Quantitative and Qualitative Analysis of Type III Antifreeze Protein Structure and Function

Abstract

Some cold water marine fishes avoid cellular damage because of freezing by expressing antifreeze proteins (AFPs) that bind to ice and inhibit its growth; one such protein is the globular type III AFP from eel pout. Despite several studies, the mechanism of ice binding remains unclear because of the difficulty in modeling the AFP-ice interaction. To further explore the mechanism, we have determined the x-ray crystallographic structure of 10 type III AFP mutants and combined that information with 7 previously determined structures to mainly analyze specific AFP-ice interactions such as hydrogen bonds. Quantitative assessment of binding was performed using a neural network with properties of the structure as input and predicted antifreeze activity as output. Using the cross-validation method, a correlation coefficient of 0.60 was obtained between measured and predicted activity, indicating successful learning and good predictive power. A large loss in the predictive power of the neural network occurred after properties related to the hydrophobic surface were left out, suggesting that van der Waal's interactions make a significant contribution to ice binding. By combining the analysis of the neural network with antifreeze activity and x-ray crystallographic structures of the mutants, we extend the existing ice-binding model to a two-step process: 1) probing of the surface for the correct ice-binding plane by hydrogen-bonding side chains and 2) attractive van der Waal's interactions between the other residues of the ice-binding surface and the ice, which increases the strength of the protein-ice interaction. Some cold water marine fishes avoid cellular damage because of freezing by expressing antifreeze proteins (AFPs) that bind to ice and inhibit its growth; one such protein is the globular type III AFP from eel pout. Despite several studies, the mechanism of ice binding remains unclear because of the difficulty in modeling the AFP-ice interaction. To further explore the mechanism, we have determined the x-ray crystallographic structure of 10 type III AFP mutants and combined that information with 7 previously determined structures to mainly analyze specific AFP-ice interactions such as hydrogen bonds. Quantitative assessment of binding was performed using a neural network with properties of the structure as input and predicted antifreeze activity as output. Using the cross-validation method, a correlation coefficient of 0.60 was obtained between measured and predicted activity, indicating successful learning and good predictive power. A large loss in the predictive power of the neural network occurred after properties related to the hydrophobic surface were left out, suggesting that van der Waal's interactions make a significant contribution to ice binding. By combining the analysis of the neural network with antifreeze activity and x-ray crystallographic structures of the mutants, we extend the existing ice-binding model to a two-step process: 1) probing of the surface for the correct ice-binding plane by hydrogen-bonding side chains and 2) attractive van der Waal's interactions between the other residues of the ice-binding surface and the ice, which increases the strength of the protein-ice interaction. antifreeze protein thermal hysteresis accessible surface area Many poikilothermic organisms have developed antifreeze proteins (AFPs)1 to resist freezing. Five classes of structurally diverse antifreeze proteins have been found in fish (for a review, see Ref. 1Davies P.L. Sykes B.D. Curr. Opin. Struct. Biol. 1997; 7: 828-834Crossref PubMed Scopus (186) Google Scholar). These proteins act by adsorbing to the surface of ice and increasing the curvature of ice fronts between the bound AFPs (2Raymond J.A. DeVries A.L. Proc. Natl. Acad. Sci. U. S. A. 1977; 74: 2589-2593Crossref PubMed Scopus (661) Google Scholar). The freezing point at the surface is depressed, which in turn inhibits the growth of ice crystals. The difference between the temperature at which the ice begins to grow (burst point) and the temperature at which the ice crystal melts is known as thermal hysteresis (TH) and is used as a measure of AFP activity.Recently, several structures of type III AFP have been determined (4Jia Z. DeLuca C.I. Chao H. Davies P.L. Nature. 1996; 384: 285-288Crossref PubMed Scopus (220) Google Scholar, 5Soennichsen F.D. DeLuca C.I. Davies P.L. Sykes B.D. Structure (Lond.). 1996; 4: 1325-1337Abstract Full Text Full Text PDF PubMed Scopus (164) Google Scholar, 6Yang D.S. Hon W.C. Bubanko S. Xue Y. Seetharaman J. Hew C.L. Sicheri F. Biophys. J. 1998; 74: 2142-2151Abstract Full Text Full Text PDF PubMed Scopus (121) Google Scholar). Based on the high-resolution x-ray structure (4Jia Z. DeLuca C.I. Chao H. Davies P.L. Nature. 