Guide Insights into Enzyme Mechanisms and Functions from Experimental and Computational Methods

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In addition, the occurrence of feedback inhibition in agreement with, in turn, that the computation-derived relative order, i. In summary, a novel binding model for protogen with PPO has been identified by combining extensive computational simulations and mutagenesis studies. Based on this newly identified binding model, the enzyme-substrate ES , enzyme-product EP recognition pathway, the corresponding free energy profiles, and the feedback inhibition mechanism have been identified. The simulated PMF free energy profile was barrierless for protogen binding, which indicates that the protogen binding process should be very fast.

But the free energy profiles showed that the dissociation process for proto should be slower than protogen, indicating that PPO activity is modulated by a feedback inhibition with respect to proto. The kinetic time courses also displayed a burst of product formation followed by a linear steady-state rate when reactions were initiated by the addition of enzyme, which is a hallmark of feedback inhibition. We believed that the established structural and energetic insights into the entire ES binding and EP dissociation process provide a valuable basis for future structure- and product-based design of highly potent PPO inhibitors for application in the development of agrochemicals or PDT cancer therapy.

The initial structure was revised first by means of adding lost residues and hydrogen atoms, checking bonds and bumps, then energy minimized for 2, steps of steepest descent calculations and 2, steps of conjugated gradient calculations by using SYBYL 7. The optimized geometries were used to construct the entire structures of protogen and the final structures of different conformations were optimized with the macrocycle fixed by using conjugated gradient in SYBYL 7. The different conformations were used as the starting structures for docking studies.

Docking calculations were performed on these conformations with AutoDock4. The protein and ligand structures were prepared with AutoDock Tools [30]. The atomic Gasteiger-Huckel charges were assigned to the ligand and receptor. A total of runs were launched. Most of the parameters for the docking calculation were set to the default values recommended by the software.

Each docked structure was scored by the built-in scoring function and was clustered by 0. During the energy minimization process, the receptor was first fixed and only the ligand was kept free; then the ligand and residue sidechains were kept free; finally all atoms of the system were kept free and refined to a convergence of 0. To avoid the drawbacks of the Autodock program and the conformational analysis method, we also tested other docking programs and methods.

See Supporting Information Figure S2 for detailed results.

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Based on the analysis of docking results, two binding models were selected for MD simulation. Prior to that, with the Gaussian-optimized geometries, the electrostatic potential and partial atomic charges were determined by performing the electrostatic potential ESP fitting according to the Merz—Singh—Kollman scheme [32] , [33]. The system was solvated in an octahedral box of TIP3P water with the crystallographic water molecules kept. Appropriate sodium counterions were added to the system to preserve neutrality.

The solvated system had a total of about 58, atoms, with about 7, of them belonging to the solute. Before the MD simulation, some energy minimization steps were applied to the system. In each step, energy minimization was first performed by using the steepest descent algorithm for 2, steps and then the conjugated gradient algorithm for another 3, steps.

The MD simulation was performed under periodic boundary conditions by using the Sander module of the AMBER9 program, as we have done for the same protein before [36]. First, the system was fixed to make the heating only for waters and counterions for 10 ps to make sure the solute was fully solvated; then, the whole system was gradually heated from 10 to K by weak-coupling method [37] and equilibrated for ps with the protein backbone fixed; lastly, the system was switched to a constant pressure equilibration to 3 ns.

All of the angles and bonds involving hydrogen atoms were constrained by using the SHAKE algorithm [40]. The time step used for the MD simulations was 2. Because the flexibility of the side chain and the ligand-protein interaction was of concern, a shorter simulation time 3 ns was adopted. The MD simulations were performed with all the hydrogen bond distances constrained at the beginning, which were then slowly relaxed. A total of 1, snapshots were taken from the last 1 ns trajectory with an interval of 1 ps to analyze the binding energy and at the same time, the counterions and water molecules waters related to the crucial hydrogen bond were not included were stripped.

Further, the MD simulations of M14 and M15 were also repeated with different sets of parameters and force-field see details in Figure S4. The final binding free energy was determined as the average of all the snapshots and the standard errors were also calculated with the same method reported before [42]. Finally, hydrogen bond energies HBE were also calculated by using a previously published method [43]. In this calculation the reaction coordinate was divided into windows separated by 0. The initial complex structure was adopted directly from our previous MD simulations. The biasing force constant applied in different windows of umbrella-sampling ranged from 4.

The selected structure for each window was first equilibrated for 50 ps and then kept running for 1, ps. The three curves associated with the MD simulations during 0. Finally, the data collected from separate simulation windows were combined along the reaction coordinate and a ns trajectory was obtained for each system, which were then used to calculate the PMF along the whole recognition pathway with the weighed histogram analysis method WHAM [45].

