Department of Chemistry, Technical University of Denmark, Building 206, DK-2800, Lyngby, Denmark and 1 Biostructure Group, Novo Nordisk A/S, Novo Nordisk Park, DK-2760 Måløv, Denmark
![]() |
Abstract |
---|
![]() ![]() ![]() ![]() ![]() ![]() |
---|
Keywords: enzyme/essential dynamics/molecular modelling/protein stability/structurefunction relationships/site-directed mutagenesis
![]() |
Introduction |
---|
![]() ![]() ![]() ![]() ![]() ![]() |
---|
The structural basis for interfacial activation has been revealed by X-ray crystallography of lipases in complex with inhibitors or co-crystallized with micelles. Three-dimensional lipase structures from Rhizomucor miehei (Brady et al., 1990; Derewenda et al., 1992a
), human pancreatic (Winkler et al., 1990
), Geotrichum candidum (Schrag and Cygler, 1993
), Candida rugosa (Grochulski et al., 1993
), Rhizopus delemar (Derewenda, 1994b), Pseudomonas glumae (Noble et al., 1993
), Penicillium camembertii (Derewenda et al., 1994a
) and Humicola lanuginosa (Lawson et al., 1994
) have been determined to high resolution. These studies provide considerable insight into the structurefunction relationships in lipases. The crystal structures indicated that these lipases all have a common
/ß-hydrolase fold (Ollis et al., 1992
; Cygler et al., 1993
), a catalytic triad (SerHisAsp/Glu) similar to that found in serine proteases (Kraut, 1977
) and a lid covering the active site making it inaccessible to the substrate. The lid, however, is not a ubiquitous feature and it has been found that some lipolytic enzymes have solvent accessible active sites (Martinez et al., 1992
; Hjort et al., 1993
; Uppenberg et al., 1994
).
The functional consequences of the structural changes observed during lipase activation are pronounced. As revealed by the crystallographic studies of the enzymeinhibitor complexes of Rhizomucor miehei lipase (Brzozowski et al., 1991; Derewenda et al., 1992b
), the pancreatic lipaseprocolipase complex crystallized in the presence of mixed micelles (van Tilbeurgh et al., 1993
) and the structure of the Candida rugosa lipase which was crystallized in the open conformation (Grochulski et al., 1993
), the conformational change observed during activation is governed by a rigid body hinge-type motion of single or multiple helices (Derewenda et al., 1994b
). During activation, the lid covering the active site is displaced by several Ångströms. This lid movement opens up the binding pocket and the active site becomes accessible to the substrate. Additionally, the movement causes (i) polar residues on the helical lid to be buried, (ii) water molecules bound at the polar protein surface in the closed conformer to be displaced and (iii) a hydrophobic lipid-binding surface adjacent to the lid to become exposed (Derewenda, 1994c
). All these contributions add favorable enthalpic and entropic terms to the stability of the activated enzyme (Dodson et al., 1992
). Experimental and computational studies have shown that electrostatic interactions mediate the contact between the active site lid and the protein surface in the activated lipases (Derewenda et al., 1992b
; van Tilbeurgh et al., 1993
; Peters et al., 1996a
and 1997
). One of the most convincing demonstrations of the functional importance of electrostatic interactions came from site-directed mutation of single titratable residues in the active site lid. Mutation of key residues in the lid decreases the catalytic activity of Rhizomucor miehei lipase (Rml) (Holmquist et al., 1993
). Protein motions are complex in nature and depend inter alia on the nature of the amino acid residue side chains. It is anticipated that certain residue types will have a more significant effect on motion than others, e.g. glycines, due to their small size, and prolines, due to their cyclic structure. Indeed, single site mutations of glycines or of non-glycine residues at other sites to glycines can have remarkable effects on the biological function of enzymes and can be lethal. Mutations involving glycines invariably affect protein stability (Hecht et al., 1986
; Matthews, 1987
; Berndt et al., 1993
), and have been stated to be the cause of reduced catalytic activity (Wilkinson et al., 1983
; Jancso and Szent-Györgyi, 1994
), and of changes in enzyme specificity (Vermersch et al., 1990
). Moreover, such mutations have been implicated as being the etiological factor in diseases such as lipoprotein lipase deficiency (Henderson et al., 1992
; Busca et al., 1996
), haemolytic anaemia (Vulliamy et al., 1988
), Alzheimer disease (Mann et al., 1992
) or insulin resistance (Almind et al., 1996
).
