Functional Characterization of MODY2 Mutations Highlights the Importance of the Fine-Tuning of Glucokinase and Its Role in Glucose Sensing

Glucokinase (GK) acts as a glucose sensor in the pancreatic beta-cell and regulates insulin secretion. Heterozygous mutations in the human GK-encoding GCK gene that reduce the activity index increase the glucose-stimulated insulin secretion threshold and cause familial, mild fasting hyperglycaemia, also known as Maturity Onset Diabetes of the Young type 2 (MODY2). Here we describe the biochemical characterization of five missense GK mutations: p.Ile130Thr, p.Asp205His, p.Gly223Ser, p.His416Arg and p.Ala449Thr. The enzymatic analysis of the corresponding bacterially expressed GST-GK mutant proteins show that all of them impair the kinetic characteristics of the enzyme. In keeping with their position within the protein, mutations p.Ile130Thr, p.Asp205His, p.Gly223Ser, and p.His416Arg strongly decrease the activity index of GK, affecting to one or more kinetic parameters. In contrast, the p.Ala449Thr mutation, which is located in the allosteric activator site, does not affect significantly the activity index of GK, but dramatically modifies the main kinetic parameters responsible for the function of this enzyme as a glucose sensor. The reduced Kcat of the mutant (3.21±0.28 s−1 vs 47.86±2.78 s−1) is balanced by an increased glucose affinity (S0.5 = 1.33±0.08 mM vs 7.86±0.09 mM) and loss of cooperativity for this substrate. We further studied the mechanism by which this mutation impaired GK kinetics by measuring the differential effects of several competitive inhibitors and one allosteric activator on the mutant protein. Our results suggest that this mutation alters the equilibrium between the conformational states of glucokinase and highlights the importance of the fine-tuning of GK and its role in glucose sensing

Structure-Based Predictive Models for Allosteric Hot Spots

In allostery, a binding event at one site in a protein modulates the behavior of a distant site. Identifying residues that relay the signal between sites remains a challenge. We have developed predictive models using support-vector machines, a widely used machine-learning method. The training data set consisted of residues classified as either hotspots or non-hotspots based on experimental characterization of point mutations from a diverse set of allosteric proteins. Each residue had an associated set of calculated features. Two sets of features were used, one consisting of dynamical, structural, network, and informatic measures, and another of structural measures defined by Daily and Gray [1]. The resulting models performed well on an independent data set consisting of hotspots and non-hotspots from five allosteric proteins. For the independent data set, our top 10 models using Feature Set 1 recalled 68–81% of known hotspots, and among total hotspot predictions, 58–67% were actual hotspots. Hence, these models have precision P = 58–67% and recall R = 68–81%. The corresponding models for Feature Set 2 had P = 55–59% and R = 81–92%. We combined the features from each set that produced models with optimal predictive performance. The top 10 models using this hybrid feature set had R = 73–81% and P = 64–71%, the best overall performance of any of the sets of models. Our methods identified hotspots in structural regions of known allosteric significance. Moreover, our predicted hotspots form a network of contiguous residues in the interior of the structures, in agreement with previous work. In conclusion, we have developed models that discriminate between known allosteric hotspots and non-hotspots with high accuracy and sensitivity. Moreover, the pattern of predicted hotspots corresponds to known functional motifs implicated in allostery, and is consistent with previous work describing sparse networks of allosterically important residues

Study of the regulatory properties of glucokinase by site-directed mutagenesis: conversion of glucokinase to an enzyme with high affinity for glucose.

To identify the amino acids involved in the specific regulatory properties of glucokinase, and particularly its low affinity for glucose, mutants of the human islet enzyme have been prepared, in which glucokinase-specific residues have been replaced. Two mutations increased the affinity for glucose by twofold (K296M) and sixfold (Y214A), the latter also decreasing the Hill coefficient from 1.75 to 1.2 with minimal change in the affinity for ATP. Combining these two mutations with N166R resulted in a 50-fold decrease in the half-saturating substrate concentration (S0.5) value, which became then comparable to the Km of hexokinase II. The location of N166, Y214, and K296 in the three-dimensional structure of glucokinase suggests that these mutations act by favoring closure of the catalytic cleft. As a rule, mutations changed the affinity for glucose and for the competitive inhibitor mannoheptulose (MH) in parallel, whereas they barely affected the affinity for N-acetylglucosamine (NAG). These and other results suggest that NAG and MH bind to the same site but to different conformations of glucokinase. A small reduction in the affinity for the regulatory protein was observed with mutations of residues on the smaller domain and in the hinge region, confirming the bipartite nature of the binding site for the regulatory protein. The K296M mutant was found to have a threefold decreased affinity for palmitoyl CoA; this effect was additive to that previously observed for the E279Q mutant, indicating that the binding site for long-chain acyl CoAs is located on the upper face of the larger domain

Structure—function analysis of the α5 and the α13 helices of human glucokinase: Description of two novel activating mutations

It was recently described that the α5 and the α13 helices of human pancreatic glucokinase play a major role in the allosteric regulation of the enzyme. In order to understand the structural importance of these helices, we have performed site-directed mutagenesis to generate glucokinase derivatives with altered residues. We have analyzed the kinetic parameters of these mutated forms and compared them with wild-type and previously defined activating mutations in these helices (A456V and Y214C). We found two new activating mutations, A460R and Y215A, which increase the affinity of the enzyme for glucose. Our results suggest that substitutions in the α5 or the α13 helices that favor the closed, active conformation of the enzyme, either by improving the interaction with surrounding residues or by improving the flexibility of the region defined by these two helices, enhance the affinity of the enzyme for glucose, and therefore its performance as a glucose phosphorylating enzyme