Species dependence of enzyme-substrate encounter rates for triose phosphate isomerases

Structural Consideration of the Working Mechanism of Fold Type I Transaminases From Eubacteria: Overt and Covert Movement

Transaminases (TAs) reversibly catalyze the transfer reaction of an amino group between an amino group donor and an amino group acceptor, using pyridoxal 5′-phosphate (PLP) as a cofactor. TAs are categorized according to the amino group position of the donor substrate and respective TAs recognize their own specific substrates. Over the past decade, a number of TA structures have been determined by X-ray crystallography. On the basis of the structural information, the detailed mechanism of substrate recognition by TAs has also been elucidated. In this review, fold type I TAs are addressed intensively. Comparative studies on structural differences between the apo and holo forms of fold type I TAs have demonstrated that regions containing the active site exhibit structural plasticity in the apo form, facilitating PLP insertion into the active site. In addition, given that TAs recognize two different kinds of substrates, they possess dual substrate specificity. It is known that spatial rearrangements of active site residues occur upon binding of the substrates. Intriguingly, positively charged residues are predominantly distributed at the active site cavity. The electric field generated by such charge distributions may attract negatively charged molecules, such as PLP and amino group acceptors, into the active site. Indeed, TAs show remarkable dynamics in diverse aspects. In this review, we describe the comprehensive working mechanism of fold type I TAs, with a focus on conformational changes.

Conservation and Role of Electrostatics in Thymidylate Synthase

Conservation of function across families of orthologous enzymes is generally accompanied by conservation of their active site electrostatic potentials. To study the electrostatic conservation in the highly conserved essential enzyme, thymidylate synthase (TS), we conducted a systematic species-based comparison of the electrostatic potential in the vicinity of its active site. Whereas the electrostatics of the active site of TS are generally well conserved, the TSs from minimal organisms do not conform to the overall trend. Since the genomes of minimal organisms have a high thymidine content compared to other organisms, the observation of non-conserved electrostatics was surprising. Analysis of the symbiotic relationship between minimal organisms and their hosts, and the genetic completeness of the thymidine synthesis pathway suggested that TS from the minimal organism Wigglesworthia glossinidia (W.g.b.) must be active. Four residues in the vicinity of the active site of Escherichia coli TS were mutated individually and simultaneously to mimic the electrostatics of W.g.b TS. The measured activities of the E. coli TS mutants imply that conservation of electrostatics in the region of the active site is important for the activity of TS, and suggest that the W.g.b. TS has the minimal activity necessary to support replication of its reduced genome.

Cross-species analysis of the glycolytic pathway by comparison of molecular interaction fields

The electrostatic potential of an enzyme is a key determinant of its substrate interactions and catalytic turnover. Here we invoke comparative analysis of protein electrostatic potentials, along with sequence and structural analysis, to classify and characterize all the enzymes in an entire pathway across a set of different organisms. The electrostatic potentials of the enzymes from the glycolytic pathway of 11 eukaryotes were analyzed by qPIPSA (quantitative protein interaction property similarity analysis). The comparison allows the functional assignment of neuron-specific isoforms of triosephosphate isomerase from zebrafish, the identification of unusual protein surface interaction properties of the mosquito glucose-6-phosphate isomerase and the functional annotation of ATP-dependent phosphofructokinases and cofactor-dependent phosphoglycerate mutases from plants. We here show that plants possess two parallel pathways to convert glucose. One is similar to glycolysis in humans, the other is specialized to let plants adapt to their environmental conditions. We use differences in electrostatic potentials to estimate kinetic parameters for the triosephosphate isomerases from nine species for which published parameters are not available. Along the core glycolytic pathway, phosphoglycerate mutase displays the most conserved electrostatic potential. The largest cross-species variations are found for glucose-6-phosphate isomerase, enolase and fructose-1,6-bisphosphate aldolase. The extent of conservation of electrostatic potentials along the pathway is consistent with the absence of a single rate-limiting step in glycolysis.

qPIPSA: relating enzymatic kinetic parameters and interaction fields

Background

The simulation of metabolic networks in quantitative systems biology requires the assignment of enzymatic kinetic parameters. Experimentally determined values are often not available and therefore computational methods to estimate these parameters are needed. It is possible to use the three-dimensional structure of an enzyme to perform simulations of a reaction and derive kinetic parameters. However, this is computationally demanding and requires detailed knowledge of the enzyme mechanism. We have therefore sought to develop a general, simple and computationally efficient procedure to relate protein structural information to enzymatic kinetic parameters that allows consistency between the kinetic and structural information to be checked and estimation of kinetic constants for structurally and mechanistically similar enzymes.