The alteration in the protein function could arise from a variety of sources involving changes in the tertiary structure, changes in the protein flexibility or disruption of hydrogen bonds (Subbiah, 1996). Of course, the effect of the mutation on the protein function will depend on the protein architecture and may involve destabilization of the enzymesubstrate or enzymetransition-state complexes resulting in changes in binding and catalysis. If the enzymesubstrate complex is destabilized relative to the enzymetransition-state complex a rate acceleration may ensue, while if the enzymetransition-state complex is destabilized the catalysis will be impaired.
An important concept in considering substrate recognition and binding which has emerged from studies of many enzymes is that of induced fit (Koshland, 1958). We surmise that many of the fluctuations that we observe in this work fall into this category. In view of the importance of glycines and prolines in protein function we have investigated the protein dynamics of Rml and the extent of fluctuations around these residues. In particular, we are interested in the mobility of the active site lid and two loop regions, Gly35Lys50 and Thr57Asn63. In our previous study, we concluded that both loop regions are important for the function of lipases (Peters et al., 1996b
) and their mobility is influenced by solvent polarity and bound inhibitor. Information about concerted atomic motions in the protein were extracted by applying the essential dynamics analysis technique (Amadei et al., 1993
). This technique has previously been used (i) to correlate essential motions in lysozyme (Amadei et al., 1993
), thermolysin (Van Aalten et al., 1995
) and lipases (Peters et al., 1996b
) to their biological function and (ii) to suggest point mutations in retinol-binding proteins (Van Aalten et al., 1997
).
![]() |
Materials and methods |
---|
![]() ![]() ![]() ![]() ![]() ![]() |
---|
The simulations were performed using periodic boundary conditions with a truncated octahedron central cell at a temperature of 300 K. SPC water taken from a liquid equilibrium configuration (Berendsen et al., 1987) were added to the box. Ten water molecules at the lowest electrostatic potential were replaced by sodium ions to neutralize the simulation cell of Rml/water systems. Details of the molecular dynamics protocol and the effect of the force field on the motions of Rml are presented elsewhere (Peters et al., 1996b
). Examinations of the molecular structures and analyses of the trajectories were carried out using the WHAT IF modeling program (Vriend, 1990
) and the essential dynamics routines supplied therein. Simulations were run for more than 1 ns and 600 ps trajectories were used for the essential dynamics and structural analyses. The essential dynamics method has been described several times in the literature and the reader is referred to Amadei et al. (1993), van Aalten et al. (1995, 1996a) and Peters et al. (1996b). Briefly, the method is based on the diagonalization of the covariance matrix of the atomic displacements (Ichiye and Karplus, 1991
), which yields a set of eigenvectors and eigenvalues. The eigenvectors represent a direction in a high-dimensional space, describing concerted displacements of atoms. The eigenvalues represent the mean square fluctuation of the total displacement along these eigenvectors. Motion within the subspace can be studied by projecting the trajectory onto the individual eigenvectors. This dot product provides information about the time dependence of the conformational changes. The reported eigenvalues are ordered for convenience by decreasing value; i.e. the first eigenvector is the vector with the largest eigenvalue. The central hypothesis of essential dynamics is that only the directions indicated by eigenvectors with sufficiently high eigenvalues are important for the description of the protein dynamics. It has been observed that these motions can be linked to the biological function of proteins (Amadei et al., 1993
; van Aalten et al., 1995
, 1996a
). In many proteins, the positional fluctuations are concentrated in correlated motions in a subspace of only a few degrees of freedom (<10% of the original configurational space), while the other degrees of freedom represent small, independent Gaussian fluctuations.
