On the pH-optimum of activity and stability of proteins
Biological macromolecules evolved to perform their function in specific cellular environment (subcellular compartments or tissues); therefore, they should be adapted to the biophysical characteristics of the corresponding environment, one of them being the characteristic pH. Many macromolecular prop...
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| Published in | Proteins, structure, function, and bioinformatics Vol. 78; no. 12; pp. 2699 - 2706 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Hoboken
Wiley Subscription Services, Inc., A Wiley Company
01.09.2010
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| Online Access | Get full text |
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| Abstract | Biological macromolecules evolved to perform their function in specific cellular environment (subcellular compartments or tissues); therefore, they should be adapted to the biophysical characteristics of the corresponding environment, one of them being the characteristic pH. Many macromolecular properties are pH dependent, such as activity and stability. However, only activity is biologically important, while stability may not be crucial for the corresponding reaction. Here, we show that the pH‐optimum of activity (the pH of maximal activity) is correlated with the pH‐optimum of stability (the pH of maximal stability) on a set of 310 proteins with available experimental data. We speculate that such a correlation is needed to allow the corresponding macromolecules to tolerate small pH fluctuations that are inevitable with cellular function. Our findings rationalize the efforts of correlating the pH of maximal stability and the characteristic pH of subcellular compartments, as only pH of activity is subject of evolutionary pressure. In addition, our analysis confirmed the previous observation that pH‐optimum of activity and stability are not correlated with the isoelectric point, pI, or with the optimal temperature. Proteins 2010. © 2010 Wiley‐Liss, Inc. |
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| AbstractList | Biological macromolecules evolved to perform their function in specific cellular environment (subcellular compartments or tissues); therefore, they should be adapted to the biophysical characteristics of the corresponding environment, one of them being the characteristic pH. Many macromolecular properties are pH dependent, such as activity and stability. However, only activity is biologically important, while stability may not be crucial for the corresponding reaction. Here we show that the pH-optimum of activity (the pH of maximal activity) is correlated with the pH-optimum of stability (the pH of maximal stability) on a set of 310 proteins with available experimental data. We speculate that such a correlation is needed to allow the corresponding macromolecules to tolerate small pH fluctuations that are inevitable with cellular function. Our findings rationalize the efforts of correlating the pH of maximal stability and the characteristic pH of subcellular compartments, since only pH of activity is subject of evolutionary pressure. In addition, our analysis confirmed the previous observation that pH-optimum of activity and stability are not correlated with the isoelectric point, pI, or with the optimal temperature. Biological macromolecules evolved to perform their function in specific cellular environment (subcellular compartments or tissues); therefore, they should be adapted to the biophysical characteristics of the corresponding environment, one of them being the characteristic pH. Many macromolecular properties are pH dependent, such as activity and stability. However, only activity is biologically important, while stability may not be crucial for the corresponding reaction. Here, we show that the pH‐optimum of activity (the pH of maximal activity) is correlated with the pH‐optimum of stability (the pH of maximal stability) on a set of 310 proteins with available experimental