Results

We describe qPIPSA: quantitative Protein Interaction Property Similarity Analysis. In this analysis, molecular interaction fields, for example, electrostatic potentials, are computed from the enzyme structures. Differences in molecular interaction fields between enzymes are then related to the ratios of their kinetic parameters. This procedure can be used to estimate unknown kinetic parameters when enzyme structural information is available and kinetic parameters have been measured for related enzymes or were obtained under different conditions. The detailed interaction of the enzyme with substrate or cofactors is not modeled and is assumed to be similar for all the proteins compared. The protein structure modeling protocol employed ensures that differences between models reflect genuine differences between the protein sequences, rather than random fluctuations in protein structure.

Conclusion

Provided that the experimental conditions and the protein structural models refer to the same protein state or conformation, correlations between interaction fields and kinetic parameters can be established for sets of related enzymes. Outliers may arise due to variation in the importance of different contributions to the kinetic parameters, such as protein stability and conformational changes. The qPIPSA approach can assist in the validation as well as estimation of kinetic parameters, and provide insights into enzyme mechanism.

Calculation of short-range interactions between proteins

Macromolecular association is an integral component of numerous cellular and technologically relevant processes. Most molecular theories of such association neglect the explicit solvent structure and rely on continuum concepts such as surface energies for calculating short-range interactions. We present a new such method for calculating the non-electrostatic component of the interaction-free energy, based on formalisms for calculating dispersion interactions between macromolecules. The interactions are separated into a short-ranged component that is treated atomistically, and a longer range component that is treated within the continuum Lifshitz-Hamaker approach. This description avoids the singularities inherent in the continuum dispersion formulation, and its effectiveness in characterizing the shape complementarity between interacting surfaces is shown to be comparable to that of surface area-based methods of similar parametric complexity. An advantage of the new method is that it allows facile calculation of the interaction free energy as a function of intermolecular separation, including steric effects; this makes it suitable for use in simulations of protein solutions.

Large-scale modelling as a route to multiple surface comparisons of the CCP module family

Numerous mammalian proteins are constructed from a limited repertoire of module-types. Proteins belonging to the regulators of complement activation family--crucial for ensuring a complement-mediated immune response is targeted against infectious agents--are composed solely of complement control protein (CCP) modules. In the current study, CCP module sequences were grouped to allow selection of the most appropriate experimentally determined structures to serve as templates in an automated large-scale structure modelling procedure. The resulting 135 individual CCP module models, valuable in their own right, are available at the online database http://www.bru.ed.ac.uk/~dinesh/ccp-db.html. Comparisons of surface properties within a particular family of modules should be more informative than sequence alignments alone. A comparison of surface electrostatic features was undertaken for the first 28 CCP modules of complement receptor type 1 (CR1). Assignments to clusters based on surface properties differ from assignments to clusters based on sequences. This observation might reflect adaptive evolution of surface-exposed residues involved in protein-protein interactions. This illustrative example of a multiple surface-comparison was indeed able to pinpoint functional sites in CR1.

