1Department of Biology and Biochemistry, University of Houston, Houston, TX 77204-5001, USA 2Present address: Emisphere Technologies, Inc., Tarrytown, NY 10591, USA
3 To whom correspondence should be addressed. e-mail: jbriggs{at}uh.edu
![]() |
Abstract |
---|
![]() ![]() ![]() ![]() ![]() ![]() |
---|
Keywords: alanine racemase/cluster analysis/molecular dynamics
![]() |
Introduction |
---|
![]() ![]() ![]() ![]() ![]() ![]() |
---|
A number of effective inhibitors of AlaR have been developed and some of them are of particular interest as agents against Mycobacterium tuberculosis. However, most of these compounds are suicide inhibitors that react with the cofactor itself, inhibiting the activity of many PLP-containing enzymes owing to their lack of target specificity. D-Cycloserine (DCS) is the only inhibitor that has been marketed clinically and is mainly used as a second-line anti-tuberculosis agent. Although it is an excellent inhibitor of tuberculosis growth, and also other pathogenic bacterial species, side-effects, especially toxicity and neurological disorders, have limited its clinical use (Helmy, 1970).
Seven crystallographic structures of AlaR from Bacillus stearothermophilus have been reported so far, including the complexes between AlaR and three inhibitors, namely propionate, 1-aminoethylphosphonic acid (Shaw et al., 1997; Stamper et al., 1998
; Morollo et al., 1999
; Watanabe et al., 2002
; Stamper and Ringe, 2003
) and recently, a DCS derivative (Fenn et al., 2003
). The crystal structure revealed that the enzyme is a homodimer of 388 residues per monomer. Each monomer is composed of two folded domains, an N-terminal domain from residues 1240 and a C-terminal domain from residues 241388. The N-terminal domain is made up of an eight-stranded
/ß-barrel and the C-terminal domain mainly of ß-strands. The active form of alanine racemase is a homodimer, such that the active site is formed by the mouth of the
/ß-barrel of one monomer and the C-terminal domain of the other monomer. The active site of AlaR is composed of PLP, which is cross-linked to Lys39 via a protonated Schiff base linkage and the amino acids in the immediate environment of the PLP.
In all of the AlaR crystal structures, an important number of water molecules have been identified. Several studies have been dedicated to the analysis of conserved water positions in different biological systems, whether they were devoted to different crystal structures of the same protein, such as the serine protease family (Rashin et al., 1986; Williams et al., 1994
) or to related proteins, such as the microbial RNases (Sreenivasan and Axelsen, 1992
; Zhang and Matthews, 1994
; Sanschagrin and Kuhn, 1998
; Ogata and Wodak, 2002
). All of these studies demonstrated that water plays a pivotal role in most biological systems, by facilitating reactions, stabilizing three-dimensional structures or mediating interactions between proteins and ligands.
A typical method for analyzing the contributions of bound solvent in a number of closely related structures is to use molecular graphics to visualize the conserved water sites and their proximity to catalytic or ligand-binding residues. Sanschagrin and Kuhn (1998) were the pioneers of using a statistical method (i.e. complete linkage clustering) to define consensus water sites in thrombin, trypsin and bovine pancreatic trypsin inhibitor (BPTI), with the goal of determining shared water sites, as well as those contributing to specificity. Ogata and Wodak (2002
) employed a similar approach to analyze the conserved water positions in a sample of 12 high-resolution MHC class I molecules, providing a list of water sites that may play an important structural and functional role. Regardless of the statistical method used, cluster analysis has proven to be a useful tool for facilitating the analysis of water sites from multiple structures and distinguishing between conserved features within a protein family and those conferring specificity.
In the present study, we analyzed structural aspects of the conserved water molecules in B.stearothermophilus alanine racemase. We employed a statistical method, which is somewhat different from the other two examples previously mentioned, with the goal of determining the extent to which water sites are conserved and to understand their putative structural role.
These structures provide an interesting scaffold to evaluate the consistency of solvent binding as determined crystallographically and its structural and functional role in B.stearothermophilus alanine racemase.
