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121 results for “Allosterism”
Supplemental Information - Allosteric activation of the co-receptor BAK1 by the EFR receptor kinase initiates immune signaling
<p>This folder contains</p> <p>1) maps of plasmids</p> <p>2) files of phylogenetic analysis </p> <p>3) Replication information</p> <p>4) Image cropping information</p> <p>5) Gene IDs and protein sequences</p> <p>that are part of the manuscript "Allosteric activation of the co-receptor BAK1 by the EFR receptor kinase initiates immune signaling"</p>
Intermolecular interactions in G protein-coupled receptor allosteric sites at the membrane interface from molecular dynamics simulations and quantum chemical calculations
<p>Allosteric modulators are called to be promising candidates in G protein-coupled receptor (GPCR) drug development by displaying target selectivity and fewer side effects. Among the allosteric sites known to date, extrahelical cavities represent an uncharacteristic binding location that raises many questions about the ligand interactions and stability; the binding site structure, and how all of these are affected by lipid molecules. In this work, we analyze the dynamics and interactions in the PAR2, C5aR1, and GCGR receptors unbound and bound to allosteric modulators at the receptor-lipid interface using molecular dynamics simulations in three lipid compositions. In addition, we performed quantum chemical calculations to further explore electrostatic interactions and the strength of atom pairwise contacts in the stabilization of the ligand-receptor complexes. We show that besides classical hydrogen bonds weak polar interactions such as O-HC, O-Br, and S-HC contacts and aromatic interactions contribute to the binding of allosteric modulators at the extrahelical sites in the middle of the membrane. The allosteric cavities are open and detectable in various membrane compositions but not always predicted as druggable. The availability of polar atoms for interactions in such cavities can be assessed by water molecules from the simulations. Although ligand-lipid interactions are weak, the lipid tails play a role in sizing and shaping the large part of the allosteric cavity. </p> <p>You will find the following files:</p> <ul> <li>Input files of the equilibration and production protocols of MD simulations (MD_simulations_inputs.zip)</li> <li>Input files and coordinate files of F-SAPT and NCIPLOT calculations (quantum_chemical_coordiates_inputs.zip)</li> </ul>
Ternary π–π Stacking Complexes by Allosteric Regulation in Multilayer Nanographenes
<p>Additional data to report <a href="https://doi.org/10.1021/jacs.4c11119">https://doi.org/10.1021/jacs.4c11119</a>:</p> <p>Construction of π–π stacking supramolecular complexes with more than two components is challenging due to the weak and directionless nature of dispersion interactions. Here we report ternary complexes of a ditopic nanographene tetraimide (<strong>1</strong>), α-substituted phthalocyanine (<strong>Pc</strong>) and polyaromatic hydrocarbons (PAHs) in solution and crystalline state via allosteric regulation. Binding of one <strong>Pc</strong> give rise to significant distortion and conformational changes in <strong>1</strong> that in turn lead to the inhibition of the second binding of <strong>Pc</strong>. The conformational changes associated with first binding allowed an allosteric binding of a third component (PAHs) to form ternary complexes in solution. <sup>1</sup>H NMR titration revealed a moderately high thermodynamic stability for the ternary complexes in CDCl<sub>3</sub>. Competition between allosterically regulated ternary complexes ([<strong>Pc·1</strong>·PAH]) and 1:2 stoichiometric binary complexes of <strong>1</strong> with PAHs ([PAH·<strong>1</strong>·PAH]) were elucidated. Further, selective formation of ternary complexes in solution led to the generation of ternary cocrystals from a 1:1:1 mixture of three components in solution. Our work shows that large π-conjugated nanographenes designed with allosteric recognition sites allow the construction of multilayer ternary complexes in solution and solid-state even with dispersive π–π interactions.</p>
Dataset for FigS2F in "DNA is the allosteric driver for the asymmetric binding of homodimer estrogen-related receptor"