data. We speculate that such a correlation is needed to allow the corresponding macromolecules to tolerate small pH fluctuations that are inevitable with cellular function. Our findings rationalize the efforts of correlating the pH of maximal stability and the characteristic pH of subcellular compartments, as only pH of activity is subject of evolutionary pressure. In addition, our analysis confirmed the previous observation that pH‐optimum of activity and stability are not correlated with the isoelectric point, pI, or with the optimal temperature. Proteins 2010. © 2010 Wiley‐Liss, Inc. Biological macromolecules evolved to perform their function in specific cellular environment (subcellular compartments or tissues); therefore, they should be adapted to the biophysical characteristics of the corresponding environment, one of them being the characteristic pH. Many macromolecular properties are pH dependent, such as activity and stability. However, only activity is biologically important, while stability may not be crucial for the corresponding reaction. Here, we show that the pH-optimum of activity (the pH of maximal activity) is correlated with the pH-optimum of stability (the pH of maximal stability) on a set of 310 proteins with available experimental data. We speculate that such a correlation is needed to allow the corresponding macromolecules to tolerate small pH fluctuations that are inevitable with cellular function. Our findings rationalize the efforts of correlating the pH of maximal stability and the characteristic pH of subcellular compartments, as only pH of activity is subject of evolutionary pressure. In addition, our analysis confirmed the previous observation that pH-optimum of activity and stability are not correlated with the isoelectric point, pI, or with the optimal temperature. Biological macromolecules evolved to perform their function in specific cellular environment (subcellular compartments or tissues); therefore, they should be adapted to the biophysical characteristics of the corresponding environment, one of them being the characteristic pH. Many macromolecular properties are pH dependent, such as activity and stability. However, only activity is biologically important, while stability may not be crucial for the corresponding reaction. Here, we show that the pH-optimum of activity (the pH of maximal activity) is correlated with the pH-optimum of stability (the pH of maximal stability) on a set of 310 proteins with available experimental data. We speculate that such a correlation is needed to allow the corresponding macromolecules to tolerate small pH fluctuations that are inevitable with cellular function. Our findings rationalize the efforts of correlating the pH of maximal stability and the characteristic pH of subcellular compartments, as only pH of activity is subject of evolutionary pressure. In addition, our analysis confirmed the previous observation that pH-optimum of activity and stability are not correlated with the isoelectric point, pI, or with the optimal temperature.Biological macromolecules evolved to perform their function in specific cellular environment (subcellular compartments or tissues); therefore, they should be adapted to the biophysical characteristics of the corresponding environment, one of them being the characteristic pH. Many macromolecular properties are pH dependent, such as activity and stability. However, only activity is biologically important, while stability may not be crucial for the corresponding reaction. Here, we show that the pH-optimum of activity (the pH of maximal activity) is correlated with the pH-optimum of stability (the pH of maximal stability) on a set of 310 proteins with available experimental data. We speculate that such a correlation is needed to allow the corresponding macromolecules to tolerate small pH fluctuations that are inevitable with cellular function. Our findings rationalize the efforts of correlating the pH of maximal stability and the characteristic pH of subcellular compartments, as only pH of activity is subject of evolutionary pressure. In addition, our analysis confirmed the previous observation that pH-optimum of activity and stability are not correlated with the isoelectric point, pI, or with the optimal temperature. |