![]() |
Materials and methods |
---|
![]() ![]() ![]() ![]() ![]() ![]() |
---|
The quality of water refinement was estimated by using a mobility measure (Sanschagrin et al., 1998), designed to normalize and combine the crystallographic temperature factor (B-value) and the occupancy. In this way, we were able to compare the atomic mobility between protein structures that were solved using different refinement protocols, in particular, those structures in which B-values were allowed to vary during refinement.
where B-valueHOH represents the B-value for each individual water molecule,
denotes the average B-value for all waters in the structure, OccupancyHOH represents the occupancy for each water molecule and
is the average occupancy of all waters in the structure.
Using this normalization, if the mobility of a water molecule, determined from its oxygen atom, has a value close to 0, this means that this water molecule displays a low degree of mobility. If the mobility value equals 1, this signifies that this water molecule has an average mobility relative to other atoms in the structure.
Clustering procedure
Seven available B.stearothermophilus AlaR crystal structures were superimposed using main-chain least-squares superposition in InsightII (Accelrys, 1997) to transform the water coordinates into the same reference frame.
The FASTCLUS procedure from the SAS Statistical Package (SAS Institute, Cary, NC) was used to cluster the water molecules from all seven crystal structures. This clustering procedure (a partitional clustering method) finds disjoint clusters of observations using the K-means method applied to coordinate data (in our case each water molecule is characterized by the Cartesian coordinates). The result of a partitional clustering method generally consists of a set of clusters, each object belonging to one cluster. Each cluster is represented by a centroid or a cluster representative that contains a summary description of all the objects contained in a cluster.
The criterion function is the average squared distance of the data items xk from their nearest cluster centroids,
where c(xk) is the index of the centroid that is closest to xk. Minimizing the cost function begins by initializing a set of k cluster centroids denoted by mi, i = 1, ..., k. The positions of the mi are then adjusted iteratively by first assigning the data samples to the nearest clusters and then recomputing the centroids. The iteration is stopped when E no longer undergoes significant changes.
The main advantages of this method are its simplicity and rapidity; however, detailed information is provided: cluster summary [frequency, root mean square deviation (r.m.s.d.), nearest cluster, distance between cluster centroids, cluster mean coordinates, etc.].
A maximum diameter of 3.0 Å was chosen, resulting in clusters with a maximum inter-water distance of 3.0 Å. This value was chosen because water molecules have an approximate effective radius of 1.6 Å, which includes the radius of the oxygen atom and a correction for the contribution of the hydrogen atoms, whose positions were not determined by X-ray crystallography. Thus, if two water molecules are placed with their oxygen atoms at a center-to-center distance of 3.0 Å, their radii will overlap by 12.5%. A value of 1.5 Å for defining the maximum cluster radius ensures that clusters do not contain several water molecules belonging to the same crystal structure, which may be within hydrogen bonding distance of one another.
Identification of buried water molecules
Buried water molecules in proteins are those that are structurally isolated from the bulk solvent. These buried waters are not easily detected by X-ray crystallography since, for the water to have a clear diffraction pattern, it must be in the same position all the time.
In our study, the PRO_ACT program (Williams et al., 1994) was used for the identification of buried water molecules. The program fills up the solvent-accessible surface of a protein with experimental and computational water molecules and then identifies those experimental waters that are not connected to bulk water by a chain of hydrogen bonds.
Hydrogen bonds
Hydrogen bonds were identified using the HBPLUS program (McDonald and Thornton, 1994) with the following criteria: a donoracceptor distance must be
3.5 Å, the donorhydrogenacceptor and the hydrogenacceptorfrom angles must be
90° (from stands for the atom covalently linked to the acceptor atom).
Molecular dynamics simulations
A 2 ns molecular dynamics simulation for the B.stearothermophilus alanine racemase homodimer has recently been reported (Mustata et al., 2003). Therefore, only a brief description is given here for completeness.
The protein structure used for the MD studies corresponds to B.stearothermophilus alanine racemase (PDB code: 1SFT) (Shaw et al., 1997), containing acetate in each active site, from which we built a model with D-Ala in one active site and propionate in the second. Propionate was modeled into the first active site by superimposing the B.stearothermophilus AlaR crystal structure in complex with the inhibitor propionate (PDB code: 2SFP) (Morollo et al., 1999
) onto the first reported alanine racemase X-ray structure (PDB code: 1SFT) (Shaw et al., 1997
). The two structures are similar to each other, with a mean C
r.m.s.d. of 0.29 Å. The substrate D-Ala was modeled in the second active site making use of the R-AlaR-1-aminoethylphosphonic acid (L-Ala-P) complex structure (PDB code: 1BD0) (Stamper et al., 1998
), which was superimposed on the same reference structure (PDB code: 1SFT) (Shaw et al., 1997
). The reason for using this structure in the modeling of D-Ala in the active site was because this was the first available X-ray structure to give a detailed description of the important interactions for binding and positioning of the substrate.