<p><strong>Abstract</strong></p> <p>The estrogen-related receptors (ERRs, NR3B), orphan members of the steroid hormone receptor (SR) subfamily (NR3), are crucial for the transcriptional control of cellular energy metabolism. As basal members of NR3 subfamily, the ERRs are key elements for the understanding of how the binding of SRs to DNA evolved from monomeric to dimeric palindromic binding sites. To unravel the initial steps of DNA selection by SRs, we combined structural, biophysical and phylogenetic studies. Our results unveil the molecular mechanisms of the ERR dimerization which are imprinted in the protein itself with DNA acting as an allosteric driver by allowing the formation of a novel extended asymmetric dimerization region (KR-box). Phylogenetic analyses suggest that the dimerization asymmetry used by ERRs is an ancestral feature necessary for establishing a strong overall dimerization interface, which was progressively lost in the course evolution by other SRs.</p> <p><strong>Methods</strong></p> <p>Ancestral character reconstruction and stochastic mapping were performed under R version 4.1.2 using the make.simmap function as implemented in the phytools package version 1.0-1. Character evolution was inferred using a model of symmetrical transition rates between the character states (SYM). 10 000 character histories were sampled to allow the incorporation of the uncertainty associated with the transition between different states. Inferred state frequencies for ancestral nodes were plotted using the describe.simmap function.</p> <p><strong>Usage Notes</strong></p> <p>This dataset contains all the files necessary to reproduce Figure S2 of the associated paper (Patel et al., in preparation). Those files are:</p> <p>- script_FigS2F.R : the R script necessary to load the data and process them as indicated in the methods section. The outputs of character mappings are also indicated in the script file, in order that the user can compare them with the results he would get on his/her own computer.</p> <p>- tree_FigS2F.nex: the backbone tree used for character mapping</p> <p>- FigS2F_KR_box.csv: the data table containing the presence-absence data regarding the KR box motif for each nuclear receptor.</p>
Dataset for identification of peptidomimetics and FDA approved drugs binding to novel allosteric pocket of the IRE1 RNase domain.
<p>Input files, protein-peptide and ligand docking datasets, and simulation trajectories, compressed in "rar" format. All calculations performed using the Schrödinger 2020-2 / 2020-3 software (modules Glide, Phase, Desmond). </p> <p>SI includes folders:</p> <p>1- "Peptide" folder contains the best peptide "Docking" complexes and "Pharmacophore" models </p> <p>2-"Quercitrin" folder contains the molecular "Docking", "MMGBSA" calculations, and "MD" simulation</p> <p>3-"Pemetrexed" folder contains the molecular "Docking", "MMGBSA" calculations, and "MD" simulation</p> <p> </p>
Allosteric Modulation of YAP/TAZ-TEAD Interaction by Palmitoylation and Small Molecule Inhibitors
<p>The tar file contains 3 directories, each of which contains all of the simulation input files (pdb, prmtop, inpcrd) and trajectory files (nc) for the simulations run. </p><ol><li>TEAD_Only: Simulations of the TEAD protein in the apo, inhibitor(inh)-bound, palmitate(plt)-bound, or palmitic acid(plm)-bound form </li><li>YAP-TEAD: Simulations of the YAP-TEAD heterodimer in the apo, inhibitor(inh)-bound, palmitate(plt)-bound, or palmitic acid(plm)-bound form </li><li>TAZ-TEAD: Simulations of the TAZ-TEAD heterodimer in the apo, inhibitor(inh)-bound, palmitate(plt)-bound, or palmitic acid(plm)-bound form </li></ol>
Neural relational inference to learn long-range allosteric interactions in proteins from molecular dynamics simulations
<p>MD simulations used in the studies of the publication "<strong>Neural relational inference to learn long-range allosteric interactions in proteins from molecular dynamics simulations</strong>"</p>
Source data for the kinetic assays in publication "Deciphering the allosteric regulation of mycobacterial inosine-5′-monophosphate dehydrogenase"
<p>Datasets of enzyme kinetics related to the publication "Deciphering the allosteric regulation of mycobacterial inosine-5′-monophosphate dehydrogenase", published in <em>Nature Communications</em> with DOI: https://doi.org/10.1038/s41467-024-50933-6 </p> <p>Individual files contain raw kinetic reaction data of the mycobacterial IMPDHs (wild type and mutant forms <em>Mycobacterium smegmatis</em> or wild type <em>Mycobacterium tuberculosis</em>) as a function of IMP, NAD+, GTP, ATP, ppGpp and Mg2+ concentration.</p> <p>Individual data sets are presented as time data points of the absorbance at 340 nm in an Excel file with a linked Graphpad graphical link. Detailed experimental conditions are available in the related publication.</p>
Source data for the HDX-MS experiments in publication "Deciphering the allosteric regulation of mycobacterial inosine-5′-monophosphate dehydrogenase"
<p>Dataset of HDX-MS experiments related to the publication "Deciphering the allosteric regulation of mycobacterial inosine-5′-monophosphate dehydrogenase", published in Nature Communications with DOI: https://doi.org/10.1038/s41467-024-50933-6 </p> <p>The differential HDX-MS experiments compare the apo and ligand-bound states of IMPDH from Mycobacterium smegmatis.</p> <p>A description of the dataset is provided in the attached README file: IMPDH_HDX-MS_README.txt.</p> <p>Detailed experimental conditions are available in the related publication.</p>
Supplementary data and code to "Known allosteric proteins have central roles in genetic disease" by G. Abrusan, D. Ascher and M. Inouye, PLOS Computational Biology 18(2):e1009806.