| Author | Talley, Kemper Alexov, Emil |
| Author_xml | – sequence: 1 givenname: Kemper surname: Talley fullname: Talley, Kemper organization: Computational Biophysics and Bioinformatics, Physics Department, Clemson University, Clemson, South Carolina 29634 – sequence: 2 givenname: Emil surname: Alexov fullname: Alexov, Emil email: ealexov@clemson.edu organization: Computational Biophysics and Bioinformatics, Physics Department, Clemson University, Clemson, South Carolina 29634 |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/20589630$$D View this record in MEDLINE/PubMed |
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| ProviderPackageCode | CITATION AAYXX |
| PublicationCentury | 2000 |
| PublicationDate | September 2010 |
| PublicationDateYYYYMMDD | 2010-09-01 |
| PublicationDate_xml | – month: 09 year: 2010 text: September 2010 |
| PublicationDecade | 2010 |
| PublicationPlace | Hoboken |
| PublicationPlace_xml | – name: Hoboken – name: United States |
| PublicationTitle | Proteins, structure, function, and bioinformatics |
| PublicationTitleAlternate | Proteins |
| PublicationYear | 2010 |
| Publisher | Wiley Subscription Services, Inc., A Wiley Company |
| Publisher_xml | – name: Wiley Subscription Services, Inc., A Wiley Company |
| References | Cedano J,Aloy P,Perez-Pons J,Querol E. Relation between amino acid composition and cellular location of proteins. J Mol Biol 1997; 266: 594-600. Cai YD,Lu L,Chen L,He JF. Predicting subcellular location of proteins using integrated-algorithm method. Mol Divers 2009. Epub ahead of print PMID: 19662505. Horiguchi M,Arita M,Kaempf-Rotzoll DE,Tsujimoto M,Inoue K,Arai H. pH-dependent translocation of alpha-tocopherol transfer protein (alpha-TTP) between hepatic cytosol and late endosomes. Genes Cells 2003; 8: 789-800. Luisi DL,Snow CD,Lin JJ,Hendsch ZS,Tidor B,Raleigh DP. Surface salt bridges, double-mutant cycles, and protein stability: an experimental and computational analysis of the interaction of the Asp 23 side chain with the N-terminus of the N-terminal domain of the ribosomal protein l9. Biochemistry 2003; 42: 7050-7060. Kawai C,Prado FM,Nunes GL,Di Mascio P,Carmona-Ribeiro AM,Nantes IL. pH-Dependent interaction of cytochrome c with mitochondrial mimetic membranes: the role of an array of positively charged amino acids. J Biol Chem 2005; 280: 34709-34717. Frenkel YV,Clark AD,Jr,Das K,Wang YH,Lewi PJ,Janssen PA,Arnold E. Concentration and pH dependent aggregation of hydrophobic drug molecules and relevance to oral bioavailability. J Med Chem 2005; 48: 1974-1983. Chang A,Scheer M,Grote A,Schomburg I,Schomburg D. BRENDA, AMENDA and FRENDA the enzyme information system: new content and tools in 2009. Nucleic Acids Res 2009; 37(Database issue): D588-D592. Garcia-Moreno B. Adaptations of proteins to cellular and subcellular pH. J Biol 2009; 8: 98. Khan A,Majid A,Choi TS. Predicting protein subcellular location: exploiting amino acid based sequence of feature spaces and fusion of diverse classifiers. Amino Acids 2010; 38: 347-350. Schreiber G,Fersht AR. Energetics of protein-protein interactions: analysis of the barnase-barstar interface by single mutations and double mutant cycles. J Mol Biol 1995; 248: 478-486. Cheng G,An F,Zou MJ,Sun J,Hao XH,He YX. Time- and pH-dependent colon-specific drug delivery for orally administered diclofenac sodium and 5-aminosalicylic acid. World J Gastroenterol 2004; 10: 1769-1774. Taylor PD,Attwood TK,Flower DR. Combining algorithms to predict bacterial protein sub-cellular location: parallel versus concurrent implementations. Bioinformation 2006; 1: 285-289. Seela F,Budow S. pH-dependent assembly of DNA-gold nanoparticles based on the i-motif. Nucleosides Nucleotides Nucleic Acids 2007; 26: 755-759. Patel MM,Shah TJ,Amin