![]() |
Results and discussion |
---|
![]() ![]() ![]() ![]() ![]() ![]() |
---|
|
In order to obtain detail structural and dynamic properties, we have performed molecular dynamics simulation of the wild-type structure of Rml in water using explicit SPC water molecules. The stability of the simulation was checked by computing several geometrical properties. Root mean square displacement (r.m.s.d.'s) calculated with respect to the initial structure, number of hydrogen bonds and radius of gyration as a function of simulation time are displayed in Figure 1. R.m.s.d. data indicate that extensive equilibration times were necessary (in the order of 200300 ps) before reaching a constant r.m.s.d.
|
|
An important issue in any computational study is the duration of the simulation. To investigate the effect of the duration of the simulation on the results of the essential dynamics (ED) analysis, we have further analyzed the 1.2 ns trajectory of the Rml simulation. The initial 400 ps trajectories were used as equilibration of the systems and were not considered in the analysis. The remaining 800 ps trajectory was divided in two equal parts. Essential dynamics analysis was separately performed on both trajectory parts, and additionally on the first part using different time slices of the trajectory (100, 200, 300 and 400 ps). The average cumulative square inner vector products calculated between the eigenvectors of the time intervals of the first trajectory part and eigenvectors of the second trajectory part are shown in Figure 3. The inner product is normalized so that for two sets of identical eigenvectors the value is 1. As shown in Figure 3a
, the inner vector product slowly converges with the number of eigenvectors. The inner product computed with 100 eigenvectors is approximately 0.65. This is lower than determined for the histidine-containing phosphocarrier protein from Escherichia coli (HPr) (de Groot et al., 1996
). The difference is again probably caused by the more complex motion in lipase. HPr consists of 85 residues, whereas for instance Rml consists of 265 amino acids. As shown in Figure 3b
, the inner vector converges more rapidly with simulation time and after 300 ps only small changes are observed (Figure 3b
). Though slow divergence of the inner product is observed, the total positional fluctuations are similar for different time intervals (see Figure 4
); i.e. the total fluctuations (root mean square deviations) are similar. In Figure 5
, the absolute values of the first three eigenvectors are displayed as a function of residue number. The essential dynamics analysis was performed on trajectories with different length ranging from 100800 ps in steps of 100 ps (picoseconds are given to the right of the curves). One would expect that with increasing simulation time the curves should converge and should show the same features. Overall the fluctuations are similar and constant over distinct time intervals. However, deviations are observed indicating that the protein explores different parts of the configurational space and even an approximately 1 ns trajectory does not cover the full configurational space (Clarage et al., 1995
; Hodel et al., 1995
; Balsera et al., 1996
). Generally, longer simulation times are required for increasing eigenvector indices to obtain convergence of protein motions observed along individual eigenvectors. Fastest convergence of fluctuations is observed along eigenvector 1, where similar motions are found after 200 ps. Relatively large fluctuations are seen for the active site lid and the segments Thr57Asn63, Pro101Gly104, Ala154Phe170, Glu221Leu239 and Ser247Leu255. These regions are shown in Figure 6
, which shows the position of glycine and proline residues (Figure 6a
). As indicated in Figures 5b and c
, motions along eigenvectors 2 and 3 vary with simulation time. However, some of the fluctuations are conserved with simulation time and similar characteristics in the absolute value of the vector as a function of time are observed.
|
|
|
|
To locate mobile regions in the enzyme a moving window superposition method was used (van Aalten et al., 1996b). Root mean square deviations (r.m.s.d.'s) calculated from the minimum and maximum structures of the eigenvector motion as a function of residue number are shown in Figure 7
. There is apparently no direct correlation between the position of the prolines and the flexibility of Rml. Significant r.m.s.d. data are observed close to glycines. Gly81, which also conserved in Rml, Humicola lanuginosalipase, Rhizopus delemar and Penicillium camembertii is located in the hinge-bend region of the active site lid and provides a flexible link for the displacement of the lid (i.e. activation of the lipase). It is noticeable, that the loops Gly35Lys50 and Thr57Asn63 (Rml numbering), which have different flexibility, show low homology between the lipases, and that the glycines (35 and 69 in Rml) are not conserved in the different lipase structures. This may suggest that fluctuations in these loops may govern the biological function of the different lipases.
