Unique coenzyme binding mode of hyperthermophilic archaealsn-glycerol-1-phosphate dehydrogenase fromPyrobaculum calidifontis

2016 ◽  
Vol 84 (12) ◽  
pp. 1786-1796 ◽  
Author(s):  
Junji Hayashi ◽  
Kaori Yamamoto ◽  
Kazunari Yoneda ◽  
Toshihisa Ohshima ◽  
Haruhiko Sakuraba
Keyword(s):  
Binding Mode ◽  
Coenzyme Binding

Elucidation of the coenzyme binding mode of further B12-dependent enzymes using a base-off analogue of coenzyme B12

2000 ◽  
Vol 10 (1-3) ◽  
pp. 345-350 ◽  
Author(s):  
László Poppe ◽  
Harald Bothe ◽  
Gerd Bröker ◽  
Wolfgang Buckel ◽  
Erhard Stupperich ◽  
...  
Keyword(s):  
Binding Mode ◽  
Coenzyme B12 ◽  
Coenzyme Binding

scholarly journals Characterization of coenzyme binding and selectivity determinants in Mycobacterium tuberculosis flavoprotein reductase A: analysis of Arg199 and Arg200 mutants at the NADP(H) 2′-phosphate binding site

2008 ◽  
Vol 417 (1) ◽  
pp. 103-114 ◽  
Author(s):  
Muna Sabri ◽  
Adrian J. Dunford ◽  
Kirsty J. McLean ◽  
Rajasekhar Neeli ◽  
Nigel S. Scrutton ◽  
...  
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Substrate Inhibition ◽  
Reduction Rate ◽  
Binding Mode ◽  
Phosphate Binding ◽  
Ferricyanide Reduction ◽  
Coenzyme Specificity ◽  
Coenzyme Binding ◽  
Kd Values ◽  
Adrenodoxin Reductase

Mycobacterium tuberculosis FprA (flavoprotein reductase A) is an NAD(P)H- and FAD-binding reductase that is structurally/evolutionarily related to adrenodoxin reductase. Structural analysis implicates Arg199 and Arg200 in interactions with the NADP(H) 2′-phosphate group. R199A, R200A and R199A/R200A mutants were characterized to explore the roles of these basic residues. All mutations abolished neutral FAD semiquinone stabilization in the NADPH-reduced enzyme, owing to weakened NADPH affinity. Instead, FAD hydroquinone was formed in all mutants, and each displayed substantially enhanced autooxidation rates (20–40-fold) compared with NADPH-reduced WT (wild-type) FprA. Steady-state ferricyanide reduction studies revealed diminished NADPH affinity (higher Km values), but lower NADH Km values. Despite a lowered kcat, the R199A/R200A mutant exhibited a 200-fold coenzyme specificity switch towards NADH, although substrate inhibition was observed at high NADH concentrations (Ki=250 μM). Stopped-flow FAD reduction studies confirmed substantially increased NADPH Kd values, although the limiting flavin reduction rate constant was similar in all mutants. The R199A mutation abolished electron transfer between hydroquinone FprA and NADP+, while this reaction progressed (via an FADH2-NADP+ charge-transfer intermediate) for R200A FprA, albeit more slowly (klim=58.1 s−1 compared with >300 s−1) than in WT. All mutations caused positive shifts in FAD potential (∼40–65 mV). Binding of an NADPH analogue (tetrahydro-NADP) induced negative shifts in potential (∼30–40 mV) only for variants with the R200A mutation, indicating distinctive effects of Arg199/Arg200 on coenzyme binding mode and FAD potential. Collectively, these data reveal important roles for the phylogenetically conserved arginines in controlling FprA FAD environment, thermodynamics, coenzyme selectivity and reactivity.

scholarly journals The –SH Protection Method for Determining Accurate Kd Values for Enzyme-Coenzyme Complexes of NAD+-Dependent Glutamate Dehydrogenase and Engineered Mutants: Evidence for Nonproductive NADPH Complexes