1996; 384: 285-288Crossref PubMed Scopus (220) Google Scholar), a model was proposed whereby surface adsorption occurs through a hydrogen bond match between the side chains of Gln-9, Asn-14, Thr-15, Thr-18, Gln-44, and the ice prism plane { 101¯0}. These polar residues form part of a flat, amphipathic face that is thought to be the ice-binding surface (Fig. 1). However, the significance of the contribution from hydrogen bonds to the AFP-ice interaction has been questioned by several studies since then. A supposedly conservative change of Thr to Ser in type I AFP led to a large loss of TH activity, whereas a change to the hydrophobic residue valine, which is a better space-filling match, caused only a small loss (7Chao H. Houston Jr., M.E. Hodges R.S. Kay C.M. Sykes B.D. Loewen M.C. Davies P.L. Sonnichsen F.D. Biochemistry. 1997; 36: 14652-14660Crossref PubMed Scopus (201) Google Scholar, 8Haymet A.D. Ward L.G. Harding M.M Knight C.A. FEBS Lett. 1998; 430: 301-306Crossref PubMed Scopus (143) Google Scholar). In the study of the high precision NMR structures of type III AFP (5Soennichsen F.D. DeLuca C.I. Davies P.L. Sykes B.D. Structure (Lond.). 1996; 4: 1325-1337Abstract Full Text Full Text PDF PubMed Scopus (164) Google Scholar), the authors argue that hydrogen bonds alone are not sufficient to explain the affinity of the protein for ice because formation of hydrogen bonds between ice and solvent water is enthalpically more favorable because of the “perfect” alignment of water with ice. The less favorable interaction between ice and AFP could be overcome by gain in entropy because of the release of protein-associated water into the bulk solvent. Shape complementarity was examined experimentally by mutating Ala-16, a residue that is located in the center of the putative ice-binding surface (9DeLuca C.I. Davies P.L Ye Q. Jia Z. J. Mol. Biol. 1998; 275: 515-525Crossref PubMed Scopus (78) Google Scholar). The loss of activity in these mutants approximately correlates with the size of the residue substituted for Ala. However, structural interpretation of these changes was complicated by shifts in adjacent residues because of the tight packing of residues at the surface.A fundamental problem in testing binding hypotheses is the difficulty in analyzing interactions in a quantitative manner. In the crystallographic structure determination of the SP-isoform of type III AFP (6Yang D.S. Hon W.C. Bubanko S. Xue Y. Seetharaman J. Hew C.L. Sicheri F. Biophys. J. 1998; 74: 2142-2151Abstract Full Text Full Text PDF PubMed Scopus (121) Google Scholar), it is also argued that hydrogen bonds are insufficient for tight binding and that flatness is perhaps a more important factor. A flatness search algorithm was designed and used to show that the proposed ice-binding surface is the flattest in the SP-isoform of type III AFP. However, in the case of the QAE-isoform of type III AFP, the putative ice-binding surface is only the second flattest plane, 2Brent Wathen, personal communication. 2Brent Wathen, personal communication. which questions the relative significance of flatness.In this study, we prepared and expressed an additional 10 mutants of the eel pout type III AFP and determined their structures to probe their contribution to the activity of the protein. Data from previous studies were also re-examined and compared. In addition, we have used a neural network (10Presnell S.R. Cohen F.E. Annu. Rev. Biophys. Biomol. Struct. 1993; 22: 283-298Crossref PubMed Scopus (46) Google Scholar, 11Müller B. Reinhardt J. Strickland M.T. Neural Networks. An Introduction. 2nd Ed. Springer-Verlag New York Inc., New York1995Google Scholar) to predict TH activity. Analysis of the structures and the neural network results shows that changes in van der Waal's interactions and to a lesser extent, hydrogen bonds, are responsible for the loss of activity in type III AFP mutants. Many poikilothermic organisms have developed antifreeze proteins (AFPs)1 to resist freezing. Five classes of structurally diverse antifreeze proteins have been found in fish (for a review, see Ref. 1Davies P.L. Sykes B.D. Curr. Opin. Struct. Biol. 1997; 7: 828-834Crossref PubMed Scopus (186) Google Scholar). These proteins act by adsorbing to the surface of ice and increasing the curvature of ice fronts between the bound AFPs (2Raymond J.A. DeVries A.L. Proc. Natl. Acad. Sci. U. S. A. 1977; 74: 2589-2593Crossref PubMed Scopus (661) Google Scholar). The freezing point at the surface is depressed, which in turn inhibits the growth of ice crystals. The difference between the temperature at which the ice begins to grow (burst point) and the temperature at which the ice crystal melts is known as thermal hysteresis (TH) and is used as a measure of AFP activity. Recently, several structures of type III AFP have been determined (4Jia Z. DeLuca C.I. Chao H. Davies P.L. Nature. 