AF,Shah NN. Design, Development and Optimization of a Novel Time and pH-Dependent Colon Targeted Drug Delivery System. Pharm Dev Technol 2009; 14: 62-69. Sato S,Raleigh DP. pH-dependent stability and folding kinetics of a protein with an unusual alpha-beta topology: the C-terminal domain of the ribosomal protein L9. J Mol Biol 2002; 318: 571-582. Schreiber G,Fersht AR. Interaction of barnase with its popypeptide inhibitor barstar studied by protein engineering. Biochemistry 1993; 32: 5145-5150. Petkova AT,Buntkowsky G,Dyda F,Leapman RD,Yau WM,Tycko R. Solid state NMR reveals a pH-dependent antiparallel beta-sheet registry in fibrils formed by a beta-amyloid peptide. J Mol Biol 2004; 335: 247-260. Nair R,Rost B. Mimicking cellular sorting improves prediction of subcellular localization. J Mol Biol 2005; 348: 85-100. Qiu JD,Luo SH,Huang JH,Sun XY,Liang RP. Predicting subcellular location of apoptosis proteins based on wavelet transform and support vector machine. Amino Acids 2010; 38: 1201-1208. Wood DO,Lee JS. Investigation of pH-dependent DNA-metal ion interactions by surface plasmon resonance. J Inorg Biochem 2005; 99: 566-574. Emanuelsson O,Nielsen H,Brunak S,Heijne G. Predicting subcellular localization of proteins based on their N-terminal amino acid sequence. J Mol Biol 2000; 300: 1005-1016. Horng JC,Demarest SJ,Raleigh DP. pH-dependent stability of the human alpha-lactalbumin molten globule state: contrasting roles of the 6 - 120 disulfide and the beta-subdomain at low and neutral pH. Proteins 2003; 52: 193-202. Lindman S,Linse S,Mulder FA,Andre I. pK(a) values for side-chain carboxyl groups of a PGB1 variant explain salt and pH-dependent stability. Biophys J 2007; 92: 257-266. Srivastava J,Barreiro G,Groscurth S,Gingras AR,Goult BT,Critchley DR,Kelly MJ,Jacobson MP,Barber DL. Structural model and functional significance of pH-dependent talin-actin binding for focal adhesion remodeling. Proc Natl Acad Sci USA 2008; 105: 14436-14441. Skoulakis S,Goodfellow JM. The pH-dependent stability of wild-type and mutant transthyretin oligomers. Biophys J 2003; 84: 2795-2804. Yoo SH. pH-dependent interaction of chromogranin A with integral membrane proteins of secretory vesicle including 260-kDa protein reactive to inositol 1,4,5-triphosphate receptor antibody. J Biol Chem 1994; 269: 12001-12006. Chou KC. Using functional domain composition and support vector machines for prediction of protein subcellular location. J Biol Chem 2002; 277: 45765-45769. Mazzini A,Polverini E,Parisi M,Sorbi RT,Favilla R. Dissociation and unfolding of bovine odorant binding protein at acidic pH. JStruct Biol 2007; 159: 82-91. Chan P,Warwicker J. Evidence for the adaptation of protein pH-dependence to subcellular pH. BMC Biol 2009; 7: 69. Luisi DL,Raleigh DP. pH-dependent interactions and the stability and folding kinetics of the N-terminal domain of L9. Electrostatic interactions are only weakly formed in the transition state for folding. J Mol Biol 2000; 299: 1091-1100. Stapley BJ,Kelley LA,Sternberg MJ. Predicting the sub-cellular location of proteins from text using support vector machines. Pac Symp Biocomput 2002: 374-385. Perico N,Purtell J,Dillon TM,Ricci MS. Conformational implications of an inversed pH-dependent antibody aggregation. J Pharm Sci 2009; 98: 3031-3042. Chen Y,Yu P,Luo J,Jiang Y. Secreted protein prediction system combining CJ-SPHMM, TMHMM, and PSORT. Mamm Genome 2003; 14: 859-865. Alexov E. Numerical calculations of the pH of maximal protein stability. The effect of the sequence composition and 3D structure. Eur J Biochem 2004; 271: 173-185. Chou KC. Prediction of protein cellular attributes using pseudo-amino acid composition. Proteins 2001; 43: 246-255. Kall L,Krogh A,Sonnhammer EL. Advantages of combined transmembrane topology and signal peptide prediction-the Phobius web server. Nucleic Acids Res 2007; 35(Web Server issue): W429-W432. Kono K,Kimura S,Imanishi Y. pH-dependent interaction of amphiphilic polypeptide poly(Lys-Aib-Leu-Aib) with lipid bilayer membrane. Biochemistry 