The system was prepared and energy minimized using the CHARMM program (Brooks et al., 1983). The thermalization, equilibration and the subsequent production phases were carried out using the NAMD program (Kalé et al., 1999
), in the NPT ensemble (pressure = 1 bar) with explicit solvent and periodic boundary conditions and a dielectric constant (
) of 1. A constant temperature of 300 K was maintained by coupling to an external bath (Berendsen et al., 1984
). The protein and solvent interact via the CHARMM22 force field where all protein atoms are explicitly represented (MacKerell et al., 1998
) and where water is characterized by the TIP3P model (Jorgensen et al., 1983
). The hydrogen atoms were added using the HBUILD routine in CHARMM. Long-range interactions were smoothly truncated at 10.5 Å with a shifting function for the electrostatic interaction and a switching function for the van der Waals interactions, the latter being applied between 9.5 and 10.5 Å. The non-bonded pairs list was updated every 10 steps. The truncation scheme applied to the calculation of electrostatic interactions was selected in order to reduce the computational effort and limit the perturbation induced by artificial periodicity imposed to the solution under periodic boundary conditions (Wood, 1995
). The observation that the conformations sampled in the protein trajectory depart little from the crystal structure supports the validity of our truncation scheme. However, recent studies have suggested that the Ewald summation method is a better protocol, at least for nucleic acids (Sagui and Darden, 1999
). It has nevertheless also been shown to present a number of artifacts (Hunenberger and McCammon, 1999
), in particular when solute cavities are large compared with the unit cell, a feature characterizing our system. Before the MD run was performed, the system was energy minimized by 500 steps of steepest descent (SD) keeping the solute fixed. The solvent plus the substrate and the inhibitor were then relaxed and also subjected to 500 steps of SD energy minimization. Then the whole system was relaxed and minimized using SD for another 1000 steps. The entire system was then gradually heated, by means of temperature reassignment, from 50 to 300 K for 60 ps of MD. The whole system was then equilibrated for an additional 360 ps of molecular dynamics at 300 K using a 2 fs time step, after which the system achieved stability. The subsequent production phase was performed in the NPT ensemble for 2 ns with a time step of 2 fs. Atomic coordinates were stored for later analysis every 0.5 ps.
![]() |
Results and discussion |
---|
![]() ![]() ![]() ![]() ![]() ![]() |
---|
|
To identify consensus water sites in B.stearothermophilus alanine racemase, we performed a partitional clustering analysis of the waters sites. Our cluster analysis identified a total number of 163 clusters from which 47 clusters exhibit conserved water positions in all seven available crystal structures of AlaR (Shaw et al., 1997; Stamper et al., 1998
; Morollo et al., 1999
; Watanabe et al., 2002
; Fenn et al., 2003
; Stamper and Ringe, 2003
) (Tables II and III). Figure 1 shows the distribution of the conserved solvent sites superimposed on the AlaR reference structure (PDB code: 1SFT). Each cluster is represented by a sphere and the size of the sphere is proportional to the number of AlaR structures in which solvent was observed at the same site. In addition, the color of each sphere reflects the conservation ratio in the analyzed crystal structures (e.g. the red spheres indicate that the water molecules are conserved in all analyzed crystal structures and are denominated here as highly conserved water sites).
|
|
|
Figure 2 compares the mobility distributions of water sites in the seven crystal structures. As can be seen, the majority of the clusters contain water molecules with mobilities between 0.4 and 1, indicating to some extent an average mobility relative to other waters in the structure. As observed previously by Levitt and Sharon (1988), clusters containing waters with low mobility tend to be located near charged residues (e.g. Water 714 in cluster 35 has a mobility of
0.4 in 1SFT and it is near Asp68, Glu69 and Asp47'). On the contrary, clusters containing waters with high mobility tend to be situated near hydrophobic residues (e.g. Water 586 in cluster 28 has a mobility of
1.4 in 1SFT and it is located near Ile310, Gly308 and Met312).