2010 ◽  
Vol 2010 ◽  
pp. 1-5 ◽  
Author(s):  
Joanna Griffin ◽  
Paul C. Engel
Keyword(s):  
Glutamate Dehydrogenase ◽  
Binding Mode ◽  
Apparent Contradiction ◽  
Double Mutation ◽  
Coenzyme Binding ◽  
Protection Method ◽  
Kd Values ◽  
Activity Measurements ◽  
Nonproductive Binding

Inactivation rates have been measured for clostridial glutamate dehydrogenase and several engineered mutants at various DTNB concentrations. Analysis of rate constants allowed determination of Kd for each non-covalent enzyme-DTNB complex and the rate constant for reaction to form the inactive enzyme-thionitrobenzoate adduct. Both parameters are sensitive to the mutations F238S, P262S, the double mutation F238S/P262S, and D263K, all in the coenzyme binding site. Study of the effects of NAD+, NADH and NADPH at various concentrations in protecting against inactivation by 200 μM DTNB allowed determination of Kd values for binding of these coenzymes to each protein, yielding surprising results. The mutations were originally devised to lessen discrimination against the disfavoured coenzyme NADP(H), and activity measurements showed this was achieved. However, the Kd determinations indicated that, although Kd values for NAD+ and NADH were increased considerably, Kd for NADPH was increased even more than for NADH, so that discrimination against binding of NADPH was not decreased. This apparent contradiction can only be explained if NADPH has a nonproductive binding mode that is not weakened by the mutations, and a catalytically productive mode that, though strengthened, is masked by the nonproductive binding. Awareness of the latter is important in planning further mutagenesis.

Experimental validation of the predicted TGR5 binding mode model

2015 ◽  
Vol 53 (01) ◽  
Author(s):  
L Spomer ◽  
CGW Gertzen ◽  
D Häussinger ◽  
H Gohlke ◽  
V Keitel
Keyword(s):  
Experimental Validation ◽  
Binding Mode

Binding Modes of Ligands Using Enhanced Sampling (BLUES): Rapid Decorrelation of Ligand Binding Modes Using Nonequilibrium Candidate Monte Carlo

2017 ◽  
Author(s):  
Samuel Gill ◽  
Nathan M. Lim ◽  
Patrick Grinaway ◽  
Ariën S. Rustenburg ◽  
Josh Fass ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Ligand Binding ◽  
Binding Mode ◽  
Free Energy Calculations ◽  
Dynamics Simulation ◽  
Binding Modes ◽  
Enhanced Sampling ◽  
Recent Success ◽  
Multiple Binding ◽  
Proper Sampling

<div>Accurately predicting protein-ligand binding is a major goal in computational chemistry, but even the prediction of ligand binding modes in proteins poses major challenges. Here, we focus on solving the binding mode prediction problem for rigid fragments. That is, we focus on computing the dominant placement, conformation, and orientations of a relatively rigid, fragment-like ligand in a receptor, and the populations of the multiple binding modes which may be relevant. This problem is important in its own right, but is even more timely given the recent success of alchemical free energy calculations. Alchemical calculations are increasingly used to predict binding free energies of ligands to receptors. However, the accuracy of these calculations is dependent on proper sampling of the relevant ligand binding modes. Unfortunately, ligand binding modes may often be uncertain, hard to predict, and/or slow to interconvert on simulation timescales, so proper sampling with current techniques can require prohibitively long simulations. We need new methods which dramatically improve sampling of ligand binding modes. Here, we develop and apply a nonequilibrium candidate Monte Carlo (NCMC) method to improve sampling of ligand binding modes.</div><div><br></div><div>In this technique the ligand is rotated and subsequently allowed to relax in its new position through alchemical perturbation before accepting or rejecting the rotation and relaxation as a nonequilibrium Monte Carlo move. When applied to a T4 lysozyme model binding system, this NCMC method shows over two orders of magnitude improvement in binding mode sampling efficiency compared to a brute force molecular dynamics simulation. This is a first step towards applying this methodology to pharmaceutically relevant binding of fragments and, eventually, drug-like molecules. We are making this approach available via our new Binding Modes of Ligands using Enhanced Sampling (BLUES) package which is freely available on GitHub.</div>

