discuss possible mechanisms in the light of two examples that have been the subjects of recent calculations.


One way to identify the features important for the electrostatic steering of a substrate toward its binding site on an enzyme is by site-directed mutagenesis. This approach has been employed to examine the fast association rates of superoxide dismutase (SOD) and acetylcholinesterase with their substrates, and barnase with the inhibitor barstar.

  • For human SOD, mutations were identified by using BD simulations to improve electrostatic steering, and, indeed, when the mutations were made, greater electrostatic enhancement of the rate was observed (5). resulting in a “superperfect” enzyme (6).

  • For acetylcholinesterase, a large number of mutations of charged residues was made, and these were shown to have little effect on the rate of substrate binding (7). This result was interpreted as evidence of lack of diffusion control and electrostatic steering. However, the rates for the mutants could be well reproduced in BD simulations, which demonstrated enhancement of rates because of electrostatic steering of substrate toward and inside the substrate-binding gorge (8, 9).

  • Barstar is the intracellular protein inhibitor of the extracellular ribonuclease barnase, and it binds very tightly with high on-rates. Even so, the rate of binding could be improved by mutation (10). The effects of mutations and ionic strength on the association rates could be well reproduced by BD simulations (11). The data show the dominance of certain residues on the protein binding faces in determining the electrostatic enhancement of the association rate.

Together, these results indicate that electrostatic enhancement of association rates arises mostly from the presence of a few charged residues close to the binding site.

Here, we take an alternative approach to site-directed mutagenesis, namely, comparison of diffusion-influenced enzymes from different species to find out what is required for electrostatically enhanced substrate binding rates. By relying on natural evolution, we are assured of examining fully functioning enzymes although they may not be fully optimized for electrostatic enhancement of substrate on-rates or fast reaction, as this may not be desirable in their in vivo environment. We examine three families of diffusion-influenced proteins, triose-phosphate isomerases (TIM), Cu,Zn-superoxide dismutases (SOD), and class A β-lactamases (BLAC), for which crystal structures are available from several organisms and whose kinetic properties have been measured (see Table 1).

Diffusional Control of Catalytic Rates. The primary indicator for diffusion control of an enzyme reaction is a fast catalytic rate that is dependent on the viscosity and ionic strength of the solvent. Both TIM and SOD are extremely fast, efficient enzymes with the rate-limiting step of their reactions under physiological conditions being the diffusion of substrate, glyceraldehyde 3-phosphate and superoxide, respectively, to the active site, Indeed, TIM has been described as a “perfect enzyme” (12, 13). The catalytic rates measured for TIMs from more than five species are all about 108 M–1·s–1 at 100 mM ionic strength (see ref. 14 and references in ref. 15), and viscosity dependence of the rates has been demonstrated (16). The catalytic rate has been measured for SODs from more than eight species, and all have rates of about 3×109 M–1·s–1 at 20 mM ionic strength (see references in ref. 17). The rates of SODs exhibit ionic strength dependence and decrease as the ionic strength increases (18). BLACs have been characterized as fully efficient enzymes with no single rate-determining step (19). They are partly diffusion-controlled for good substrates, such as benzylpenicillin with a single negative charge, and most have catalytic rates of 107 to 108 M–1·s–1 for such substrates at 100 mM ionic strength (20, 21).

BD Simulations. Experimental association rates were reproduced well for six variants of SOD (17) and four variants of TIM (15) by BD simulation. These results show that the main features influencing the catalytic rates are represented in the simulation model. The protein is represented by all atoms observed crystallographically plus modeled polar hydrogen atoms, with each atom assigned a partial charge and a van der Waals radius. The protein is immersed in a uniform solvent continuum. The electrostatic potential of the protein is computed from numerical solution of the finite-difference linearized Poisson-Boltzmann equation (22). The substrate is represented by a charged sphere (for SOD) or dumbbell (for TIM). The molecules are treated as rigid, and intermolecular hydrodynamic interactions are neglected. Comparison of simulations with and without a net charge on the substrate show that electrostatic interactions enhance the association rates for all the enzyme variants studied.

Electrostatic Potential Similarity Analysis. To quantify the common features in the electrostatic potentials of different variants of the enzymes, we carried out an electrostatic po-tential similarity analysis. The members of each family of enzymes were superimposed by matching α-carbons. Then

Table 1. Properties of the diffusion-influenced enzymes triose-phosphate isomerase (TIM), superoxide dismutase (SOD), and β-lacktamase (BLAC)






Glyceraldehyde 3-phosphate



Net charge of substrate, c




No. of protein variants compared




Variants compared together with Protein Data Base identifier code (listed in order of increasing net charge)

E.coli (ltre), yeast (lypi), chicken muscle.* T.brucei (5tim)

Spinach (Isrd), frog (Ixso), yeast (Isdy), human (Ispd), bovine (2sod), P.leiognathi (lyai)

E.coli (TEM-1) (Ixpb), B.licheniformis (4blm), S.albus G, S.aureus (3blm)

Net charges of proteins at neutral pH. e

–12, –6, –2, +12

–8, –6, –4, –4, –2, +2

–6, –6, –4, +16

Range of sequence identity between proteins, %




Measured kcatKm, M–1·s–1×10–8




Ionic strength for rate measurement, mM




E.coli, Escherichia coli; T.brucei, Trypanosoma brucei; P.leiognathi, Photobacterium leiognathi; B.licheniformis, Bacillus licheniformis; S.albus, Streptomyces albus; S.aureus, Staphylococcus aureus.

*Coordinates provided by P.Artymiuk.

Coordinates provided by O.Dideberg.

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