|
Dimer interface
We investigated the relative arrangement of the highly conserved water sites in the AlaR homodimer and observed that 64% of these water sites (30 out of 47) are clustered at the interface between the N-terminal domain (/ß-barrel) of the first monomer and the C-terminal domain (essentially composed of ß strands) of the second monomer (Figure 3). As Figure 3 indicates, there are two major accumulations of water sites, one of which is close to the active site of the first monomer (displayed in gray in Figure 3) and a second one positioned at the interface between the two monomers, which forms a canal to the active site.
|
The interface is mainly hydrophilic with 80% of the interface residues polar and only 20% hydrophobic. Shaw et al. (1997) have shown that there are very few obvious polar interactions between the two monomers (i.e. few salt bridges and direct hydrogen bonds that bridge the two monomers) and suggested that these types of interactions do not appear to be responsible for maintaining the dimer structure (Shaw et al., 1997
). However, Figure 4 illustrates the remarkable degree to which the dimerization surfaces are electrostatically complementary. We can see that when the homodimer is pulled apart and the electrostatic potential is mapped on to the molecular surface of the dimer interface, for every positively charged area, a matching area of negative electrostatic charge exists in the dimer interface. This type of electrostatic complementarity at the dimer interface is not aleatory but rather consistent with the expected properties of a dimer interface (Miller, 1989
; Jones and Thornton, 1995
; Miller and Krause, 1996
).
|
|
Consensus hydration sites and interactions at the dimer interface from MD simulation
Our procedure of identifying conserved hydration sites makes use of static pictures provided by structures solved by X-ray crystallographic methods. Although individual structures give the same location for 47 water sites in all seven analyzed structures, their importance can be confirmed only after verifying that these hydration sites remain invariant in a fully solvated environment of an MD simulation. In order to address this, structures were extracted from a previously described 2 ns MD trajectory (Mustata et al., 2003).
In order to determine if we had sampled enough of the conformational space, we compared the 2 ns trajectory with a 1 ns trajectory. By comparison, we saw that both MD simulations lead to perfectly comparable results. As a measure of structural stability, the r.m.s.ds of backbone atoms of individual conformations of alanine racemase were computed along the 1 ns and 2 ns trajectories. This r.m.s.d., measured relative to the minimized crystal structure conformation has a value of about 0.8 Å at the beginning of the 1 ns trajectory versus 0.75 Å for the 2 ns trajectory, indicating that movements away from the crystal structure have occurred during the thermalization and equilibration periods that preceded the production run. Thereafter, only a small overall drift was observed, with fluctuation of the order of 0.6 Å during the 1 ns trajectory and 0.35 Å during the 2 ns trajectory, indicating a stable protein structure. The backbone r.m.s.d. of the average protein conformation with respect to the minimized crystal structure computed from the entire 1 ns trajectory is 1.25 Å versus 1.20 Å from the 2 ns trajectory. The r.m.s.d. of all the atoms (including aliphatic hydrogens) is 1.55 Å for the 1 ns trajectory and 1.35 Å for the 2 ns trajectory. Overall, if we compare the r.m.s.ds of the atoms computed along the 1 ns trajectory with those of the 2 ns trajectory, we can see that there are no significant changes in terms of structural stability.
The root mean square fluctuations (r.m.s.fs) per residue are almost identical and essential dynamics analyses have shown that the motions along each of the most significant eigenvectors are also similar. Within the time-scale of the simulations, we also saw that the protein did not undergo significant unfolding processes, as evidenced by stable radius of gyration and by the secondary structure content calculated along the 2 ns and 1 ns trajectories. We believe that if major changes, in terms of protein or homodimer interface stability, had occurred, we would have seen it within the first 1 ns of the simulation.