Binding Modes of Ligands Using Enhanced Sampling (BLUES): Rapid Decorrelation of Ligand Binding Modes Using Nonequilibrium Candidate Monte Carlo

2018 ◽  
Author(s):  
Samuel Gill ◽  
Nathan M. Lim ◽  
Patrick Grinaway ◽  
Ariën S. Rustenburg ◽  
Josh Fass ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Ligand Binding ◽  
Binding Mode ◽  
Free Energy Calculations ◽  
Dynamics Simulation ◽  
Binding Modes ◽  
Enhanced Sampling ◽  
Recent Success ◽  
Multiple Binding ◽  
Proper Sampling

<div>Accurately predicting protein-ligand binding is a major goal in computational chemistry, but even the prediction of ligand binding modes in proteins poses major challenges. Here, we focus on solving the binding mode prediction problem for rigid fragments. That is, we focus on computing the dominant placement, conformation, and orientations of a relatively rigid, fragment-like ligand in a receptor, and the populations of the multiple binding modes which may be relevant. This problem is important in its own right, but is even more timely given the recent success of alchemical free energy calculations. Alchemical calculations are increasingly used to predict binding free energies of ligands to receptors. However, the accuracy of these calculations is dependent on proper sampling of the relevant ligand binding modes. Unfortunately, ligand binding modes may often be uncertain, hard to predict, and/or slow to interconvert on simulation timescales, so proper sampling with current techniques can require prohibitively long simulations. We need new methods which dramatically improve sampling of ligand binding modes. Here, we develop and apply a nonequilibrium candidate Monte Carlo (NCMC) method to improve sampling of ligand binding modes.</div><div><br></div><div>In this technique the ligand is rotated and subsequently allowed to relax in its new position through alchemical perturbation before accepting or rejecting the rotation and relaxation as a nonequilibrium Monte Carlo move. When applied to a T4 lysozyme model binding system, this NCMC method shows over two orders of magnitude improvement in binding mode sampling efficiency compared to a brute force molecular dynamics simulation. This is a first step towards applying this methodology to pharmaceutically relevant binding of fragments and, eventually, drug-like molecules. We are making this approach available via our new Binding Modes of Ligands using Enhanced Sampling (BLUES) package which is freely available on GitHub.</div>

D3R Grand Challenge 4: Ligand Similarity and MM-GBSA-Based Pose Prediction and Affinity Ranking for BACE-1 Inhibitors

2019 ◽  
Author(s):  
Sukanya Sasmal ◽  
Léa El Khoury ◽  
David Mobley
Keyword(s):  
Binding Mode ◽  
Energy Estimates ◽  
Poor Correlation ◽  
Grand Challenge ◽  
Pose Prediction ◽  
Design Data ◽  
Data Resource ◽  
Affinity Ranking ◽  
Ligand Similarity ◽  
Bace 1