1990; 29: 3631-3637. Shin CJ,Wong S,Davis MJ,Ragan MA. Protein-protein interaction as a predictor of subcellular location. BMC Syst Biol 2009; 3: 28. Grey MJ,Tang Y,Alexov E,McKnight CJ,Raleigh DP,Palmer AG,III. Characterizing a partially folded intermediate of the villin headpiece domain under non-denaturing conditions: contribution of His41 to the pH-dependent stability of the N-terminal subdomain. J Mol Biol 2006; 355: 1078-1094. Garcia-Mayoral MF,del Pozo AM,Campos-Olivas R,Gavilanes JG,Santoro J,Rico M,Laurents DV,Bruix M. pH-Dependent conformational stability of the ribotoxin alpha-sarcin and four active site charge substitution variants. Biochemistry 2006; 45: 13705-13718. Pedersen S,Nesgaard L,Baptista RP,Melo EP,Kristensen SR,Otzen DE. pH-dependent aggregation of cutinase is efficiently suppressed by 1,8-ANS. Biopolymers 2006; 83: 619-629. Allemand JF,Bensimon D,Jullien L,Bensimon A,Croquette V. pH-dependent specific binding and combing of DNA. Biophys J 1997; 73: 2064-2070. Re F,Sesana S,Barbiroli A,Bonomi F,Cazzaniga E,Lonati E,Bulbarelli A,Masserini M. Prion protein structure is affected by pH-dependent interaction with membranes: a study in a model system. FEBS Lett 2008; 582: 215-220. Nasibov E,Kandemir-Cavas C. Protein subcellular location prediction using optimally weighted fuzzy k-NN algorithm. Comput Biol Chem 2008; 32: 448-451. Shatkay H,Hoglund A,Brady S,Blum T,Donnes P,Kohlbacher O. SherLoc: high-accuracy prediction of protein subcellular localization by integrating text and protein sequence data. Bioinformatics 2007; 23: 1410-1417. Srinivasan R,Jones EM,Liu K,Ghiso J,Marchant RE,Zagorski MG. pH-dependent amyloid and protofibril formation by the ABri peptide of familial British dementia. J Mol Biol 2003; 333: 1003-1023. Olson LJ,Hindsgaul O,Dahms NM,Kim JJ. Structural insights into the mechanism of pH-dependent ligand binding and release by the cation-dependent mannose 6-phosphate receptor. J Biol Chem 2008; 283: 10124-10134. Horng JC,Cho JH,Raleigh DP. Analysis of the pH-dependent folding and stability of histidine point mutants allows characterization of the denatured state and transition state for protein folding. J Mol Biol 2005; 345: 163-173. Zhou M,Boekhorst J,Francke C,Siezen RJ. LocateP: genome-scale subcellular-location predictor for bacterial proteins. BMC Bioinformatics 2008; 9: 173. Kundrotas PJ,Alexov E. Electrostatic properties of protein-protein complexes. Biophys J 2006; 91: 1724-1736. Brady S,Shatkay H. EpiLoc: a (working) text-based system for predicting protein subcellular location. Pac Symp Biocomput 2008: 604-615. Muga A,Gonzalez-Manas JM,Lakey JH,Pattus F,Surewicz WK. pH-dependent stability and membrane interaction of the pore-forming domain of colicin A. J Biol Chem 1993; 268: 1553-1557. Chan P,Lovric J,Warwicker J. Subcellular pH and predicted pH-dependent features of proteins. Proteomics 2006; 6: 3494-3501. Chaves FA,Richards KA,Torelli A,Wedekind J,Sant AJ. Peptide-binding motifs for the I-Ad MHC class II molecule: alternate pH-dependent binding behavior. Biochemistry 2006; 45: 6426-6433. Fuertes MA,Perez JM,Soto M,Menendez M,Alonso C. Thermodynamic stability of the C-terminal domain of the human inducible heat shock protein 70. Biochim Biophys Acta 2004; 1699: 45-56. Seela F,Chittepu P. Oligonucleotides containing 6-aza-2′-deoxyuridine: synthesis, nucleobase protection, pH-dependent duplex stability, and metal-DNA formation. J Org Chem 2007; 72: 4358-4366. Smedley JG,III,Sharp JS,Kuhn JF,Tomer KB. Pro 2002; 277 2008; 9 2003; 14 2008; 105 2008; 32 2007; 72 2002; 318 2000; 299 2003; 52 2008; 582 2007; 35 2001; 43 2004; 32 2009; 14 2004; 577 2004; 335 2009; 98 1994; 269 2005; 345 1993; 32 2003; 8 2007; 373 1997; 266 2005; 348 1995; 248 2003; 84 2007; 23 2003; 42 2004; 1699 2007; 26 2006; 91 2010; 38 2009 2008 2007; 92 2006; 6 2006; 1 2002 1993; 268 2005; 48 2003; 333 2008; 283 2006; 355 2004; 10 2007; 159 2005; 280 1997; 73 2006; 83 2006; 45 2000; 300 1990; 29 2004; 271 2008; 47 2009; 8 2009; 7 2009; 3 2005; 99 2009; 37 