Within the 2 ns time-scale of the simulation, we have shown that the second active site (D-Ala in the active site) becomes more stabilized in the presence of the substrate versus inhibitor. Our results have shown that fluctuations in the region of the active sites were of differing magnitude, being larger in the presence of inhibitor, and that fluctuations in the /ß-barrel are more substantial upon inhibitor binding with the
-helix H8 and the loop between
-helix H8 and ß-strand B8 showing extensive flexibility (Mustata et al., 2003
). In contrast, upon substrate binding very little displacement was exhibited by the N-terminal domain. Significant flexibility was observed in the C-terminal domain of the second monomer (substrate bound) and very little in the first monomer (inhibitor bound). This flexibility was also induced by inhibitor binding since this C-terminal domain faces the mouth of the
/ß-barrel of the first monomer (with propionate in the active site) (Mustata et al., 2003
). From Table V we can see that the r.m.s.fs of the C
atoms of the interface residues display similar values, except for the active site residues (i.e. Arg136, His166, Tyr265') and the residues located in their proximity.
|
Our analysis on the conserved water molecules located at the dimer interface and in the active site region was performed on snapshots extracted every 20 ps from the 2 ns long trajectory (i.e. 101 snapshots). The choice of the time interval is based on the mobility of the bulk water of the simulation, which will diffuse about 3.0 Å in 20 ps of simulation. Only waters that are within 3.5 Å from the interface were retained, to ensure that these waters are within hydrogen bonding distance of any dimer interface atom. All of the 101 snapshots extracted from the MD trajectory were superimposed on the 1SFT X-ray structure (Shaw et al., 1997) in order to bring all structures into the same reference frame. The same FASTCLUS procedure (SAS Institute) as described in Materials and methods was used to cluster the water molecules.
From Table VI it can be seen that all salt bridges between the two monomers are well preserved during the simulation with only one exception, that is, the salt bridge between Arg290 (monomer 1) and Glu355 (monomer 2) which is present only in 2% of the 2 ns simulation time. This is mainly caused by the presence of the inhibitor propionate in the active site of the first monomer. The hydrogen bonds between residues from both monomers located at the dimer interface are generally well preserved. However, seven hydrogen-bonding interactions are not retained for the entire length of the simulation. The residues involved in these interactions belong to the propionate-bound active site and this clearly demonstrates that upon inhibitor binding the interface between the two monomers is disrupted.
|
The structurally determined crystal waters that are not in the immediate proximity of the propionate-bound active site show a relatively high mobility (55% mobility) during the MD simulation and exchange with bulk solvent (Table VI). This is not surprising, since water molecules which are mobile in the MD simulation could sample other local interactions. In contrast, waters that are located in the center of the dimer interface and closer to the substrate-bound active site are much less mobile, as indicated by the hydrogen bond presence (7080% and even 100%) for the entire length of the trajectory. This was also observed for conserved water molecules that are close to the substrate-bound active site but not located at the dimer interface (1020% mobility) (data not shown), which is a result of the fact that the active site becomes more stabilized in the presence of the substrate, D-Ala, versus the non-covalent inhibitor propionate.
Experimental studies have been devoted to the elucidation of the catalytic mechanism of AlaR and revealed that the enzyme employs a two-base mechanism in which Lys39 and Tyr265' are the acidbase catalysts. Watanabe et al. (2002) proposed proton transfer between Tyr265' and Lys39 as a principal component of a mechanism in which a protonated
-carboxyl is employed. Recently, Spies and Toney (2003
) have suggested that this mechanism is improbable, since the substrate carboxylate is stabilized by hydrogen bonds from the side-chain guanidine group of Arg136 and from the main-chain amide of Met312' (Morollo et al., 1999
). Based on their multiple kinetic isotope effect methodology applied to alanine racemase, they propose that the dynamic water molecules and hydrogen-bonding interactions in the active site are responsible for the rapid equilibration of active site protons with the solvent, based on their pKa values (Spies and Toney, 2003
).