|
Microbial lipases have attracted considerable attention, due to their capability of catalyzing a wide variety of reactions, which allows their widespread application in industrial areas, such as detergents, food processing, synthesis of oils or enantiomerically pure compounds (Wulfson, 1994). Many lipases show discrete substrate specificity, which is probably governed by distinct interactions between substrate and protein and/or conformational changes (flexibility) in the protein. It is generally recognized (Subbiah, 1996
) that protein motions are dependent on the location of glycines (and maybe prolines) residues in the protein structure. These motions could be central to the biological function of lipases and could determine the activity and selectivity of these enzymes. These fluctuations constitute one of the most clearly defined examples of induced fit in enzymes.
To study the protein dynamics in Rml and to determine fluctuations close to glycine or proline residues, we have performed molecular dynamics simulations in periodic boundary conditions using explicit SPC water. The first 400 ps was discarded for equilibration and the remaining 800 ps trajectory was considered in the analyses. Flexible regions in the protein were determined using the essential dynamics analysis technique combined with the moving window position method. To study the effect of the length of the simulation on the protein motions, we divided the 1.2 ns trajectory in increasing time intervals. The essential dynamics analyses indicate that motions along different eigenvectors converge slowly with simulation time. Motions along eigenvectors with larger indices require longer simulation time to converge than those motions described by eigenvectors with smaller indices. Fluctuations in the active site as well as (for activation important) segments Thr57Asn63 and Pro101Gly104 are observed along several eigenvectors and are conserved along the trajectory. Other fluctuations (e.g. Ala154Phe170, Glu221Leu239 and Ser247Leu255) occur but their extent/frequency vary with simulation time. We conclude that those fluctuations at or in close proximity to the active site can represent an induced fit mechanism. The observed fluctuations are associated with the location of glycines in the protein structure, while no clear correlation is observed between protein dynamics and the presence of proline residues.
![]() |
Acknowledgments |
---|
![]() |
Notes |
---|
![]() |
References |
---|
![]() ![]() ![]() ![]() ![]() ![]() |
---|
Amadei,A., Linssen,A.B.M. and Berendsen,H.J.C. (1993) Proteins Struct. Funct. Genet., 17, 412425.[ISI][Medline]
Balsera,M.A., Wriggers,W., Oono,Y. and Schulten,K. (1996) J. Phys. Chem., 100, 25672572.[ISI]
Berendsen,H.J.C., Grigera,J.R. and Straatsma,T.P. (1987) J. Phys. Chem., 91, 62696271.[ISI]
Berndt,K.D., Beunink,J., Schröder,W. and Wüthrich,K. (1993) Biochemistry, 32, 45644570.[ISI][Medline]
Bernstein,B.E., Michels,P.A. and Hol,W.G. (1997) Nature, 385, 275278.[ISI][Medline]
Bernstein,F.C., Koetzle,T.F., Williams,G.J.B., Meyer, E,F., Brice,M.D., Rogers,J.R., Kennard,O., Shimanouchi,T. and Tasumi,M. (1977) J. Mol. Biol., 112, 535542.[ISI][Medline]
Brady,L. et al. (1990) Nature, 343, 767770.[ISI][Medline]
Brockman,H.L. (1984) In Bergström,B. and Brockman,H.L. (eds), Lipases. Elsevier, Amsterdam, pp. 146.
