scholarly journals Interaction of CheY with the C-Terminal Peptide of CheZ

2007 ◽  
Vol 190 (4) ◽  
pp. 1419-1428 ◽  
Author(s):  
Jayita Guhaniyogi ◽  
Ti Wu ◽  
Smita S. Patel ◽  
Ann M. Stock
Keyword(s):  
Response Regulator ◽  
State Level ◽  
Kinetic Studies ◽  
Fold Increase ◽  
Structural Data ◽  
Binding Mode ◽  
Binding Modes ◽  
Protein Interfaces ◽  
Recognition Elements ◽  
Primary Output

ABSTRACT Chemotaxis, a means for motile bacteria to sense the environment and achieve directed swimming, is controlled by flagellar rotation. The primary output of the chemotaxis machinery is the phosphorylated form of the response regulator CheY (P∼CheY). The steady-state level of P∼CheY dictates the direction of rotation of the flagellar motor. The chemotaxis signal in the form of P∼CheY is terminated by the phosphatase CheZ. Efficient dephosphorylation of CheY by CheZ requires two distinct protein-protein interfaces: one involving the strongly conserved C-terminal helix of CheZ (CheZC) tethering the two proteins together and the other constituting an active site for catalytic dephosphorylation. In a previous work (J. Guhaniyogi, V. L. Robinson, and A. M. Stock, J. Mol. Biol. 359:624-645, 2006), we presented high-resolution crystal structures of CheY in complex with the CheZC peptide that revealed alternate binding modes subject to the conformational state of CheY. In this study, we report biochemical and structural data that support the alternate-binding-mode hypothesis and identify key recognition elements in the CheY-CheZC interaction. In addition, we present kinetic studies of the CheZC-associated effect on CheY phosphorylation with its physiologically relevant phosphodonor, the histidine kinase CheA. Our results indicate mechanistic differences in phosphotransfer from the kinase CheA versus that from small-molecule phosphodonors, explaining a modest twofold increase of CheY phosphorylation with the former, observed in this study, relative to a 10-fold increase previously documented with the latter.

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>

scholarly journals Computational Investigations on the Binding Mode of Ligands for the Cannabinoid-Activated G Protein-Coupled Receptor GPR18

Biomolecules ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 686 ◽  
Author(s):  
Alexander Neumann ◽  
Viktor Engel ◽  
Andhika B. Mahardhika ◽  
Clara T. Schoeder ◽  
Vigneshwaran Namasivayam ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
G Protein ◽  
Phenyl Ring ◽  
Binding Mode ◽  
Dynamics Simulation ◽  
Simulation Studies ◽  
Binding Modes ◽  
G Protein Coupled Receptor ◽  
G Protein Coupled

GPR18 is an orphan G protein-coupled receptor (GPCR) expressed in cells of the immune system. It is activated by the cannabinoid receptor (CB) agonist ∆9-tetrahydrocannabinol (THC). Several further lipids have been proposed to act as GPR18 agonists, but these results still require unambiguous confirmation. In the present study, we constructed a homology model of the human GPR18 based on an ensemble of three GPCR crystal structures to investigate the binding modes of the agonist THC and the recently reported antagonists which feature an imidazothiazinone core to which a (substituted) phenyl ring is connected via a lipophilic linker. Docking and molecular dynamics simulation studies were performed. As a result, a hydrophobic binding pocket is predicted to accommodate the imidazothiazinone core, while the terminal phenyl ring projects towards an aromatic pocket. Hydrophobic interaction of Cys251 with substituents on the phenyl ring could explain the high potency of the most potent derivatives. Molecular dynamics simulation studies suggest that the binding of imidazothiazinone antagonists stabilizes transmembrane regions TM1, TM6 and TM7 of the receptor through a salt bridge between Asp118 and Lys133. The agonist THC is presumed to bind differently to GPR18 than to the distantly related CB receptors. This study provides insights into the binding mode of GPR18 agonists and antagonists which will facilitate future drug design for this promising potential drug target.