The Drug Design Data Resource (D3R) Grand Challenges present an opportunity to assess, in the context of a blind predictive challenge, the accuracy and the limits of tools and methodologies designed to help guide pharmaceutical drug discovery projects. Here, we report the results of our participation in the D3R Grand Challenge 4, which focused on predicting the binding poses and affinity ranking for compounds targeting the beta-amyloid precursor protein (BACE-1). Our ligand similarity-based protocol using HYBRID (OpenEye Scientific Software) successfully identified poses close to the native binding mode for most of the ligands with less than 2 A RMSD accuracy. Furthermore, we compared the performance of our HYBRID-based approach to that of AutoDock Vina and Dock 6 and found that HYBRID performed better here for pose prediction. We also conducted end-point free energy estimates on protein-ligand complexes using molecular mechanics combined with generalized Born surface area method (MM-GBSA). We found that the binding affinity ranking based on MM-GBSA scores have poor correlation with the experimental values. Finally, the main lessons from our participation in D3R Grand Challenge 4 suggest that: i) the generation of the macrocycles conformers is a key step for successful pose prediction, ii) the protonation states of the BACE-1 binding site should be treated carefully, iii) the MM-GBSA method could not discriminate well between different predicted binding poses, and iv) the MM-GBSA method does not perform well at predicting protein-ligand binding affinities here.

Application of the ESMACS Binding Free Energy Protocol to a Highly Varied Ligand Dataset: Lactate Dehydogenase A

2019 ◽  
Author(s):  
David Wright ◽  
Fouad Husseini ◽  
Shunzhou Wan ◽  
Christophe Meyer ◽  
Herman Van Vlijmen ◽  
...  
Keyword(s):  
Free Energy ◽  
Surface Area ◽  
Binding Free Energy ◽  
Normal Mode Analysis ◽  
Binding Mode ◽  
Accessible Surface Area ◽  
Solvent Accessible Surface Area ◽  
Mode Analysis ◽  
Energy Calculation ◽  
Accessible Surface

<div>Here, we evaluate the performance of our range of ensemble simulation based binding free energy calculation protocols, called ESMACS (enhanced sampling of molecular dynamics with approximation of continuum solvent) for use in fragment based drug design scenarios. ESMACS is designed to generate reproducible binding affinity predictions from the widely used molecular mechanics Poisson-Boltzmann surface area (MMPBSA) approach. We study ligands designed to target two binding pockets in the lactate dehydogenase A target protein, which vary in size, charge and binding mode. When comparing to experimental results, we obtain excellent statistical rankings across this highly diverse set of ligands. In addition, we investigate three approaches to account for entropic contributions not captured by standard MMPBSA calculations: (1) normal mode analysis, (2) weighted solvent accessible surface area (WSAS) and (3) variational entropy. </div>

Ruthenium(II) Complexes Bearing Thioether-Appended α- Iminopyridine Ligands: Arene Precursors Permit Access to K2-N,N and K3-N,N,S Complexes

2019 ◽  
Author(s):  
Victoria A. Ternes ◽  
Hannah A. Morgan ◽  
Austin P. Lanquist ◽  
Michael P. Murray ◽  
Bradley Wile
Keyword(s):  
Crystal Structure ◽  
Solid State ◽  
Strong Field ◽  
Active Role ◽  
Binding Mode ◽  
Phenethyl Alcohol ◽  
Ru Complexes

Herein we report the preparation of a series of Ru(II) complexes featuring alpha-iminopyridine ligands bearing thioether functionality (NNS<sup>R</sup>, where R = Me, CH<sub>2</sub>Ph, Ph). Metallation using (<i>p</i> cymene)RuCl dimer permits access to (k<sup>2</sup>-N,N)Ru complexes in which the thioether moiety remains uncoordinated. In the presence of a strong field ligand such as acetonitrile or triphenylphosphine, the p-cymene moiety is displaced, and the ligand adopts a k<sup>3</sup>-N,N,S binding mode. These complexes are characterized using a combination of solution and solid state methods, including the crystal structure of [(NNS<sup>Me</sup>)Ru(NCMe)<sub>2</sub>Cl]Cl. The k<sup>2</sup>-N,N Ru(II) complexes are shown to serve as efficient precatalysts for the oxidation of sec-phenethyl alcohol at 5 mol% loadings, using a variety of external oxidants and solvents. The complex bearing an S-Ph donor was found to be the most active of those surveyed, suggesting that the thioether donor plays an active role in catalyst speciation for this transformation.

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