Brzozowski,A.M., Derewenda,U., Derewenda,Z.S., Dodson,G.G., Lawson, D.M., Turkenburg,J.P., Bjorkling,F., Huge-Jensen,B., Patkar,S.A. and Thim,L. (1991) Nature, 351, 491494.[ISI][Medline]
Busca,R., Martinez,M., Vilella,E., Pognonec,P., Deeb,S., Auwerx,J., Reina,M. and Vilaro,S. (1996) J. Biol. Chem., 271, 21392146.
Clarage,J.B., Romo,T., Andrews,B.K., Pettitt,B.M. and Phillips,G.N.,Jr (1995) Proc. Natl Acad. Sci. USA, 92, 32883292.[Abstract]
Cygler,M., Schrag,J.D., Sussman,J.L., Harel,M., Silman,I., Gentry,M.K. and Doctor,B.P. (1993) Protein Sci., 2, 366382.
De Benedetti,P.G., Fanelli,F., Menziani,M.C., Cocchi,M., Testa,R. and Leonardi,A. (1997) Bioorg. Med. Chem., 5, 809816.[ISI][Medline]
De Groot,B.L., Amadei,A., Scheek,R.M., van Nuland,N.A.J. and Berendsen, H.J.C. (1996) Proteins Struct. Funct. Genet., 26, 314322.[ISI][Medline]
Derewenda,Z.S., Derewenda,U. and Dodson,G.G. (1992a) J. Mol. Biol., 227, 818839.[ISI][Medline]
Derewenda,U., Brzozowski,A.M., Lawson,D.M. and Derewenda,Z.S. (1992b) Biochemistry, 31, 15321541.[ISI][Medline]
Derewenda,U., Swenson,L., Green,R., Wei,Y., Dodson,G.G., Yamaguchi,S., Haas,M.J. and Derewenda,Z.S. (1994a) Nature Struct. Biol., 1, 3647.[ISI][Medline]
Derewenda,U., Swenson,L., Wei,Y., Green,R., Kobos,P.M., Joerger,R., Haas,M.J. and Derewenda,Z.S. (1994b) J. Lipid Res., 35, 524534.[Abstract]
Derewenda,Z.S. (1994c) Adv. Protein Chem., 45, 152.[ISI][Medline]
Derewenda,Z.S. (1995) Nature Struct. Biol., 2, 347349.[ISI][Medline]
Dodson,G.G., Lawson,D.M. and Winkler,F.K. (1992) Faraday Disc., 93, 95105.[ISI][Medline]
Europort-D. (1997) Parallel version of GROMOS87 was developed by the Parallel Applications Centre, Southampton, UK and installed on the 18 processor SGI Challenge at Novo Nordisk A/S.
Filipowsky,M.E., Kopka,M.L., Brazil-Zison,M., Lown,J.W. and Dickerson, R.E. (1996) Biochemistry, 35, 1539715410.[ISI][Medline]
Grochulski,P.,L. Yunge,J.D. Schrag,F. Bouthillier,P. Smith,D. Harrison,B. Rubin, and Cygler,M. (1993) J. Biol. Chem., 268, 1284312847.
Hardy,F., Vriend,G., Veltman,O.R., van der Vinne,B., Venema,G. and Eijsink,V.G.H. (1993) FEBS Lett., 317, 8992.[ISI][Medline]
Hartsough,D.S. and Merz,M.,Jr (1993) J. Am. Chem. Soc., 115, 65296537.[ISI]
Hodel,A., Rice,L.M., Simonson,T., Fox,R.O. and Brünger,A.T. (1995) Protein Sci., 4, 636654.