As we have shown, eight water sites located in the active site regions of the AlaR homodimer were found to be conserved in all seven X-ray structures (see Figure 5 and Table II; the active site waters are displayed in italic bold in Table II). These hydration sites were monitored for the entire length of the simulation to determine if they are continually present in the active site region. The buried water molecule of the propionate-bound active site (cluster 46 in Table II) showed a very low mobility. This was also the case for the water site that belongs to the substrate-bound active site (cluster 13 in Table II). All of the six other water sites located in the propionate-bound active site were occupied by solvent for the entire length of the 2 ns trajectory, with the crystallographic waters occasionally replaced by bulk solvent. Interestingly, two water molecules of the propionate-bound active site were replaced, after 700 ps of the simulation, by waters that were initially located at the dimer interface. We should point out that the diffusion of waters positioned at the dimer interface is not limited to only these two water molecules but, since these water molecules were the only ones found to be highly conserved in all seven X-ray structures, we refer exclusively to these two. In this way our analysis is not biased by the presence of an inhibitor/substrate in the active site.
|
Conclusion
The present study involved an analysis of conserved water sites in seven crystal structures of alanine racemase from B.stearothermophilus in the resolution range 1.62.2 Å. A total of 163 clusters have been identified, of which 47 exhibit conserved water positions in all seven available crystal structures. Two major accumulations of water sites were identified, one of which is located in the active site region of the first monomer and a second one positioned at the interface between the two monomers, which forms a canal to the active site of one of the two monomers.
The MD analysis revealed that the hydrogen bond interactions at the dimer interface are disrupted by the presence of the inhibitor propionate. Considering the fact that a weak inhibitor such as propionate (Ki = 20 ± 3 mM) (Morollo et al., 1999) has an influence on disturbing the hydrogen bond network that exists at the AlaR dimer interface, one would obviously expect that a stronger inhibitor (e.g. the DCS derivative) (Stamper and Ringe, 2003a
) may have a more dramatic effect. Further MD studies with the DCS derivative should help to confirm these hypotheses.
We suggest that one of the possible structural roles that the water sites identified at the interface between the two monomers might have is to maintain and stabilize the alanine racemase dimer. These water molecules can stabilize the interface between the two monomers through hydrogen bonding but, owing to the mobility of these water molecules, this stabilization is not immobile but rather driven by fluctuations of the interface residues. A second role that could be attributed to the interface water sites might be to supply the active site continuously with water molecules in order to allow the rapid equilibration of active site protons with the solvent. These are plausible hypotheses that could be further investigated by experimental methods. One of these methods could be used to explore the role of the water molecules by site-directed mutagenesis and the osmotic stress technique. The purpose of site-directed mutagenesis will be to disrupt the water-mediated hydrogen bond network that links the two alanine racemase monomers. Small-angle neutron scattering coupled with the osmotic stress technique could be used to probe the connection between structural change and thermodynamics of the enzyme under osmotic stress (Parsegian et al., 2000). It is well known that the action of many proteins couples the binding of ligand to conformational changes in the protein that change the number of water molecules sequestered in pockets, cavities or channels. The neutron scattering measurements will provide information about structural changes that can be thereafter used to extract energy changes through osmotic stress thermodynamics.
![]() |
Acknowledgements |
---|
|
|
|
|
![]() |
References |
---|
![]() ![]() ![]() ![]() ![]() ![]() |
---|
Adams,E. (1976) Adv. Enzymol. Relat. Areas Mol. Biol., 44, 69138.[ISI][Medline]
Berendsen,H.J.C., Postma,J.P.M., van Gunsteren,W.F., DiNola,A. and Haak,J.R. (1984) J. Chem. Phys., 81, 36843690.[CrossRef][ISI]
Brooks,B.R., Bruccoleri,R.E., Olafson,B.D., States,D.J., Swaminathan,S. and Karplus,M. (1983) J. Comput. Chem., 4, 187217.[ISI]
Fenn,T.D., Stamper,G.F., Morollo,A.A. and Ringe,D. (2003) Biochemistry, 42, 57755783.[CrossRef][ISI][Medline]
Helmy,B. (1970) Scand. J. Respir. Dis., Suppl., 71, 220225.[Medline]
Honig,B. and Nicholls,A. (1995) Science, 268, 11441149.[ISI][Medline]
Hunenberger,P.H. and McCammon,J.A. (1999) Biophys. Chem., 78, 12, 6988.[CrossRef][ISI][Medline]
Janin,J. and Chothia,C. (1990) J. Biol. Chem., 265, 1602716030.