Comparative structural and energetic analysis of WW domain-peptide interactions

WW domains are small globular protein interaction modules found in a wide spectrum of proteins. They recognize their target proteins by binding specifically to short linear peptide motifs that are often proline-rich. To infer the determinants of the ligand binding propensities of WW domains, we analyzed 42 WW domains. We built models of the 3D structures of the WW domains and their peptide complexes by comparative modeling supplemented with experimental data from peptide library screens. The models provide new insights into the orientation and position of the peptide in structures of WW domain-peptide complexes that have not yet been determined experimentally. From a protein interaction property similarity analysis (PIPSA) of the WW domain structures, we show that electrostatic potential is a distinguishing feature of WW domains and we propose a structure-based classification of WW domains that expands the existent ligand-based classification scheme. Application of the comparative molecular field analysis (CoMFA), GRID/GOLPE and comparative binding energy (COMBINE) analysis methods permitted the derivation of quantitative structure-activity relationships (QSARs) that aid in identifying the specificity-determining residues within WW domains and their ligand-recognition motifs. Using these QSARs, a new group-specific sequence feature of WW domains that target arginine-containing peptides was identified. Finally, the QSAR models were applied to the design of a peptide to bind with greater affinity than the known binding peptide sequences of the yRSP5-1 WW domain. The prediction was verified experimentally, providing validation of the QSAR models and demonstrating the possibility of rationally improving peptide affinity for WW domains. The QSAR models may also be applied to the prediction of the specificity of WW domains with uncharacterized ligand-binding properties.

Essential motions in a fungal lipase with bound substrate, covalently attached inhibitor and product

As an aid to understanding the influence of dynamic fluctuations during esterolytic catalysis, we follow protein flexibility at three different steps along the catalytic pathway from substrate binding to product clearance via a covalently attached inhibitor, which represents a transition-state mimic. We have applied a classical approach, using molecular dynamics simulations to monitor protein dynamics in the nanosecond regime. We filter out small amplitude fluctuations and focus on the anharmonic contributions to the overall dynamics. This 'essential dynamics' analysis reveals different modes of response along the pathway suggesting that binding, catalysis and product clearance occur along different energy surfaces. Motions in the enzyme with a covalently attached ligand are more complex and occur along several eigenvectors. The magnitudes of the fluctuations in these individual subspaces are significantly smaller than those observed for the substrate and product molecules, indicating that the energy surface is shallow and that a relatively large number of conformational substates are accessible. On the other hand, substrate binding and product release occur at distinct modes of the protein flexibility suggesting that these processes occur along rough energy surfaces with only a few minima. Detailed energetic analyses along the trajectories indicated that in all cases binding is dominated by van der Waals interactions. The carboxylate form of the product is stabilized by a tight hydrogen bond network involving in particular Ser82, which may be a potential cause of product inhibition. Considerations such as these should aid the understanding of mechanisms of substrate, inhibitor or product recognition and could become of importance in the design of new substrates or inhibitors for enzymes.

Recognition between flexible protein molecules: induced and assisted folding

This review focuses on a very important but little understood type of molecular recognition--the recognition between highly flexible molecular structures. The formation of a specific complex in this case is a dynamic process that can occur through sequential steps of mutual conformational adaptation. This allows modulation of specificity and affinity of interaction in extremely broad ranges. The interacting partners can interact together to form a complex with entirely new properties and produce conformational signal transduction at substantial distance. We show that this type of recognition is frequent in formation of different protein-protein and protein-nucleic acid complexes. It is also characteristic for self-assembly of protein molecules from their unfolded fragments as well as for interaction of molecular chaperones with their substrates and it can be the origin of 'protein misfolding' diseases. Thermodynamic and kinetic features of this type of dynamic recognition and the principles underlying their modeling and analysis are discussed.

Biochemical evidence that Escherichia coli hyi (orf b0508, gip) gene encodes hydroxypyruvate isomerase

We found a significant activity of hydroxypyruvate isomerase in Escherichia coli clone cells harboring an E. coli gene (called orf b0508 or gip), which is located downstream of the glyoxylate carboligase gene. We newly designated the gene hyi. The enzyme was purified from cell extracts of the E. coli clone. The enzyme had a molecular mass of 58 kDa and was composed of two identical subunits. The optimum pH for the isomerization of hydroxypyruvate was 6.8-7.2. The enzyme required no cofactor. It exclusively catalyzed the isomerization between hydroxypyruvate and tartronate semialdehyde. The apparent K(m) value for hydroxypyruvate was 12.5 mM. The amino acid sequence of E. coli hydroxypyruvate isomerase is highly similar to those of glyoxylate-induced proteins, Gip, found widely from prokaryotes to eukaryotes.