e_1_2_6_51_2 e_1_2_6_53_2 e_1_2_6_30_2 Stapley BJ (e_1_2_6_50_2) 2002 e_1_2_6_19_2 e_1_2_6_13_2 e_1_2_6_34_2 e_1_2_6_59_2 e_1_2_6_11_2 e_1_2_6_32_2 e_1_2_6_17_2 e_1_2_6_38_2 e_1_2_6_55_2 e_1_2_6_15_2 e_1_2_6_36_2 e_1_2_6_57_2 e_1_2_6_62_2 e_1_2_6_20_2 e_1_2_6_41_2 e_1_2_6_60_2 e_1_2_6_7_2 e_1_2_6_3_2 e_1_2_6_5_2 e_1_2_6_24_2 e_1_2_6_47_2 e_1_2_6_22_2 e_1_2_6_28_2 e_1_2_6_43_2 Brady S (e_1_2_6_49_2) 2008 e_1_2_6_26_2 e_1_2_6_45_2 e_1_2_6_52_2 e_1_2_6_31_2 e_1_2_6_18_2 e_1_2_6_12_2 e_1_2_6_35_2 e_1_2_6_58_2 e_1_2_6_10_2 e_1_2_6_33_2 e_1_2_6_16_2 e_1_2_6_39_2 e_1_2_6_54_2 e_1_2_6_14_2 e_1_2_6_37_2 e_1_2_6_56_2 e_1_2_6_61_2 e_1_2_6_42_2 e_1_2_6_40_2 Fuertes MA (e_1_2_6_9_2) 2004; 1699 e_1_2_6_8_2 e_1_2_6_29_2 e_1_2_6_4_2 e_1_2_6_6_2 e_1_2_6_23_2 e_1_2_6_48_2 e_1_2_6_2_2 e_1_2_6_21_2 e_1_2_6_27_2 e_1_2_6_44_2 e_1_2_6_25_2 e_1_2_6_46_2 |
| References_xml | – reference: Cai YD,Lu L,Chen L,He JF. Predicting subcellular location of proteins using integrated-algorithm method. Mol Divers 2009. Epub ahead of print PMID: 19662505. – reference: Schreiber G,Fersht AR. Interaction of barnase with its popypeptide inhibitor barstar studied by protein engineering. Biochemistry 1993; 32: 5145-5150. – reference: Pedersen S,Nesgaard L,Baptista RP,Melo EP,Kristensen SR,Otzen DE. pH-dependent aggregation of cutinase is efficiently suppressed by 1,8-ANS. Biopolymers 2006; 83: 619-629. – reference: Horng JC,Demarest SJ,Raleigh DP. pH-dependent stability of the human alpha-lactalbumin molten globule state: contrasting roles of the 6 - 120 disulfide and the beta-subdomain at low and neutral pH. Proteins 2003; 52: 193-202. – reference: Kono K,Kimura S,Imanishi Y. pH-dependent interaction of amphiphilic polypeptide poly(Lys-Aib-Leu-Aib) with lipid bilayer membrane. Biochemistry 1990; 29: 3631-3637. – reference: Srivastava J,Barreiro G,Groscurth S,Gingras AR,Goult BT,Critchley DR,Kelly MJ,Jacobson MP,Barber DL. Structural model and functional significance of pH-dependent talin-actin binding for focal adhesion remodeling. Proc Natl Acad Sci USA 2008; 105: 14436-14441. – reference: Frenkel YV,Clark AD,Jr,Das K,Wang YH,Lewi PJ,Janssen PA,Arnold E. Concentration and pH dependent aggregation of hydrophobic drug molecules and relevance to oral bioavailability. J Med Chem 2005; 48: 1974-1983. – reference: Smedley JG,III,Sharp JS,Kuhn JF,Tomer KB. Probing the pH-dependent prepore to pore transition of Bacillus anthracis protective antigen with differential oxidative protein footprinting. Biochemistry 2008; 47: 10694-10704. – reference: Barthelmes J,Ebeling C,Chang A,Schomburg I,Schomburg D. BRENDA, AMENDA and FRENDA: the enzyme information system in 2007. Nucleic Acids Res 2007; 35(Database issue): D511-D514. – reference: Allemand JF,Bensimon D,Jullien L,Bensimon A,Croquette V. pH-dependent specific binding and combing of DNA. Biophys J 1997; 73: 2064-2070. – reference: Nasibov E,Kandemir-Cavas C. Protein subcellular location prediction using optimally weighted fuzzy k-NN algorithm. Comput Biol Chem 2008; 32: 448-451. – reference: Garcia-Mayoral MF,del Pozo AM,Campos-Olivas R,Gavilanes JG,Santoro J,Rico M,Laurents DV,Bruix M. pH-Dependent conformational stability of the ribotoxin alpha-sarcin and four active site charge substitution variants. Biochemistry 2006; 45: 13705-13718. – reference: Luisi DL,Snow CD,Lin JJ,Hendsch ZS,Tidor B,Raleigh DP. Surface salt bridges, double-mutant cycles, and protein stability: an experimental and computational analysis of the interaction of the Asp 23 side chain with the N-terminus of the N-terminal domain of the ribosomal protein l9. Biochemistry 2003; 42: 7050-7060. – reference: Sato S,Raleigh DP. pH-dependent stability and folding kinetics of a protein with an unusual alpha-beta topology: the C-terminal domain of the ribosomal protein L9. J Mol Biol 2002; 318: 571-582. – reference: Olson LJ,Hindsgaul O,Dahms NM,Kim JJ. Structural insights into the mechanism of pH-dependent ligand binding and release by the cation-dependent mannose 6-phosphate receptor. J Biol Chem 2008; 283: 