scholarly journals Definition of the Binding Architecture to a Target Promoter of HP1043, the Essential Master Regulator of Helicobacter pylori

2021 ◽  
Vol 22 (15) ◽  
pp. 7848
Author(s):  
Annamaria Zannoni ◽  
Simone Pelliciari ◽  
Francesco Musiani ◽  
Federica Chiappori ◽  
Davide Roncarati ◽  
...  
Keyword(s):  
Helicobacter Pylori ◽  
Response Regulator ◽  
Consensus Sequence ◽  
Binding Mode ◽  
In Vitro Transcription ◽  
Target Sequence ◽  
Computational Alanine Scanning ◽  
Definition Of ◽  
Target Promoter

HP1043 is an essential orphan response regulator of Helicobacter pylori orchestrating multiple crucial cellular processes. Classified as a member of the OmpR/PhoB family of two-component systems, HP1043 exhibits a highly degenerate receiver domain and evolved to function independently of phosphorylation. Here, we investigated the HP1043 binding mode to a target sequence in the hp1227 promoter (Php1227). Scanning mutagenesis of HP1043 DNA-binding domain and consensus sequence led to the identification of residues relevant for the interaction of the protein with a target DNA. These determinants were used as restraints to guide a data-driven protein-DNA docking. Results suggested that, differently from most other response regulators of the same family, HP1043 binds in a head-to-head conformation to the Php1227 target promoter. HP1043 interacts with DNA largely through charged residues and contacts with both major and minor grooves of the DNA are required for a stable binding. Computational alanine scanning on molecular dynamics trajectory was performed to corroborate our findings. Additionally, in vitro transcription assays confirmed that HP1043 positively stimulates the activity of RNA polymerase.

scholarly journals Identification of V6.51L as a selectivity hotspot in stereoselective A2B adenosine receptor antagonist recognition

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xuesong Wang ◽  
Willem Jespers ◽  
Rubén Prieto-Díaz ◽  
Maria Majellaro ◽  
Adriaan P. IJzerman ◽  
...  
Keyword(s):  
Radioligand Binding ◽  
Structural Data ◽  
Binding Mode ◽  
Selective Recognition ◽  
Chiral Hplc ◽  
Binding Assays ◽  
Structural Determinants ◽  
X Ray Crystallography ◽  
Adenosine Receptor Antagonist ◽  
Energy Perturbation

AbstractThe four adenosine receptors (ARs) A1AR, A2AAR, A2BAR, and A3AR are G protein-coupled receptors (GPCRs) for which an exceptional amount of experimental and structural data is available. Still, limited success has been achieved in getting new chemical modulators on the market. As such, there is a clear interest in the design of novel selective chemical entities for this family of receptors. In this work, we investigate the selective recognition of ISAM-140, a recently reported A2BAR reference antagonist. A combination of semipreparative chiral HPLC, circular dichroism and X-ray crystallography was used to separate and unequivocally assign the configuration of each enantiomer. Subsequently affinity evaluation for both A2A and A2B receptors demonstrate the stereospecific and selective recognition of (S)-ISAM140 to the A2BAR. The molecular modeling suggested that the structural determinants of this selectivity profile would be residue V2506.51 in A2BAR, which is a leucine in all other ARs including the closely related A2AAR. This was herein confirmed by radioligand binding assays and rigorous free energy perturbation (FEP) calculations performed on the L249V6.51 mutant A2AAR receptor. Taken together, this study provides further insights in the binding mode of these A2BAR antagonists, paving the way for future ligand optimization.

scholarly journals Spanning the gap: unraveling RSC dynamics in vivo

2021 ◽  
Author(s):  
Heinz Neumann ◽  
Bryan J. Wilkins
Keyword(s):  
Cell Cycle ◽  
Posttranslational Modifications ◽  
Transcriptional Activation ◽  
Binding Mode ◽  
Binding Modes ◽  
Binding Domains ◽  
Binding Interface ◽  
The Many ◽  
And Function