<p>Scripts and data to reproduce the figures and supplementary figures of "G. Abrusan, D. Ascher and M. Inouye (2022) Known allosteric proteins have central roles in genetic disease." PLOS Computational Biology 18(2):e1009806. https://doi.org/10.1371/journal.pcbi.1009806.</p>
Data from: Biochemical, structural and dynamical characterizations of the lactate dehydrogenase from Selenomonas ruminantium provide information about an intermediate evolutionary step prior to complete allosteric regulation acquisition in the super family of lactate and malate dehydrogenases.
<p>This data accompanies the paper entitled <strong><em>Biochemical, structural and dynamical characterizations of the lactate dehydrogenase from Selenomonas ruminantium provide information about an intermediate evolutionary step prior to complete allosteric regulation acquisition in the super family of lactate and malate dehydrogenases.</em></strong></p> <p>The zip archive contains the results of molecular dynamics simulations of the 2 systems investigated in the paper: <em>S. rum</em> and <em>T. mar</em> LDHs. The systems have been simulated at 315 K for <em>S. rum </em>and 340 K for <em>T. mar</em>. Final configurations of the proteins after productions are provided for all the systems in GRO Gromos87 format. Trajectories with the positions of the proteins every 100 ps are provided for all the systems in XTC gromacs format.</p>
Receptor cavity-based screening reveals potential allosteric modulators of gonadotropin receptors in carp (Cyprinus carpio)
<p>The datasets include input files used for docking including the receptor models, docking grids and and ligand databases consisting of prepared ligand used in screening of potential allosteric modulators for carp FSHR and LHR. the original dataset were sourced from The compound libraries from <a href="https://enamine.net/compound-libraries">https://enamine.net/compound-libraries</a> and are free to access, downloaded and used as per the mentioned sites terms and conditions. The ligand Database given here are constructed and processed using the Phase module (Phase, Schrödinger, LLC, New York, NY, 2021.). The dataset also includes .pdb files of the docked ligands. </p>
Allosteric kinase inhibitors
<p>The deposition contains 262 allosteric human protein kinase inhibitors for which X-ray structures of kinase-inhibitor complexes are available.</p> <p>The deposition updates allosteric kinase inhibitors available in <a href="https://doi.org/10.5281/zenodo.4436775">https://doi.org/10.5281/zenodo.4436775</a>.</p>
Illuminating the mechanism and allosteric behavior of NanoLuc luciferase
<p>NanoLuc, a superior β-barrel fold luciferase, was engineered 10 years ago but the nature of its catalysis<br> remains puzzling. Here experimental and computational techniques were combined, revealing that<br> imidazopyrazinone luciferins bind to an intra-barrel catalytic site but also to an allosteric site shaped on<br> the enzyme surface. Binding to the allosteric site prevents simultaneous binding to the catalytic site, and<br> vice versa, through concerted conformational changes. We demonstrate that restructuration of the<br> allosteric site can boost the luminescent reaction in the remote active site. Mechanistically, an intra-barrel<br> arginine coordinates the imidazopyrazinone component of luciferin which then react with O 2 via a radical<br> charge-transfer mechanism, and it also protonates the resulting excited amide product to form a light-<br> emitting neutral species. Concomitantly, an aspartate, supported by two tyrosines, is fine-tuning the blue<br> color emitter to secure a high emission intensity. This information is critical to engineering the next-<br> generation of ultrasensitive bioluminescent reporters.</p>
In silico data for: Folding correctors can restore CFTR post-translational folding landscape by allosteric domain-domain coupling