1996; 384: 285-288Crossref PubMed Scopus (220) Google Scholar, 5Soennichsen F.D. DeLuca C.I. Davies P.L. Sykes B.D. Structure (Lond.). 1996; 4: 1325-1337Abstract Full Text Full Text PDF PubMed Scopus (164) Google Scholar, 6Yang D.S. Hon W.C. Bubanko S. Xue Y. Seetharaman J. Hew C.L. Sicheri F. Biophys. J. 1998; 74: 2142-2151Abstract Full Text Full Text PDF PubMed Scopus (121) Google Scholar). Based on the high-resolution x-ray structure (4Jia Z. DeLuca C.I. Chao H. Davies P.L. Nature. 1996; 384: 285-288Crossref PubMed Scopus (220) Google Scholar), a model was proposed whereby surface adsorption occurs through a hydrogen bond match between the side chains of Gln-9, Asn-14, Thr-15, Thr-18, Gln-44, and the ice prism plane { 101¯0}. These polar residues form part of a flat, amphipathic face that is thought to be the ice-binding surface (Fig. 1). However, the significance of the contribution from hydrogen bonds to the AFP-ice interaction has been questioned by several studies since then. A supposedly conservative change of Thr to Ser in type I AFP led to a large loss of TH activity, whereas a change to the hydrophobic residue valine, which is a better space-filling match, caused only a small loss (7Chao H. Houston Jr., M.E. Hodges R.S. Kay C.M. Sykes B.D. Loewen M.C. Davies P.L. Sonnichsen F.D. Biochemistry. 1997; 36: 14652-14660Crossref PubMed Scopus (201) Google Scholar, 8Haymet A.D. Ward L.G. Harding M.M Knight C.A. FEBS Lett. 1998; 430: 301-306Crossref PubMed Scopus (143) Google Scholar). In the study of the high precision NMR structures of type III AFP (5Soennichsen F.D. DeLuca C.I. Davies P.L. Sykes B.D. Structure (Lond.). 1996; 4: 1325-1337Abstract Full Text Full Text PDF PubMed Scopus (164) Google Scholar), the authors argue that hydrogen bonds alone are not sufficient to explain the affinity of the protein for ice because formation of hydrogen bonds between ice and solvent water is enthalpically more favorable because of the “perfect” alignment of water with ice. The less favorable interaction between ice and AFP could be overcome by gain in entropy because of the release of protein-associated water into the bulk solvent. Shape complementarity was examined experimentally by mutating Ala-16, a residue that is located in the center of the putative ice-binding surface (9DeLuca C.I. Davies P.L Ye Q. Jia Z. J. Mol. Biol. 1998; 275: 515-525Crossref PubMed Scopus (78) Google Scholar). The loss of activity in these mutants approximately correlates with the size of the residue substituted for Ala. However, structural interpretation of these changes was complicated by shifts in adjacent residues because of the tight packing of residues at the surface. A fundamental problem in testing binding hypotheses is the difficulty in analyzing interactions in a quantitative manner. In the crystallographic structure determination of the SP-isoform of type III AFP (6Yang D.S. Hon W.C. Bubanko S. Xue Y. Seetharaman J. Hew C.L. Sicheri F. Biophys. J. 1998; 74: 2142-2151Abstract Full Text Full Text PDF PubMed Scopus (121) Google Scholar), it is also argued that hydrogen bonds are insufficient for tight binding and that flatness is perhaps a more important factor. A flatness search algorithm was designed and used to show that the proposed ice-binding surface is the flattest in the SP-isoform of type III AFP. However, in the case of the QAE-isoform of type III AFP, the putative ice-binding surface is only the second flattest plane, 2Brent Wathen, personal communication. 2Brent Wathen, personal communication. which questions the relative significance of flatness. In this study, we prepared and expressed an additional 10 mutants of the eel pout type III AFP and determined their structures to probe their contribution to the activity of the protein. Data from previous studies were also re-examined and compared. In addition, we have used a neural network (10Presnell S.R. Cohen F.E. Annu. Rev. Biophys. Biomol. Struct. 1993; 22: 283-298Crossref PubMed Scopus (46) Google Scholar, 11Müller B. Reinhardt J. Strickland M.T. Neural Networks. An Introduction. 2nd Ed. Springer-Verlag New York Inc., New York1995Google Scholar) to predict TH activity. Analysis of the structures and the neural network results shows that changes in van der Waal's interactions and to a lesser extent, hydrogen bonds, are responsible for the loss of activity in type III AFP mutants. We thank Sherry Gauthier and Dr. Qilu Ye for their excellent technical assistance. We are also grateful to Brent Wathen for help running the neural network.