Exploring the binding mode of PQ912 against secretory glutaminyl cyclase through systematic exploitation of conformational ensembles

2021 ◽  
Author(s):  
Remya Chandran ◽  
K.V. Dileep
Keyword(s):  
Binding Mode ◽  
Glutaminyl Cyclase ◽  
Conformational Ensembles

scholarly journals A Metadynamics-Based Protocol for the Determination of GPCR-Ligand Binding Modes

2019 ◽  
Vol 20 (8) ◽  
pp. 1970 ◽  
Author(s):  
Christian A. Söldner ◽  
Anselm H. C. Horn ◽  
Heinrich Sticht
Keyword(s):  
Ligand Binding ◽  
Pharmaceutical Research ◽  
Binding Mode ◽  
Model Systems ◽  
Binding Modes ◽  
Enhanced Sampling ◽  
Conformational Ensembles ◽  
Precise Knowledge ◽  
Preferential Binding ◽  
Dynamics Simulations

G protein-coupled receptors (GPCRs) are a main drug target and therefore a hot topic in pharmaceutical research. One important prerequisite to understand how a certain ligand affects a GPCR is precise knowledge about its binding mode and the specific underlying interactions. If no crystal structure of the respective complex is available, computational methods can be used to deduce the binding site. One of them are metadynamics simulations which have the advantage of an enhanced sampling compared to conventional molecular dynamics simulations. However, the enhanced sampling of higher-energy states hampers identification of the preferred binding mode. Here, we present a novel protocol based on clustering of multiple walker metadynamics simulations which allows identifying the preferential binding mode from such conformational ensembles. We tested this strategy for three different model systems namely the histamine H1 receptor in combination with its physiological ligand histamine, as well as the β 2 adrenoceptor with its agonist adrenaline and its antagonist alprenolol. For all three systems, the proposed protocol was able to reproduce the correct binding mode known from the literature suggesting that the approach can more generally be applied to the prediction of GPCR ligand binding in future.

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.

Association of multiple nucleotide variations in the pituitary glutaminyl cyclase gene QPC with low radial BMD in adult women.

2020 ◽  
Author(s):  
Lungwani Muungo
Keyword(s):  
Linkage Disequilibrium ◽  
Multiple Regression ◽  
Genetic Variations ◽  
Strong Linkage Disequilibrium ◽  
Adult Women ◽  
Nucleotide Polymorphisms ◽  
Haplotype Estimation ◽  
Factors Affecting ◽  
Glutaminyl Cyclase ◽  
Strong Linkage

Correlation between 13 genetic variations of the glutaminyl-peptide cyclotransferase gene andadjusted aBMD was tested among 384 adult women. Among 13 variations with strong linkage disequilibrium,R54W showed a prominent association (p ? 0.0003), which was more striking when examined among 309 eldersubjects (&gt;50 years; p ? 0.0001). Contribution for postmenopausal bone loss was suggested.Introduction: Alterations in homeostatic regulation of estrogen through the hypothalamus-pituitary-gonadal axis(HPG axis) importantly affect the pathogenesis of osteoporosis. Osteoporosis-susceptibility genes have beenproposed in this hormonal axis, such as estrogen receptor genes and the gonadotropin-releasing hormone gene(GnRH). Here we report another example of genes: glutaminyl-peptide cyclotransferase gene (QPCT), an essentialmodifier of pituitary peptide hormones, including GnRH.Materials and Methods: Analyses of association of 13 single nucleotide polymorphisms (SNPs) at the QPCT locuswith adjusted areal BMD (adj-aBMD) were carried out among 384 adult women. Linkage disequilibrium (LD) wasanalyzed by haplotype estimation and calculation of D? and r2. Multiple regression analysis was applied forevaluating the combined effects of the variations.Results and Conclusions: LD analysis indicated strong linkage disequilibrium within the entire 30-kb region of theQPCT gene. Significant correlations were observed between the genotypes of the six SNPs and the radial adj-aBMD,among which R54W (nt ? 160C?T) presented the most prominent association (p ? 0.0003). Striking associationwas observed for these SNPs among the 309 subjects ?50 years of age (R54W, p ? 0.0001; ?1095T?C, p ?0.0002; ?1844C?T, p ? 0.0002). Multiple regression analyses indicated that multiple SNPs in the gene might actin combination to determine the radial adj-aBMD. These results indicate that genetic variations in QPCT are theimportant factors affecting the BMD of adult women that contribute to susceptibility for osteoporosis. The datashould provide new insight into the etiology of the disease and may suggest a new target to be considered duringtreatment.J Bone Miner

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