Harry A. Expression and purification methods of h PPO were the same as used with our previous publication [21]. The product had a maximum excitation wavelength of nm and a maximum emission wavelength of nm. The reaction was initiated by the addition of substrate, and the autoxidation rate was subtracted. The kinetic parameters, including the Michaelis-Menten constant K m , the maximal velocity V max , and the catalytic constant k cat , were determined by a Lineweaver-Burk plot.

Two experiments were performed to verify the occurrence of feedback inhibition. Experiment 1: The concentration of h PPO enzyme was 3. The reaction was initiated by the addition of various concentrations of the substrate 0. The auto-oxidation rate of protogen was measured in the absence of enzyme and this rate was excluded from the final enzyme kinetic time-course. Experiment 2: Different concentrations of h PPO enzyme 0. Conformational distribution ratio of the conformers.

View of the binding modes of the substrate in the PPO active site, plots of key distance changes versus simulation time, and substrate-residues interaction spectrums of M14 and M We acknowledge the Computer Center at University of Kentucky for supercomputing time on a Dell Supercomputer Cluster consisting of 4, processors.

Browse Subject Areas? Click through the PLOS taxonomy to find articles in your field. Introduction To understand the function of an enzyme, the binding of the substrate S and the structure of the enzyme—substrate ES complex are central issues in determining the catalytic mechanism. Download: PPT. Figure 1. Protoporphyrinogen oxidase PPO catalyzes the oxidation reaction of protoporphyrinogen IX protogen left with molecular oxygen to produce protoporphyrin IX proto right.

Table 1. Figure 2. Table 2. Table 3. Kinetic parameters of wild-type and mutant h PPO. Figure 3. Free energy profiles determined for PPO binding with protogen black curve and proto red curve. Figure 4. Figure 5. Conclusion In summary, a novel binding model for protogen with PPO has been identified by combining extensive computational simulations and mutagenesis studies.

Molecular Dynamics Simulation and Free Energy Calculation Based on the analysis of docking results, two binding models were selected for MD simulation. Kinetic Assays for Feedback Inhibition Two experiments were performed to verify the occurrence of feedback inhibition.

High-Throughput Computational and Experimental Techniques in Structural Genomics

Supporting Information. Figure S1. The scheme of the spacial conformation of the macrocycle of the substrate. Figure S2.

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Figure S3. Figure S4. Figure S5. The models of protogen binding with different mt PPO mutants.


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Figure S6. The models of protogen binding with different h PPO mutants. Figure S7. View of the binding modes of proto in the PPO active site. Figure S8. The structural comparison between WT and R98A. Figure S9. Table S1. Docking Study Results of Different Conformers. Table S2.

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Acknowledgments We acknowledge the Computer Center at University of Kentucky for supercomputing time on a Dell Supercomputer Cluster consisting of 4, processors. References 1. Am Sci — View Article Google Scholar 2. Protoporphyrinogen oxidase activity in mitochondrial extracts of Saccharomyces cerevisiae. J Biol Chem — View Article Google Scholar 3. View Article Google Scholar 4. View Article Google Scholar 5. View Article Google Scholar 6. Bioorg Chem — View Article Google Scholar 7.

Biochim Biophys Acta 10— View Article Google Scholar 8. Biochim Biophys Acta — View Article Google Scholar 9. Arnould S, Camadro JM The domain structure of protoporphyrinogen oxidase, the molecular target of diphenyl ether-type herbicides. View Article Google Scholar Biochem J — Pest Manag Sci — Volker A, Burkhard G Antimicrobial photodynamic therapy compound and method of use.

US Patent Photodiagnosis Photodyn Ther 6: — J Photochem Photobiol B 1—8. Porphyric Pesticides: American Chemical Society. Zhang D, Gullingsrud J, McCammon JA Potentials of mean force for acetylcholine unbinding from the alpha7 nicotinic acetylcholine receptor ligand-binding domain. J Am Chem Soc — Buch I, Giorgino T, De Fabritiis G Complete reconstruction of an enzyme-inhibitor binding process by molecular dynamics simulations.

Pergamon, Oxford. EMBO J — J Comput Aided Mol Des — Huang X, Zheng F, Zhan CG Human butyrylcholinesterase-cocaine binding pathway and free energy profiles by molecular dynamics and potential of mean force simulations. J Phys Chem B — Frieden E, Walter C Prevalence and significance of the product inhibition of enzymes. Nature — Zeldenrust F, Wadman WJ Two forms of feedback inhibition determine the dynamical state of a small hippocampal network. We are always looking for ways to improve customer experience on Elsevier.

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