Biomedical subjects
Publications and source records attributed to A M Mathiowetz.
Anilinoquinazolines currently of interest as inhibitors of tyrosine kinases have been found to be allosteric inhibitors of the enzyme fructose 1,6-bisphosphatase. These represent a new approach to inhibition of F16BPase and serve as leads for further drug design. Enzyme inhibition is achieved by binding at an unidentified allosteric site.
BACKGROUND: Glycogen phosphorylases catalyze the breakdown of glycogen to glucose-1-phosphate for glycolysis. Maintaining control of blood glucose levels is critical in minimizing the debilitating effects of diabetes, making liver glycogen phosphorylase a potential therapeutic target. RESULTS: The binding site in human liver glycogen phosphorylase (HLGP) for a class of promising antidiabetic agents was identified crystallographically. The site is novel and functions allosterically by stabilizing the inactive conformation of HLGP. The initial view of the complex revealed key structural information and inspired the design of a new class of inhibitors which bind with nanomolar affinity and whose crystal structure is also described. CONCLUSIONS: We have identified the binding site of a new class of allosteric HLGP inhibitors. The crystal structure revealed the details of inhibitor binding, led to the design of a new class of compounds, and should accelerate efforts to develop therapeutically relevant molecules for the treatment of diabetes.
We report here the backbone 1HN, 15N, 13C alpha, 13CO, and 1H alpha NMR assignments for the catalytic domain of human fibroblast collagenase (HFC). Three independent assignment pathways (matching 1H, 13C alpha, and 13CO resonances) were used to establish sequential connections. The connections using 13C alpha resonances were obtained from HNCOCA and HNCA experiments; 13CO connections were obtained from HNCO and HNCACO experiments. The sequential proton assignment pathway was established from a 3D (1H/15N) NOESY-HSQC experiment. Amino acid typing was accomplished using 13C and 15N chemical shifts, specific labeling of 15N-Leu, and spin pattern recognition from DQF-COSY. The secondary structure was determined by analyzing the 3D (1H/15N) NOESY-HSQC. A preliminary NMR structure calculation of HFC was found to be in agreement with recent X-ray structures of human fibroblast collagenase and human neutrophil collagenase as well as similar to recent NMR structures of a highly homologous protein, stromelysin. All three helices were located; a five-stranded beta-sheet (four parallel strands, one antiparallel strand) was also determined. beta-Sheet regions were identified by cross-strand d alpha N and d NN connections and by strong intraresidue d alpha N correlations, and were corroborated by observing slow amide proton exchange. Chemical shift changes in a selectively 15N-labeled sample suggest that substantial structural changes occur in the active site cleft on the binding of an inhibitor.
In this study, structure-based drug design of matrix metalloproteinase inhibitors [human fibroblast collagenase (HFC), human fibroblast stromelysin (HFS), and human neutrophil collagenase (HNC)] was utilized in the development of potent hydroxamates which contain novel, heteroatom-based modifications of the P1' group. A series containing a P1' butyramide group resulted in a nanomolar potent and selective HNC inhibitor as well as a dual HFS/HNC inhibitor. Benzylic ethers with a four- or five-carbon methylene linker in the P1' position also produced nanomolar potent HFS/HNC inhibition and micromolar potent HFC inhibition as expected. Surprisingly, the phenolic ethers of the same overall length as the benzylic ethers showed nanomolar potencies against HFC, as well as HFS and HNC. The potency profile of the phenolic ethers was optimized by structure-activity relationships of the phenolic group and the C-terminal amide. These inhibitors may help elucidate the in vivo roles of matrix metalloproteinases in normal and disease states.
We tested the dihedral probability grid Monte Carlo (DPG-MC) methodology to determine optimal conformations of polypeptides by applying it to predict the low energy ensemble for two peptides whose solution NMR structures are known: integrin receptor peptide (YGRGDSP, Type II beta-turn) and S3 alpha-helical peptide (YMSEDEL KAAEAAFKRHGPT). DPG-MC involves importance sampling, local random stepping in the vicinity of a current local minima, and Metropolis sampling criteria for acceptance or rejection of new structures. Internal coordinate values are based on side-chain-specific dihedral angle probability distributions (from analysis of high-resolution protein crystal structures). Important features of DPG-MC are: (1) Each DPG-MC step selects the torsion angles (phi, psi, chi) from a discrete grid that are then applied directly to the structure. The torsion angle increments can be taken as S = 60, 30, 15, 10, or 5 degrees, depending on the application. (2) DPG-MC utilizes a temperature-dependent probability function (P) in conjunction with Metropolis sampling to accept or reject new structures. For each peptide, we found close agreement with the known structure for the low energy conformational ensemble located with DPG-MC. This suggests that DPG-MC will be useful for predicting conformations of other polypeptides.
Dihedral probability grid Monte Carlo (DPG-MC) is a general-purpose method of conformational sampling that can be applied to many problems in peptide and protein modeling. Here we present the DPG-MC method and apply it to predicting complete protein structures from C alpha coordinates. This is useful in such endeavors as homology modeling, protein structure prediction from lattice simulations, or fitting protein structures to X-ray crystallographic data. It also serves as an example of how DPG-MC can be applied to systems with geometric constraints. The conformational propensities for individual residues are used to guide conformational searches as the protein is built from the amino-terminus to the carboxyl-terminus. Results for a number of proteins show that both the backbone and side chain can be accurately modeled using DPG-MC. Backbone atoms are generally predicted with RMS errors of about 0.5 A (compared to X-ray crystal structure coordinates) and all atoms are predicted to an RMS error of 1.7 A or better.