AbstractMultiple reports over the past 2 years have provided the first complete structural analyses for the essential yeast chromatin remodeler, RSC, providing elaborate molecular details for its engagement with the nucleosome. However, there still remain gaps in resolution, particularly within the many RSC subunits that harbor histone binding domains.Solving contacts at these interfaces is crucial because they are regulated by posttranslational modifications that control remodeler binding modes and function. Modifications are dynamic in nature often corresponding to transcriptional activation states and cell cycle stage, highlighting not only a need for enriched spatial resolution but also temporal understanding of remodeler engagement with the nucleosome. Our recent work sheds light on some of those gaps by exploring the binding interface between the RSC catalytic motor protein, Sth1, and the nucleosome, in the living nucleus. Using genetically encoded photo-activatable amino acids incorporated into histones of living yeast we are able to monitor the nucleosomal binding of RSC, emphasizing the regulatory roles of histone modifications in a spatiotemporal manner. We observe that RSC prefers to bind H2B SUMOylated nucleosomes in vivo and interacts with neighboring nucleosomes via H3K14ac. Additionally, we establish that RSC is constitutively bound to the nucleosome and is not ejected during mitotic chromatin compaction but alters its binding mode as it progresses through the cell cycle. Our data offer a renewed perspective on RSC mechanics under true physiological conditions.

scholarly journals A Structural Overview of Vascular Endothelial Growth Factors Pharmacological Ligands: From Macromolecules to Designed Peptidomimetics

Molecules ◽  
2021 ◽  
Vol 26 (22) ◽  
pp. 6759
Author(s):  
Xiaoqing Ye ◽  
Jean-François Gaucher ◽  
Michel Vidal ◽  
Sylvain Broussy
Keyword(s):  
Growth Factors ◽  
Growth Factor ◽  
Unnatural Amino Acids ◽  
Structural Data ◽  
Age Related Macular Degeneration ◽  
Vascular Endothelial ◽  
Binding Modes ◽  
Therapeutic Applications ◽  
X Ray Crystallography ◽  
Age Related

The vascular endothelial growth factor (VEGF) family of cytokines plays a key role in vasculogenesis, angiogenesis, and lymphangiogenesis. VEGF-A is the main member of this family, alongside placental growth factor (PlGF), VEGF-B/C/D in mammals, and VEGF-E/F in other organisms. To study the activities of these growth factors under physiological and pathological conditions, resulting in therapeutic applications in cancer and age-related macular degeneration, blocking ligands have been developed. These have mostly been large biomolecules like antibodies. Ligands with high affinities, at least in the nanomolar range, and accurate structural data from X-ray crystallography and NMR spectroscopy have been described. They constitute the main focus of this overview, which evidences similarities and differences in their binding modes. For VEGF-A ligands, and to a limited extent also for PlGF, a transition is now observed towards developing smaller ligands like nanobodies and peptides. These include unnatural amino acids and chemical modifications for designed and improved properties, such as serum stability and greater affinity. However, this review also highlights the scarcity of such small molecular entities and the striking lack of small organic molecule ligands. It also shows the gap between the rather large array of ligands targeting VEGF-A and the general absence of ligands binding other VEGF members, besides some antibodies. Future developments in these directions are expected in the upcoming years, and the study of these growth factors and their promising therapeutic applications will be welcomed.

scholarly journals SuCOS is Better than RMSD for Evaluating Fragment Elaboration and Docking Poses

2019 ◽  
Author(s):  
Susan Leung ◽  
Michael Bodkin ◽  
Frank von Delft ◽  
Paul Brennan ◽  
Garrett Morris
Keyword(s):  
Binding Mode ◽  
Docking Studies ◽  
Binding Modes ◽  
False Negatives ◽  
Ligand Interaction ◽  
Cross Docking ◽  
Protein Ligand Interaction ◽  
Feature Overlap ◽  
Better Than ◽  
Fragment Based Drug Discovery