Jones,S. and Thornton,J.M. (1995) Prog. Biophys. Mol. Biol., 63, 3165.[CrossRef][ISI][Medline]
Jorgensen,W.L., Chandresekhar,J., Madura,J., Impey,R. and Klein,M. (1983) J. Chem. Phys., 79, 926935.[CrossRef][ISI]
Kalé,L., Skeel,R., Bhandarkar,M., Brunner,R., Gursoy,A., Krawetz,N., Phillips,J., Shinozaki,A., Varadarajan,K. and Schulten,K. (1999) J. Comput. Phys., 151, 283312.[CrossRef][ISI]
Levitt,M. and Sharon,R. (1988) Proc. Natl Acad. Sci. USA, 85, 75577561.[Abstract]
MacKerell,A.D. et al. (1998) J. Phys. Chem., 102, 35863616.[ISI]
Mahoney,M.W. and Jorgensen,W.L. (2000) J. Chem. Phys., 112, 8910.[CrossRef][ISI]
Mahoney,M.W. and Jorgensen,W.L. (2001) J. Chem. Phys., 114, 363366.[CrossRef][ISI]
Makarov,V.A., Andrews,B.K. and Pettitt,B.M. (1998) Biopolymers, 45, 469478.[CrossRef][ISI][Medline]
McDonald,I.K. and Thornton,J.M. (1994) J. Mol. Biol., 238, 777793.[CrossRef][ISI][Medline]
Miller,M.D. and Krause,K.L. (1996) Protein Sci., 5, 2433.
Miller,S. (1989) Protein Eng., 3, 7783.[ISI][Medline]
Morollo,A.A., Petsko,G.A. and Ringe,D. (1999) Biochemistry, 38, 32933301.[CrossRef][ISI][Medline]
Mustata,G.I., Soares,T.A. and Briggs,J.M. (2003) Biopolymers, 70, 186200.[CrossRef][ISI][Medline]
Neuhaus,F.C. (1967) Antimicrob. Agents Chemother., 7, 304313.
Nicholls,A., Sharp,K.A. and Honig,B. (1991) Proteins, 11, 281296.[ISI][Medline]
Ogata,K. and Wodak,S.J. (2002) Protein Eng., 15, 697705.[CrossRef][ISI][Medline]
Parsegian,V.A., Rand,R.P. and Rau,D.C. (2000) Proc. Natl Acad. Sci. USA, 97, 39873992.
Phillips,G.N.,Jr and Pettitt,B.M. (1995) Protein Sci., 4, 149158.
Rashin,A.A., Iofin,M. and Honig,B. (1986) Biochemistry, 25, 36193625.[ISI][Medline]
Sagui,C. and Darden,T.A. (1999) Annu. Rev. Biophys. Biomol. Struct., 28, 155179.[CrossRef][ISI][Medline]
Sanschagrin,P.C. and Kuhn,L.A. (1998) Protein Sci., 7, 20542064.
Shaw,J.P., Petsko,G.A. and Ringe,D. (1997) Biochemistry, 36, 13291342.[CrossRef][ISI][Medline]
Spies,M.A. and Toney,M.D. (2003) Biochemistry, 6, 50995107.[CrossRef]
Sreenivasan,U. and Axelsen,P.H. (1992) Biochemistry, 31, 1278512791.[ISI][Medline]
Stamper,G.F. and Ringe,D. (2003) PDB Code: 1FTX, http://www.rcsb.org.
Stamper,G.F., Morollo,A.A., Ringe,D. and Stamper,C.G. (1998) Biochemistry, 37, 1043810445.[CrossRef][ISI][Medline]
Strych,U. and Benedik,M.J. (2002) J. Bacteriol., 184, 43214325.
Teeter,M.M. (1991) Annu. Rev. Biophys. Biophys. Chem., 20, 577600.[CrossRef][ISI][Medline]
Watanabe,A., Yoshimura,T., Mikami,B., Hayashi,H., Kagamiyama,H. and Esaki,N. (2002) J. Biol. Chem., 277, 1916619172.
Williams,M.A., Goodfellow,J.M. and Thornton,J.M. (1994) Protein Sci., 3, 12241235.
Wong,C.M.J. (1987) Isr. J. Chem., 27, 211215.[ISI]
Wood,R.H. (1995) J. Chem. Phys., 103, 61776184.[CrossRef][ISI]
Zhang,X.J. and Matthews,B.W. (1994) Protein Sci., 3, 10311039.
Received December 4, 2003; revised March 21, 2004; accepted March 31, 2004 Edited by Brian Matthews
|