Two new methods developed for molecular dynamics simulations of very large proteins are applied to a series of proteins ranging up to the protein capsid of tomato bushy stunt virus (TBSV). For molecular dynamics of very large proteins and polymers, it is useful to carry out the dynamics using internal coordinates (say, torsions only) rather than Cartesian coordinates. This allows larger time steps, eliminates problems with the classical description of high energy modes, and focuses on the important degrees of freedom. The resulting equation of motion has the form. [formula: see text] where for T is the vector of generalized forces, M(theta) is the moments of inertia tensor, theta is the vector of torsions, and C is a vector containing Coriolis forces and nonbond forces. The problem is that to calculate the acceleration vector theta from M, C, and T requires inverting M(theta), an order N3 calculation. Since the number of degrees of freedom might be 300,000 for a million atom system, solving these equations every time step is impractical, restricting internal coordinate methods to small systems. The new method, Newton-Euler Inverse Mass Operator (NEIMO) dynamics, constructs the torsional accelerations vector theta = M-1 (T-C) directly by an order N process, allowing internal-coordinate dynamics to be solved for super larger (million atom) systems. The first use of the NEIMO method for molecular dynamics of proteins is presented here. A second serious difficulty for large proteins is calculation of the nonbond forces. We report here the first application to proteins of the new Cell Multipole Method (CMM) to evaluate the Coulomb and van der Waals interactions. The costs of CMM scales linearly with the number of particles while retaining an accuracy significantly better than standard nonbond methods (involving cutoffs). Results for NEIMO and CMM are given for simulations of a wide range of peptide and protein systems, including the protein capsid of TBSV with 488,000 atoms. The computational times for NEIMO and CMM are demonstrated to scale linearly with size. With NEIMO the dynamics time steps can be as large as 20 fs (for small peptides), much larger than possible with standard Cartesian coordinate dynamics. For TBSV we considered both the normal form and the high pH form, in which the Ca2+ ions are removed. These calculations lead to a contraction of the protein for both forms (probably because of ignoring the RNA core not observed in the X-ray).
The function of arginine 65, a conserved residue located at the periphery of the active site cleft in yeast 3-phosphoglycerate kinase (PGK), has been investigated by site-directed mutagenesis. Mutant enzymes with glutamine, serine and alanine at position 65 all have very similar kinetic properties. The maximum velocities, determined in the absence of sulfate anion, are approximately 100% higher than the Vmax of wild-type PGK. The Km values are increased 2- to 3-fold for ATP and 5- to 6-fold for 3-phosphoglycerate (3PG). These results demonstrate that arginine 65 is not essential for catalysis. In contrast to wild-type enzyme, the mutants are not activated by sulfate ions. In addition, steady-state kinetic experiments indicate that the mutants are no longer activated by high concentrations of either 3PG or ATP. The dissociation constants for anions were determined by spectral titrations of the R65Q mutant labeled with a chromophoric probe. The Kd for 3PG is increased 6-fold, as compared to wild-type PGK, whereas the Kd for ATP is essentially unchanged. The Kd for sulfate is decreased less than 2-fold. The suppression of substrate- and sulfate-dependent activation suggests that arginine 65 participates in the regulatory mechanism responsible for activation of the enzyme.
A cluster of conserved histidines and arginines (His-62, His-167, Arg-21, Arg-38, and Arg-168) in 3-phosphoglycerate kinase (PGK) has been implicated as possibly involved in the binding of 3-phosphoglycerate (3-PG) and/or stabilization of the negatively charged transition state. The role of these residues in the catalytic function of yeast PGK and in the substrate- and sulfate-dependent activation was investigated by site-directed mutagenesis. The following substitutions, R21A, R21Q, H62Q, H167S, and R168Q, produced functional enzymes. In contrast, the R38A and R38Q mutations resulted in a complete loss of catalytic activity. These results demonstrate that of the basic residues studied, only arginine 38 is essential for the catalytic function of PGK. A moderate decrease in the catalytic efficiency as the result of the R21A, H167S, and R168Q mutations and an increased catalytic efficiency of the H62Q mutant rule out a possible role of a positive charge at these positions in the mechanism of phosphoryl transfer reaction. In contrast to the wild type PGK and the H62Q mutant, both of which are activated at low and inhibited at high sulfate concentration, the H167S, R168Q, and R21A mutants exhibited a progressive inhibition with increased concentration of sulfate. The activation observed at high concentration of either ATP or 3-PG as a variable substrate in the steady-state kinetics of wild type PGK was abolished as the result of the latter three mutations. The results of this work support the hypothesis that PGK has two binding sites for anionic ligands, the catalytic and regulatory sites for each substrate and the activatory and inhibitory sites for sulfate, and suggest that arginine 21, arginine 168, and histidine 167 are located in the activatory anion binding site, common for sulfate, 3-PG, and ATP. The increased Km values for both substrates and decreased specific activities of the mutants suggest that this regulatory site is close to the catalytic site.
Molecular dynamics simulations were coupled with experimental data from biochemistry and genetics to generate a theoretical structure for the binding domain of Hin recombinase complexed with the hix site of DNA. The theoretical model explains the observed sequence specificity of Hin recombinase and leads to a number of testable predictions concerning altered sequence selectivity for various mutants of protein and DNA.