10124-10134. – reference: Mazzini A,Polverini E,Parisi M,Sorbi RT,Favilla R. Dissociation and unfolding of bovine odorant binding protein at acidic pH. JStruct Biol 2007; 159: 82-91. – reference: Nair R,Rost B. Mimicking cellular sorting improves prediction of subcellular localization. J Mol Biol 2005; 348: 85-100. – reference: Stapley BJ,Kelley LA,Sternberg MJ. Predicting the sub-cellular location of proteins from text using support vector machines. Pac Symp Biocomput 2002: 374-385. – reference: Qiu JD,Luo SH,Huang JH,Sun XY,Liang RP. Predicting subcellular location of apoptosis proteins based on wavelet transform and support vector machine. Amino Acids 2010; 38: 1201-1208. – reference: Fuertes MA,Perez JM,Soto M,Menendez M,Alonso C. Thermodynamic stability of the C-terminal domain of the human inducible heat shock protein 70. Biochim Biophys Acta 2004; 1699: 45-56. – reference: Brady S,Shatkay H. EpiLoc: a (working) text-based system for predicting protein subcellular location. Pac Symp Biocomput 2008: 604-615. – reference: Seela F,Chittepu P. Oligonucleotides containing 6-aza-2′-deoxyuridine: synthesis, nucleobase protection, pH-dependent duplex stability, and metal-DNA formation. J Org Chem 2007; 72: 4358-4366. – reference: Alexov E. Numerical calculations of the pH of maximal protein stability. The effect of the sequence composition and 3D structure. Eur J Biochem 2004; 271: 173-185. – reference: Kawai C,Prado FM,Nunes GL,Di Mascio P,Carmona-Ribeiro AM,Nantes IL. pH-Dependent interaction of cytochrome c with mitochondrial mimetic membranes: the role of an array of positively charged amino acids. J Biol Chem 2005; 280: 34709-34717. – reference: Grey MJ,Tang Y,Alexov E,McKnight CJ,Raleigh DP,Palmer AG,III. Characterizing a partially folded intermediate of the villin headpiece domain under non-denaturing conditions: contribution of His41 to the pH-dependent stability of the N-terminal subdomain. J Mol Biol 2006; 355: 1078-1094. – reference: Khan A,Majid A,Choi TS. Predicting protein subcellular location: exploiting amino acid based sequence of feature spaces and fusion of diverse classifiers. Amino Acids 2010; 38: 347-350. – reference: Skoulakis S,Goodfellow JM. The pH-dependent stability of wild-type and mutant transthyretin oligomers. Biophys J 2003; 84: 2795-2804. – reference: Perico N,Purtell J,Dillon TM,Ricci MS. Conformational implications of an inversed pH-dependent antibody aggregation. J Pharm Sci 2009; 98: 3031-3042. – reference: Seela F,Budow S. pH-dependent assembly of DNA-gold nanoparticles based on the i-motif. Nucleosides Nucleotides Nucleic Acids 2007; 26: 755-759. – reference: Chan P,Warwicker J. Evidence for the adaptation of protein pH-dependence to subcellular pH. BMC Biol 2009; 7: 69. – reference: Horiguchi M,Arita M,Kaempf-Rotzoll DE,Tsujimoto M,Inoue K,Arai H. pH-dependent translocation of alpha-tocopherol transfer protein (alpha-TTP) between hepatic cytosol and late endosomes. Genes Cells 2003; 8: 789-800. – reference: Cedano J,Aloy P,Perez-Pons J,Querol E. Relation between amino acid composition and cellular location of proteins. J Mol Biol 1997; 266: 594-600. – reference: Schreiber G,Fersht AR. Energetics of protein-protein interactions: analysis of the barnase-barstar interface by single mutations and double mutant cycles. J Mol Biol 1995; 248: 478-486. – reference: Patel MM,Shah TJ,Amin AF,Shah NN. Design, Development and Optimization of a Novel Time and pH-Dependent Colon Targeted Drug Delivery System. Pharm Dev Technol 2009; 14: 62-69. – reference: Garcia-Moreno B. Adaptations of proteins to cellular and subcellular pH. J Biol 2009; 8: 98. – reference: Imamoto Y,Harigai M,Kataoka M. Direct observation of the pH-dependent equilibrium between L-like and M intermediates of photoactive yellow protein. FEBS Lett 2004; 577: 75-80. – reference: Yoo SH. pH-dependent interaction of chromogranin A with integral membrane proteins of secretory vesicle including 260-kDa protein reactive to inositol 1,4,5-triphosphate receptor antibody. J Biol Chem 