pseudo-amino acid composition and support vector machine for prediction of enzyme subfamily classes. , 2007, Journal of theoretical biology.

[40]  D. Baker,et al.  Contact order, transition state placement and the refolding rates of single domain proteins. , 1998, Journal of molecular biology.

[41]  M. Gromiha,et al.  Comparison between long-range interactions and contact order in determining the folding rate of two-state proteins: application of long-range order to folding rate prediction. , 2001, Journal of molecular biology.

[42]  Guangya Zhang,et al.  Predicting lipase types by improved Chou's pseudo-amino acid composition. , 2008, Protein and peptide letters.

[43]  Nicole Sips,et al.  Structural determinants of the rate of protein folding. , 2003, Journal of theoretical biology.

[44]  D Wang,et al.  Use of fuzzy-logic-inspired features to improve bacterial recognition through classifier fusion , 1998, IEEE Trans. Syst. Man Cybern. Part B.

[45]  David Myers,et al.  Microcomputer tools for steady-state enzyme kinetics , 1985, Comput. Appl. Biosci..

[46]  K. Chou,et al.  Predicting protein fold pattern with functional domain and sequential evolution information. , 2009, Journal of theoretical biology.

[47]  T. Creighton,et al.  Protein Folding , 1992 .

[48]  Cristian Robert Munteanu,et al.  Natural/random protein classification models based on star network topological indices , 2008, Journal of Theoretical Biology.

[49]  K. Chou,et al.  Graphic rules in steady and non-steady state enzyme kinetics. , 1989, The Journal of biological chemistry.

[50]  H A Scheraga,et al.  Folding of the twisted beta-sheet in bovine pancreatic trypsin inhibitor. , 1985, Biochemistry.

[51]  G P Zhou,et al.  Some insights into protein structural class prediction , 2001, Proteins.

[52]  A. Finkelstein,et al.  Prediction of protein folding rates from the amino acid sequence-predicted secondary structure , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[53]  K. Chou.  Structural bioinformatics and its impact to biomedical science. , 2004, Current medicinal chemistry.

[54]  K. Chou,et al.  Prediction of protein structural classes. , 1995, Critical reviews in biochemistry and molecular biology.

[55]  T. Creighton,et al.  Protein Folding: An unfolding story , 1995, Current Biology.

[56]  K. Neet,et al.  Demonstration of a slow conformational change in liver glucokinase by fluorescence spectroscopy. , 1990, The Journal of biological chemistry.

[57]  C. Zhang,et al.  A joint prediction of the folding types of 1490 human proteins from their genetic codons. , 1993, Journal of theoretical biology.

[58]  K. Chou,et al.  Does the folding type of a protein depend on its amino acid composition? , 1995, FEBS letters.

[59]  K. Chou.  A novel approach to predicting protein structural classes in a (20–1)‐D amino acid composition space , 1995, Proteins.

[60]  H. Scheraga,et al.  Experimental and theoretical aspects of protein folding. , 1975, Advances in protein chemistry.

[61]  M. Michael Gromiha,et al.  FOLD-RATE: prediction of protein folding rates from amino acid sequence , 2006, Nucleic Acids Res..

[62]  Chris H. Q. Ding,et al.  Multi-class protein fold recognition using support vector machines and neural networks , 2001, Bioinform..

[63]  P. Y. Chou,et al.  Prediction of the secondary structure of proteins from their amino acid sequence. , 2006 .