One of the fundamental assumptions of fragment-based drug discovery is that the fragment’s binding mode will be conserved upon elaboration into larger compounds. The most common way of quantifying binding mode similarity is Root Mean Square Deviation (RMSD), but Protein Ligand Interaction Fingerprint (PLIF) similarity and shape-based metrics are sometimes used. We introduce SuCOS, an open-source shape and chemical feature overlap metric. We explore the strengths and weaknesses of RMSD, PLIF similarity, and SuCOS on a dataset of X-ray crystal structures of paired elaborated larger and smaller molecules bound to the same protein. Our redocking and cross-docking studies show that SuCOS is superior to RMSD and PLIF similarity. When redocking, SuCOS produces fewer false positives and false negatives than RMSD and PLIF similarity; and in cross-docking, SuCOS is better at differentiating experimentally-observed binding modes of an elaborated molecule given the pose of its non-elaborated counterpart. Finally we show that SuCOS performs better than AutoDock Vina at differentiating actives from decoy ligands using the DUD-E dataset. SuCOS is available at https://github.com/susanhleung/SuCOS . <br>

scholarly journals Dissimilar Ligands Bind in a Similar Fashion: A Guide to Ligand Binding-Mode Prediction with Application to CELPP Studies

2021 ◽  
Vol 22 (22) ◽  
pp. 12320
Author(s):  
Xianjin Xu ◽  
Xiaoqin Zou
Keyword(s):  
Molecular Similarity ◽  
Complex Structure ◽  
Binding Mode ◽  
Molecular Structures ◽  
Complex Structures ◽  
Binding Modes ◽  
Ligand Complex ◽  
Systematic Analysis ◽  
Binding Mode Prediction ◽  
Similarity Principle

The molecular similarity principle has achieved great successes in the field of drug design/discovery. Existing studies have focused on similar ligands, while the behaviors of dissimilar ligands remain unknown. In this study, we developed an intercomparison strategy in order to compare the binding modes of ligands with different molecular structures. A systematic analysis of a newly constructed protein–ligand complex structure dataset showed that ligands with similar structures tended to share a similar binding mode, which is consistent with the Molecular Similarity Principle. More importantly, the results revealed that dissimilar ligands can also bind in a similar fashion. This finding may open another avenue for drug discovery. Furthermore, a template-guiding method was introduced for predicting protein–ligand complex structures. With the use of dissimilar ligands as templates, our method significantly outperformed the traditional molecular docking methods. The newly developed template-guiding method was further applied to recent CELPP studies.

scholarly journals SuCOS is Better than RMSD for Evaluating Fragment Elaboration and Docking Poses

2019 ◽  
Author(s):  
Susan Leung ◽  
Michael Bodkin ◽  
Frank von Delft ◽  
Paul Brennan ◽  
Garrett Morris
Keyword(s):  
Binding Mode ◽  
Docking Studies ◽  
Binding Modes ◽  
False Negatives ◽  
Ligand Interaction ◽  
Cross Docking ◽  
Protein Ligand Interaction ◽  
Feature Overlap ◽  
Better Than ◽  
Fragment Based Drug Discovery

One of the fundamental assumptions of fragment-based drug discovery is that the fragment’s binding mode will be conserved upon elaboration into larger compounds. The most common way of quantifying binding mode similarity is Root Mean Square Deviation (RMSD), but Protein Ligand Interaction Fingerprint (PLIF) similarity and shape-based metrics are sometimes used. We introduce SuCOS, an open-source shape and chemical feature overlap metric. We explore the strengths and weaknesses of RMSD, PLIF similarity, and SuCOS on a dataset of X-ray crystal structures of paired elaborated larger and smaller molecules bound to the same protein. Our redocking and cross-docking studies show that SuCOS is superior to RMSD and PLIF similarity. When redocking, SuCOS produces fewer false positives and false negatives than RMSD and PLIF similarity; and in cross-docking, SuCOS is better at differentiating experimentally-observed binding modes of an elaborated molecule given the pose of its non-elaborated counterpart. Finally we show that SuCOS performs better than AutoDock Vina at differentiating actives from decoy ligands using the DUD-E dataset. SuCOS is available at https://github.com/susanhleung/SuCOS . <br>

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