1994; 269: 12001-12006. – reference: Chou KC. Prediction of protein cellular attributes using pseudo-amino acid composition. Proteins 2001; 43: 246-255. – reference: Chang A,Scheer M,Grote A,Schomburg I,Schomburg D. BRENDA, AMENDA and FRENDA the enzyme information system: new content and tools in 2009. Nucleic Acids Res 2009; 37(Database issue): D588-D592. – reference: Kundrotas PJ,Alexov E. Electrostatic properties of protein-protein complexes. Biophys J 2006; 91: 1724-1736. – reference: Petkova AT,Buntkowsky G,Dyda F,Leapman RD,Yau WM,Tycko R. Solid state NMR reveals a pH-dependent antiparallel beta-sheet registry in fibrils formed by a beta-amyloid peptide. J Mol Biol 2004; 335: 247-260. – reference: Wood DO,Lee JS. Investigation of pH-dependent DNA-metal ion interactions by surface plasmon resonance. J Inorg Biochem 2005; 99: 566-574. – reference: Nair R,Rost B. LOCnet and LOCtarget: sub-cellular localization for structural genomics targets. Nucleic Acids Res 2004; 32(Web Server issue): W517-W521. – reference: Chou KC. Using functional domain composition and support vector machines for prediction of protein subcellular location. J Biol Chem 2002; 277: 45765-45769. – reference: Kall L,Krogh A,Sonnhammer EL. Advantages of combined transmembrane topology and signal peptide prediction-the Phobius web server. Nucleic Acids Res 2007; 35(Web Server issue): W429-W432. – reference: Lindman S,Linse S,Mulder FA,Andre I. pK(a) values for side-chain carboxyl groups of a PGB1 variant explain salt and pH-dependent stability. Biophys J 2007; 92: 257-266. – reference: Luisi DL,Raleigh DP. pH-dependent interactions and the stability and folding kinetics of the N-terminal domain of L9. Electrostatic interactions are only weakly formed in the transition state for folding. J Mol Biol 2000; 299: 1091-1100. – reference: Chen Y,Yu P,Luo J,Jiang Y. Secreted protein prediction system combining CJ-SPHMM, TMHMM, and PSORT. Mamm Genome 2003; 14: 859-865. – reference: Zhou M,Boekhorst J,Francke C,Siezen RJ. LocateP: genome-scale subcellular-location predictor for bacterial proteins. BMC Bioinformatics 2008; 9: 173. – reference: Hom RA,Vora M,Regner M,Subach OM,Cho W,Verkhusha VV,Stahelin RV,Kutateladze TG. pH-dependent binding of the Epsin ENTH domain and the AP180 ANTH domain to PI(4,5)P2-containing bilayers. J Mol Biol 2007; 373: 412-423. – reference: Re F,Sesana S,Barbiroli A,Bonomi F,Cazzaniga E,Lonati E,Bulbarelli A,Masserini M. Prion protein structure is affected by pH-dependent interaction with membranes: a study in a model system. FEBS Lett 2008; 582: 215-220. – reference: Muga A,Gonzalez-Manas JM,Lakey JH,Pattus F,Surewicz WK. pH-dependent stability and membrane interaction of the pore-forming domain of colicin A. J Biol Chem 1993; 268: 1553-1557. – reference: Emanuelsson O,Nielsen H,Brunak S,Heijne G. Predicting subcellular localization of proteins based on their N-terminal amino acid sequence. J Mol Biol 2000; 300: 1005-1016. – reference: Srinivasan R,Jones EM,Liu K,Ghiso J,Marchant RE,Zagorski MG. pH-dependent amyloid and protofibril formation by the ABri peptide of familial British dementia. J Mol Biol 2003; 333: 1003-1023. – reference: Horng JC,Cho JH,Raleigh DP. Analysis of the pH-dependent folding and stability of histidine point mutants allows characterization of the denatured state and transition state for protein folding. J Mol Biol 2005; 345: 163-173. – reference: Chaves FA,Richards KA,Torelli A,Wedekind J,Sant AJ. Peptide-binding motifs for the I-Ad MHC class II molecule: alternate pH-dependent binding behavior. Biochemistry 2006; 45: 6426-6433. – reference: Cheng G,An F,Zou MJ,Sun J,Hao XH,He YX. Time- and pH-dependent colon-specific drug delivery for orally administered diclofenac sodium and 5-aminosalicylic acid. World J Gastroenterol 2004; 10: 1769-1774. – reference: Shin CJ,Wong S,Davis MJ,Ragan MA. 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| Title | On the pH-optimum of activity and stability of proteins |
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