<p>Directory layout and description for deposited data, scripts, and results associated with</p> <p><strong>Folding correctors can restore CFTR post-translational folding landscape by allosteric domain-domain coupling</strong></p> <p>Naoto Soya, Haijin Xu, Ariel Roldan, Zhengrong Yang, Haoxin Ye, Fan Jiang, Aiswarya Premchandar, Guido Veit, Susan P.C. Cole, John Kappes, Tamas Hegedus, and Gergely L. Lukacs</p> <p> </p> <p>Two files are provided:</p> <ol> <li><strong>soya_md_trajectories.tar</strong> - This file contains the trajectories merged from the last part (450-500 ns) of the parallel simulations: md_450000_500000.xtc</li> <li><strong>soya_insilico_data.zip</strong> - This file contains all other deposited files including input data, scripts, results files.<br> The content of this file can be found below:</li> </ol> <p><strong>README.md </strong>- the content of this description</p> <p><strong>homo - Homology modeling</strong></p> <ul> <li>run*.py, myloopmodel.py, and mymodel.py files are separated for technical reasons, for running model-building in parallel mode</li> <li><strong>cftr-loop</strong> - Demonstrates the removal of the RI and seeling the break with loopmodeling</li> <li><strong>mrp1</strong> - Scripts and input files for human MRP1 homology modeling; the large unresolved loop in NBD1 was not modeled but sealed for MD; this required renumbering of the ouput</li> <li><strong>mrp6</strong> - Scripts, input, and output files for human MRP1 homology modeling; output: mrp6_human_closed.pdb; the selected CFTR and MRP1 models were the input for MD simulaitons; to see these energy minimized structures, please see the corresponding 'md' directory below.</li> </ul> <p><strong>md - Moldecular dynamics</strong></p> <ul> <li>The <strong>md_system_info.xlsx</strong> file contains the basic properties of simulation boxes</li> <li>MD parameter files: step6*.mdp for minimization and equilibration; step7_production.mdp for production run</li> <li>wordom.dat is the wordom configuration file</li> <li>cmap_mda.mp.py is a script for contact map calculation</li> <li><strong>cftr-*, mrp1-*</strong> <ul> <li>the simulation system generated by CHARMM-GUI: step5_charmm2gmx.pdb</li> <li>the output gro file of parallel simulations (the last state of the sysmtems): md_[1-6].gro</li> <li>! the trajectory merged from the last part (450-500 ns) of the parallel simulations: trajectories md_450000_500000.xtc are in a separte file (soya_md_trajectories.tar) with the same directory structure</li> <li>the merged trajectory contains only the SOLU; the corresponding structure file: prot.pdb</li> <li>index.ndx</li> </ul> </li> </ul> <p><strong>figures</strong></p> <ul> <li><strong>figure-3a</strong> <ul> <li>pdb files are the output of gmx rmsf</li> <li>pse file is saved visualization of the pdb files for PyMOL<br> </li> </ul> </li> <li><strong>figure-3c-s4b</strong> <ul> <li>You can run color_all.tcl in VMD to reproduce the network communities in structural context; this is dependent on the .pdb and .vmd files also deposited in this directory</li> <li>Network community members (residues) are listed in the Word files</li> <li>dri in file names and in scripts refers to 6ss<br> </li> </ul> </li> <li><strong>figure-s3a</strong> <ul> <li>tmd1_structures.pse contains the structures for PyMOL</li> <li>Please see the Source Data file for plotting RMSF</li> <li>Contact map data are in the tmd1_wt.npy and tmd1_r170g.npy file<br> </li> </ul> </li> <li><strong>figure-s3e</strong> <ul> <li>PyMOL pse files to visualise the dynamics of NBD1/2 structures<br> </li> </ul> </li> <li><strong>figure-s4a</strong> <ul> <li>Contains the calculated betweenness.txt files</li> <li>betweenness_plots.py for plotting</li> <li>wt_prot.pdb: required for plotting with resi thick-labels<br> </li> </ul> </li> <li><strong>figure-s5c</strong> <ul> <li>PyMOL pse files to visualise the dynamics of NBD1/2 structures<br> </li> </ul> </li> <li><strong>figure-s8d</strong> <ul> <li>Data for MRP1/ABCC1</li> <li>You can run color_all.tcl in VMD to reproduce the network communities in structural context; this is dependent on the .pdb and .vmd files also deposited in this directory</li> <li>Network community members (residues) are listed in the Word files</li> </ul> </li> </ul>
