Skip to content

Study and evaluation of the un/binding kinetics of Mineralocorticoid (MR) and a mutation (MR_S810L) receptor steroid agonist Aldosterone (Aldo), Cortisol (Col), and Progesterone (Str) ligands using Molecular Dynamics (MD) and Monte Carlo (MC) simulations, LiGaMD and LiBELa softwares respectively.

Notifications You must be signed in to change notification settings

saguileran/MD-SCPI

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Molecular Modeling and Simulation - Physics Institute of São Carlos (IPSC)

Table of Contents

Overview

Study and evaluation of the unbinding kinetics of Mineralocorticoid (MR and MR-S810L) receptor steroid agonist Cortisol (COL), Aldosterone (AS4), and Progesterone (STR) ligands using Molecular Dynamics (MD) and Monte Carlo (MC) simulations, LiGaMD and LiBELa softwares respectively.

Objectives

  • Prepare the input files: PDB and mol files of the Mineralocorticoid (MR) and MR mutation (S810L) ligands and the Aldosterone (AS4), Cortisol (COL), and Progestero (STR) proteins
  • Create the Molecular Dynamics (MD) simulations for the MR/MR_mut - aldosterone/cortisol/progesteron system
  • Create the Monte Carlo (MC) simulations for the MR aldosterone/cortisol/prgesteron systems
  • Contrast MD and MC simulations, does the MC simulation show the same behavior as MC?

Links of Interest

Reports made during the internship. Here you can find weekly updates and the final report with some conclusions.

Output Files

MR-AS4 MD simulation

Mineralocorticoid (MR) protein interaction with aldosteron (AS4) ligand

MR-COL MD simulation

Mineralocorticoid (MR) protein interaction with cortisol (COL) ligand

MD Energies

Total energies of the MR-AS4/COL systems

This image is obtained using the PlotEnergies.ipynb notebook that use jscatter pacakge to import dat files and matplotlib to plot.

MC Energies

Total energies of the MC-AS4 system

MC RMSD

RMSD as function of MC time steap of the MC-AS4 system

PyEMMA

States

States found in the MR-Aldo system using PyEMMA

States Examples

States examples of the MR-Aldo system

These image are obtained using the notebooks Plots_MC.ipynb, which use jscatter pacakge to import dat files and matplotlib to plot, and PyEMMA_AS4.ipynb, which uses PyEMMA to analyze the simulatiosn outputs.

Conclusions

  • LiGaMD is not eble to reproduce ligand un/binding events, while or nether LiGaMD2
  • LiBELa software is abel to emulate the ligand un/binding events when a high temperature is used, above of 5000K
  • Analyzing MC simulations with PyEMMA shows that in the tal sysmtem the ligand scape easier than in the other systems, talk also about mutations.

References

Proteins and Ligands

[1] Chantal Hellal-Levy, Jérôme Fagart, Anny Souque, and Marie-Edith Rafestin-Oblin. Mechanistic aspects of mineralocorticoid receptor activation. Kidney International, 57(4):1250–1255, 2000.

[2] Marie-Edith Rafestin-Oblin, Anny Souque, Brigitte Bocchi, Gregory Pinon, Jerome Fagart, and Alain Vandewalle. The Severe Form of Hypertension Caused by the Activating S810L Mutation in the Mineralocorticoid Receptor Is Cortisone related. Endocrinology, 144(2):528–533, 02 2003.

[3] David S. Geller, Anita Farhi, Nikki Pinkerton, Michael Fradley, Michael Moritz, Adrian Spitzer, Gretchen Meinke, Francis T. F. Tsai, Paul B. Sigler, and Richard P. Lifton. Activating mineralocorticoid receptor mutation in hypertension exacerbated by pregnancy. Science, 289(5476):119–123, 2000.

[4] Jérôme Fagart, Jessica Huyet, Grégory M. Pinon, Marina Rochel, Claudine Mayer, and Marie-Edith Rafestin-Oblin. Crystal structure of a mutant mineralocorticoid receptor responsible for hypertension. Nature Structural & Molecular Biology, 12(6):554–555, Jun 2005.

[5] John W. Funder. Aldosterone and mineralocorticoid receptors: Orphan questions. Kidney International, 57(4):1358–1363, 2000.