Hjort,A. et al. (1993) Biochemistry, 32, 47024707.[ISI][Medline]
Hecht,M.H., Sturtevant,J.M. and Sauer,R.T. (1986) Proteins Struct. Funct. Genet., 1, 4346.[Medline]
Henderson,H.E., Hassan,F., Berger,G.B.M. and Hayden,R. (1992) J. Med. Gen., 29, 119122.[Abstract]
Holmquist,M., Martinelle,M., Berglund,P., Clausen,I.G., Patkar,S., Svendsen,A. and Hult,K. (1993) J. Protein Chem., 12, 749757.[ISI][Medline]
Ichiye,T. and Karplus,M. (1991) Proteins Struct. Funct. Genet., 11, 205217.[ISI][Medline]
Jancso,A. and Szent-Györgyi,A.G. (1994) Proc. Natl Acad. Sci. USA, 91, 87628766.[Abstract]
Kern,P., Brunne,R.M. and Folkers,G. (1994) J. Comp. Aided Mol. Des., 8, 367388.[ISI]
Koshland,D.E.,Jr (1958) Proc. Natl Acad. Sci. USA, 44, 98104.[ISI]
Kraut,J. (1977) Annu. Rev. Biochem., 46, 331384.[ISI][Medline]
Lawson,D.M., Brzozowski,A.M., Dodson,G.G., Hubbard,R.E., Huge-Jensen,B., Boel,E. and Derewenda,Z.S. (1994) In Woolley,P. and Petersen,S.B. (eds), LipasesTheir Structure, Biochemistry and Applications. Cambridge University Press, Cambridge, pp. 7794.
Mann,D.M.A., Jones,D., Snowden,J.S., Neary,D. and Hardy,J. (1992) Neurosci. Lett., 137, 225228.[ISI][Medline]
Martin,J.R., Mulder,F.A., Karimi-Nejad,Y., van der Zwan,J., Mariani,M., Schipper,D. and Boelens,R. (1997) Structure, 5, 521532.[ISI][Medline]
Martinez,C., De Geus,P., Lauwereys,M., Matthyssens,G. and Cambillau,C. (1992) Nature, 356, 615618.[ISI][Medline]
Masul,A., Fujiwara,N. and Imanaka,T. (1994) Appl. Environ. Microbiol., 60, 35793584.[Abstract]
Matthews,B.W. (1987) Biochemistry, 26, 68856888.[ISI][Medline]
Miyazaki,S., Shimura,J., Hirose,S., Sanokawa,R., Tsurui,H., Wakiya,M., Sugawara,H. and Shirai,T. (1997) Int. Immunol., 9, 771777.[Abstract]
Muderhwa,J.M. and Brockman,H.L. (1992) Biochemistry, 31, 149155.[ISI][Medline]
Narayana,N., Cox,S., Nguyen-huu,X., Ten Eyck,L.F. and Taylor,S.S. (1997) Structure, 5, 921935.[ISI][Medline]
Noble,M.E.M., Cleasby,A., Johnson,L.N., Egmond,M.R. and Frenken,L.G.J. (1993) FEBS Lett., 331, 123128.[ISI][Medline]
Olah,G.A., Mitchell,R.D., Sosnick,T.R., WalshD.A. and Trewhella,J. (1993) Biochemistry, 32, 36493657.[ISI][Medline]
Ollis,D.L. et al. (1992) Protein Engng, 5, 197211.[Abstract]
Olson,M.A. (1997) Proteins, 27, 8095.[ISI][Medline]
Peters,G.H., Olsen,O.H., Svendsen,A. and Wade,R. (1996a) Biophys. J., 71, 119126.[Abstract]
Peters,G.H., van Aalten,D.M.F., Edholm,O., Toxvaerd,S. and Bywater,R. (1996b) Biophys. J., 71, 22452251.[Abstract]
Peters,G.H., Toxvaerd,S., Olsen,O. and Svendsen,A. (1997) Protein Engng, 10, 137145.[Abstract]
Piéroni,G., Gargouri,Y., Sarda,L. and Verger,R. (1990) Questions Adv. Coll. Int. Sci., 32, 341378.
Ptaszek,L.M., Vijayakumar,S. Ravishanker,G. and Beveridge,D.L. (1994) Biopolymers, 34, 1451153.
Ribas de Pouplana,L., Auld,D.S., Kim,S. and Schimmel,P. (1996) Biochemistry, 35, 80958102.[ISI][Medline]
Schrag,J.D. and Cygler,M. (1993) J. Mol. Biol., 230, 575591.[ISI][Medline]
Subbiah,S. (1996) Protein Motions. Molecular Biology Intelligence Unit, Springer-Verlag, Heidelberg, Germany.
Teplyakov,A., Sebastiao,P., Obmolova,G., Perrakis,A., Brush.G.S., Bessman, M.J. and Wilson,K.S. (1996) EMBO J., 15, 34873497.[Abstract]
Uppenberg,J., Hansen,M.T., Patkar,S. and Jones,T.A. (1994) Structure, 2, 293308.[ISI][Medline]
Van Aalten,D.M.F., Amadei,A., Linssen,A.B.M., Eijsink,V.G.H. and Vriend,G. (1995) Proteins Struct. Funct. Genet., 22, 4554.[ISI][Medline]
Van Aalten,D.M.F., Amadei,A., Bywater,R., Findlay,J.B.C., Berendsen,H.J.C., Sander,C. and Stouten,P.F.W. (1996a) Biophys. J., 70, 684692.[Abstract]
Van Aalten,D.M.F., Findlay,J.B.C., Amadei,A. and Berendsen,H.J.C. (1996b) Protein Engng, 8, 11291135.[Abstract]
Van Aalten,D.M.F., Jones,P.C., de Sousa,M. and Findlay,J.B.C. (1997) Protein Engng, 10, 3137.[Abstract]
Van Gunsteren,W.F. and Berendsen,H.J.C. (1987) GROMOS: Groningen Molecular Simulation Computer Program Package. University of Groningen, The Netherlands.
Van Tilbeurgh,H., Egloff,M.P., Martinez,C., Rugani,N., Verger,R. and Cambillau,C. (1993) Nature, 362, 814820.[ISI][Medline]
Verger,R., Pattus,F., Piéroni,G., Riviere,C., Ferrrato,F., Leonardi,G. and Dargent,B. (1984) Colloid. Surf., 10, 163180.[ISI]
Vermersch,P.S., Tesmer,J.G.G., Lemon,D.D. and Quiocho,F.A. (1990) J. Biol. Chem., 265, 1659216603.
Von der Osten,C., Hedegaard,L., Østergaard,P., Lauridsen,C., Kierstein,L. and Branner,S. (1993) In Van der Tweel,W.J.J., Harder,A. and Buitelaar,R.M. (eds), Stability and Stabilization of Enzymes. Elsevier, New York, pp. 133144.
Vriend,G. (1990) J. Mol. Graph., 8, 5256.[ISI][Medline]
Vulliamy,T.J., D'Urso,M., Battistuzzi,G., Estrada,M., Foulkes,N.S., Martini,G., Calabro,V., Poggi,V., Giordana,R., Town,M., Luzzatto,L. and Persico,M.G. (1988) Proc. Natl Acad. Sci. USA, 85, 51715175.[Abstract]
Wilkinson,A.J., Fersht,A.R., Blow,D.M. and Winter,G. (1983) Biochemistry, 22, 35813586.[ISI][Medline]
Winkler,F.K., D'Arcy,A. and Hunziker,W. (1990) Nature, 343, 771774.[ISI][Medline]
Wulfson,E.N. (1994) In Woolley,P. and Petersen,S.B. (eds), LipasesTheir Structure, Biochemistry and Applications. Cambridge University Press, Cambridge, pp. 271288.
Yutani,K., Hayashi,S., Sugisaki,Y. and Ogasahara,K. (1991) Proteins Struct. Funct. Genet., 9, 9098.[ISI][Medline]
Yutani,K., OgasaharaK., Kimura,A. and Sugino,Y. (1982) J. Mol. Biol., 160, 387390.[ISI][Medline]
Zheng,J., Knighton,D.R., Xuong,N.H., Taylor,S.S., Sowadski,J.M. and Ten Eyck,L.F. (1993) Protein Sci., 2, 15591573.
Received January 12, 1999; revised June 4, 1999; accepted June 11, 1999.