Molecular dynamics results of the complex 3CLpro allosteric groove with compound 5
<p>Molecular dynamics results of the complex 3CLpro allosteric groove with compound <strong>5</strong>. The protein structure is shown in gray and the compound <strong>5</strong> is shown in magenta.</p>
Data from: Myristoyl's dual role in allosterically regulating and localizing Abl kinase
<p>c-Abl kinase, a key signalling hub in many biological processes ranging from cell development to proliferation, is tightly regulated by two inhibitory Src homology domains. An N-terminal myristoyl-modification can bind to a hydrophobic pocket in the kinase C-lobe, which stabilizes the auto-inhibitory assembly. Activation is triggered by myristoyl release. We used molecular dynamics simulations to show how both myristoyl and the Src homology domains are required to impose the full inhibitory effect on the kinase domain, and reveal the allosteric transmission pathway at residue-level resolution. Importantly, we find myristoyl insertion into a membrane to thermodynamically compete with binding to c-Abl. Myristoyl thus not only localizes the protein to the cellular membrane, but membrane attachment at the same time enhances activation of c-Abl by stabilizing its pre-activated state. Our data put forward a model in which lipidation tightly couples kinase localization and regulation, a scheme that currently appears to be unique for this non-receptor tyrosine kinase.</p>
Proteolytic cleavage of Arabidopsis thaliana phosphoenolpyruvate carboxykinase-1 modifies its allosteric regulation
<p>Phospho<i>enol</i>pyruvate carboxykinase (PEPCK) plays a crucial role in gluconeogenesis. In this work, we analyze the proteolysis of <i>Arabidopsis thaliana</i> PEPCK1 (<i>Ath</i>PEPCK1) in germinating seedlings. We found that the amount of <i>Ath</i>PEPCK1 protein peaks at 24-48 hours post-imbibition. Concomitantly, we observed shorter versions of <i>Ath</i>PEPCK1, putatively generated by metacaspase-9 (<i>Ath</i>MC9). To study the impact of <i>Ath</i>MC9 cleavage on the kinetic and regulatory properties of <i>Ath</i>PEPCK1, we produced truncated mutants based on the reported <i>Ath</i>MC9 cleavage sites. The Δ19 and Δ101 truncated mutants of <i>Ath</i>PEPCK1 showed similar kinetic parameters and the same quaternary structure than the WT. However, activation by malate and inhibition by glucose 6-phosphate were abolished in the Δ101 mutant. We propose that proteolysis of <i>Ath</i>PEPCK1 in germinating seedlings operates as a mechanism to adapt the sensitivity to allosteric regulation during the sink-to-source transition.</p>
Supplemental Data for "Plus and minus ends of microtubule respond asymmetrically to kinesin binding by a long range directionally driven allosteric mechanism"
<p>This is raw data set associated with all the figures in the article "Plus and minus ends of microtubule respond asymmetrically to kinesin binding by a long range directionally driven allosteric mechanism" published in Science Advances by Huong T Vu, Zhechun Zhang, Riina Tehver and D. Thirumalai. </p>
Data from: Protein Conformational Space at the Edge of Allostery: Turning a Non-allosteric Malate Dehydrogenase into an "Allosterized" Enzyme using Evolution Guided Punctual Mutations
<p>This data accompanies the paper entitled <em>Protein Conformational Space at the Edge of Allostery: Turning a Non-allosteric Malate Dehydrogenase into an “Allosterized” Enzyme using Evolution Guided Punctual Mutations</em></p> <p>The zip archive contains the results of molecular dynamics simulations of the 4 systems investigated in the paper: wt of A. ful MalDH and three mutants. Each system has been simulated at two temperatures, 300 K and 340 K. Starting configurations of the proteins after equilibration are provided for all the systems in GRO Gromos87 format. Trajectories with the positions of the proteins every 100 ps are provided for all the systems in XTC gromacs format.</p>
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