Software

[6] K. Belfon I.Y. Ben-Shalom J.T. Berryman S.R. Brozell D.S. Cerutti T.E. Cheatham III G.A. Cisneros V.W.D. Cruzeiro T.A. Darden R.E. Duke G. Giambasu M.K. Gilson H. Gohlke A.W. Goetz R. Harris S. Izadi S.A. Izmailov K. Kasavajhala M.C. Kaymak E. King A. Ko-valenko T. Kurtzman T.S. Lee S. LeGrand P. Li C. Lin J. Liu T. Luchko R. Luo M. Machado V. Man M. Manathunga K.M. Merz Y. Miao O. Mikhailovskii G. Monard H. Nguyen K.A. O’Hearn A. Onufriev F. Pan S. Pantano R. Qi A. Rahnamoun D.R. Roe A. Roitberg C. Sagui S. Schott-Verdugo A. Shajan J. Shen C.L. Simmerling N.R. Skrynnikov J. Smith J. Swails R.C. Walker J. Wang J. Wang H. Wei R.M. Wolf X. Wu Y. Xiong Y. Xue D.M. York S. Zhao D.A. Case, H.M. Aktulga and P.A. Kollman (2022). Amber 2022. University of California, San Francisco.

[7] Jinan Wang and Yinglong Miao. Ligand gaussian accelerated molecular dynamics 2 (ligamd2): Improved calculations of ligand binding thermodynamics and kinetics with closed protein pocket. Journal of Chemical Theory and Computation, 19(3):733–745, 2023. PMID: 36706316.

[8] Yinglong Miao, Apurba Bhattarai, and Jinan Wang. Ligand gaussian accelerated molecular dynamics (ligamd): Characterization of ligand binding thermodynamics and kinetics. Journal of Chemical Theory and Computation, 16(9):5526–5547, 2020. PMID: 32692556.

[9] Yinglong Miao, Apurba Bhattarai, and Jinan Wang. Ligand gaussian accelerated molecular dynamics (ligamd): Characterization of ligand binding thermodynamics and kinetics. bioRxiv, 2020.

[10] Heloisa dos Santos Muniz and Alessandro S. Nascimento. Ligand- and receptor-based docking with LiBELa. Journal of Computer-Aided Molecular Design, 29(8):713–723, Aug 2015.

[11] Pablo R. Arantes, Marcelo D. Polêto, Conrado Pedebos, and Rodrigo Ligabue-Braun. Making-it-rain: Cloud-based molecular simulations for everyone, August 2021.

[12] Matthew M. Copeland, Hung N. Do, Lane Votapka, Keya Joshi, Jinan Wang, Rommie E. Amaro, and Yinglong Miao. Gaussian Accelerated Molecular Dynamics in OpenMM. The Journal of Physical Chemistry B, 126(31):5810–5820, 2022. PMID: 35895977.

[13] Jinan Wang, Pablo R. Arantes, Apurba Bhattarai, Rohaine V. Hsu, Shristi Pawnikar, Yu-ming M. Huang, Giulia Palermo, and Yinglong Miao. Gaussian accelerated molecular dynamics: Principles and applications. WIREs Computational Molecular Science, 11(5):e1521, 2021.

[14] Geraldo Rodrigues Sartori and Alessandro S. Nascimento. Comparative Analysis of Electrostatic Models for Ligand Docking. Frontiers in Molecular Biosciences, 6, 2019.

[15] Heloisa S. Muniz and Alessandro S. Nascimento. Towards a critical evaluation of an empirical and volume-based solvation function for ligand docking. PLOS ONE, 12(3):1–19, 03 2017.

Theory

[16] Tamar Schlick. Molecular Modeling and Simulation: An Interdisciplinary Guide, volume 21 of Interdis- ciplinary Applied Mathematics. Springer New York, NY, Berlin, Heidelberg, 2 edition, August 2010.

[17] A.R. Leach. Molecular Modelling: Principles and Applications. Prentice Hall, 2 edition, 2001.

About

Study and evaluation of the un/binding kinetics of Mineralocorticoid (MR) and a mutation (MR_S810L) receptor steroid agonist Aldosterone (Aldo), Cortisol (Col), and Progesterone (Str) ligands using Molecular Dynamics (MD) and Monte Carlo (MC) simulations, LiGaMD and LiBELa softwares respectively.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages