Literature DB >> 28355542

Exploring Binding Mechanisms in Nuclear Hormone Receptors by Monte Carlo and X-ray-derived Motions.

Christoph Grebner1, Daniel Lecina2, Victor Gil2, Johan Ulander3, Pia Hansson4, Anita Dellsen4, Christian Tyrchan5, Karl Edman6, Anders Hogner3, Victor Guallar7.   

Abstract

In this study, we performed an extensive exploration of the ligand entry mechanism for members of the steroid nuclear hormone receptor family (androgen receptor, estrogen receptor α, glucocorticoid receptor, mineralocorticoid receptor, and progesterone receptor) and their endogenous ligands. The exploration revealed a shared entry path through the helix 3, 7, and 11 regions. Examination of the x-ray structures of the receptor-ligand complexes further showed two distinct folds of the helix 6-7 region, classified as "open" and "closed", which could potentially affect ligand binding. To improve sampling of the helix 6-7 loop, we incorporated motion modes based on principal component analysis of existing crystal structures of the receptors and applied them to the protein-ligand sampling. A detailed comparison with the anisotropic network model (an elastic network model) highlights the importance of flexibility in the entrance region. While the binding (interaction) energy of individual simulations can be used to score different ligands, extensive sampling further allows us to predict absolute binding free energies and analyze reaction kinetics using Markov state models and Perron-cluster cluster analysis, respectively. The predicted relative binding free energies for three ligands binding to the progesterone receptor are in very good agreement with experimental results and the Perron-cluster cluster analysis highlighted the importance of a peripheral binding site. Our analysis revealed that the flexibility of the helix 3, 7, and 11 regions represents the most important factor for ligand binding. Furthermore, the hydrophobicity of the ligand influences the transition between the peripheral and the active binding site.
Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

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Year:  2017        PMID: 28355542      PMCID: PMC5375144          DOI: 10.1016/j.bpj.2017.02.004

Source DB:  PubMed          Journal:  Biophys J        ISSN: 0006-3495            Impact factor:   4.033


  37 in total

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Journal:  J Chem Theory Comput       Date:  2012-06-18       Impact factor: 6.006

2.  Simulating Large-Scale Conformational Changes of Proteins by Accelerating Collective Motions Obtained from Principal Component Analysis.

Authors:  Junhui Peng; Zhiyong Zhang
Journal:  J Chem Theory Comput       Date:  2014-08-12       Impact factor: 6.006

3.  Monte Carlo Free Ligand Diffusion with Markov State Model Analysis and Absolute Binding Free Energy Calculations.

Authors:  Ryoji Takahashi; Víctor A Gil; Victor Guallar
Journal:  J Chem Theory Comput       Date:  2013-12-19       Impact factor: 6.006

4.  PELE:  Protein Energy Landscape Exploration. A Novel Monte Carlo Based Technique.

Authors:  Kenneth W Borrelli; Andreas Vitalis; Raul Alcantara; Victor Guallar
Journal:  J Chem Theory Comput       Date:  2005-11       Impact factor: 6.006

5.  The intrinsic dynamics of enzymes plays a dominant role in determining the structural changes induced upon inhibitor binding.

Authors:  Ahmet Bakan; Ivet Bahar
Journal:  Proc Natl Acad Sci U S A       Date:  2009-08-17       Impact factor: 11.205

6.  Unveiling prolyl oligopeptidase ligand migration by comprehensive computational techniques.

Authors:  Martin Kotev; Daniel Lecina; Teresa Tarragó; Ernest Giralt; Víctor Guallar
Journal:  Biophys J       Date:  2015-01-06       Impact factor: 4.033

Review 7.  Everything you wanted to know about Markov State Models but were afraid to ask.

Authors:  Vijay S Pande; Kyle Beauchamp; Gregory R Bowman
Journal:  Methods       Date:  2010-06-04       Impact factor: 3.608

Review 8.  Nuclear hormone receptor signals as new therapeutic targets for urothelial carcinoma.

Authors:  H Miyamoto; Y Zheng; K Izumi
Journal:  Curr Cancer Drug Targets       Date:  2012-01       Impact factor: 3.428

9.  Allosteric changes in protein structure computed by a simple mechanical model: hemoglobin T<-->R2 transition.

Authors:  Chunyan Xu; Dror Tobi; I Bahar
Journal:  J Mol Biol       Date:  2003-10-10       Impact factor: 5.469

10.  Research resource: nuclear hormone receptor expression in the endocrine pancreas.

Authors:  Jen-Chieh Chuang; Ji-Young Cha; James C Garmey; Raghavendra G Mirmira; Joyce J Repa
Journal:  Mol Endocrinol       Date:  2008-07-31
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  5 in total

1.  Δ9 -Tetrahydrocannabinolic acid alleviates collagen-induced arthritis: Role of PPARγ and CB1 receptors.

Authors:  Belén Palomares; Martín Garrido-Rodriguez; Claudia Gonzalo-Consuegra; María Gómez-Cañas; Suwipa Saen-Oon; Robert Soliva; Juan A Collado; Javier Fernández-Ruiz; Gaetano Morello; Marco A Calzado; Giovanni Appendino; Eduardo Muñoz
Journal:  Br J Pharmacol       Date:  2020-07-08       Impact factor: 8.739

2.  Structural mechanism underlying ligand binding and activation of PPARγ.

Authors:  Jinsai Shang; Douglas J Kojetin
Journal:  Structure       Date:  2021-03-12       Impact factor: 5.871

3.  Adaptive simulations, towards interactive protein-ligand modeling.

Authors:  Daniel Lecina; Joan F Gilabert; Victor Guallar
Journal:  Sci Rep       Date:  2017-08-16       Impact factor: 4.379

4.  Monte Carlo simulations using PELE to identify a protein-protein inhibitor binding site and pose.

Authors:  Lucía Díaz; Daniel Soler; Gary Tresadern; Christophe Buyck; Laura Perez-Benito; Suwipa Saen-Oon; Victor Guallar; Robert Soliva
Journal:  RSC Adv       Date:  2020-02-17       Impact factor: 3.361

5.  Atomistic simulations shed new light on the activation mechanisms of RORγ and classify it as Type III nuclear hormone receptor regarding ligand-binding paths.

Authors:  Suwipa Saen-Oon; Estrella Lozoya; Victor Segarra; Victor Guallar; Robert Soliva
Journal:  Sci Rep       Date:  2019-11-21       Impact factor: 4.379

  5 in total

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