Classification of protein sequences by homology modeling and quantitative analysis of electrostatic similarity

Protein electrostatics plays a key role in ligand binding and protein-protein interactions. Therefore, similarities or dissimilarities in electrostatic potentials can be used as indicators of similarities or dissimilarities in protein function. We here describe a method to compare the electrostatic properties within protein families objectively and quantitatively. Three-dimensional structures are built from database sequences by comparative modeling. Molecular potentials are then computed for these with a continuum solvation model by finite difference solution of the Poisson-Boltzmann equation or analytically as a multipole expansion that permits rapid comparison of very large datasets. This approach is applied to 104 members of the Pleckstrin homology (PH) domain family. The deviation of the potentials of the homology models from those of the corresponding experimental structures is comparable to the variation of the potential in an ensemble of structures from nuclear magnetic resonance data or between snapshots from a molecular dynamics simulation. For this dataset, the results for analysis of the full electrostatic potential and the analysis using only monopole and dipole terms are very similar. The electrostatic properties of the PH domains are generally conserved despite the extreme sequence divergence in this family. Notable exceptions from this conservation are seen for PH domains linked to a Db1 homology (DH) domain and in proteins with internal PH domain repeats.

Computer simulation of protein-protein association kinetics: acetylcholinesterase-fasciculin

Computer simulations were performed to investigate the role of electrostatic interactions in promoting fast association of acetylcholinesterase with its peptidic inhibitor, the neurotoxin fasciculin. The encounter of the two macromolecules was simulated with the technique of Brownian dynamics (BD), using atomically detailed structures, and association rate constants were calculated for the wild-type and a number of mutant proteins. In a first set of simulations, the ordering of the experimental rate constants for the mutant proteins was correctly reproduced, although the absolute values of the rate constants were overestimated by a factor of around 30. Rigorous calculations of the full electrostatic interaction energy between the two proteins indicate that this overestimation of association rates results at least in part from approximations made in the description of interaction energetics in the BD simulations. In particular, the initial BD simulations neglect the unfavourable electrostatic desolvation effects that result from the exclusion of high dielectric solvent that accompanies the approach of the two low dielectric proteins. This electrostatic desolvation component is so large that the overall contribution of electrostatics to the binding energy of the complex is unlikely to be strongly favourable. Nevertheless, electrostatic interactions are still responsible for increased association rates, because even if they are unfavourable in the fully formed complex, they are still favourable at intermediate protein-protein separation distances. It therefore appears possible for electrostatic interactions to promote the kinetics of binding even if they do not make a strongly favourable contribution to the thermodynamics of binding. When an approximate description of these electrostatic desolvation effects is included in a second set of BD simulations, the relative ordering of the mutant proteins is again correctly reproduced, but now association rate constants that are much closer in magnitude to the experimental values are obtained. Inclusion of electrostatic desolvation effects also improves reproduction of the experimental ionic strength dependence of the wild-type association rate.

On the protein-protein diffusional encounter complex

When two proteins diffuse together to form a bound complex, an intermediate is formed at the end-point of diffusional association which is called the encounter complex. Its characteristics are important in determining association rates, yet its structure cannot be directly observed experimentally. Here, we address the problem of how to construct the ensemble of three-dimensional structures which constitute the protein-protein diffusional encounter complex using available experimental data describing the dependence of protein association rates on mutation and on solvent ionic strength and viscosity. The magnitude of the association rates is fitted well using a variety of definitions of encounter complexes in which the two proteins are located at up to about 17 A root-mean-squared distance from their relative arrangement in the bound complex. Analysis of the ionic strength dependence of bimolecular association rates shows that this is determined to a greater extent by the (protein charge) - (salt ion) separation distance than by the protein-protein charge separation distance. Consequently, ionic strength dependence of association rates provides little information about the geometry of the encounter complex. On the other hand, experimental data on electrostatic rate enhancement, mutation and viscosity dependence suggest a model of the encounter complex in which the two proteins form a subset of the contacts present in the bound complex and are significantly desolvated.