1 / 23

A Technical Introduction to the MD-OPEP Simulation Tools

A Technical Introduction to the MD-OPEP Simulation Tools. Jessica Nasica Universit é de Montr é al Montr éal, Québec, Canada. Outline. Overview of the simulation method Why use “simulator”? The OPEP force-field Running the simulation: what you need to get started

dianne
Download Presentation

A Technical Introduction to the MD-OPEP Simulation Tools

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. A Technical Introduction to the MD-OPEP Simulation Tools Jessica Nasica Université de Montréal Montréal, Québec, Canada

  2. Outline • Overview of the simulation method • Why use “simulator”? • The OPEP force-field • Running the simulation: what you need to get started • The simulation step by step • The output of the “simulator” • The analysis tools • The PTWHAM analysis • The RMSD analysis • Secondary structure tools • Contacts tools • Clustering tools • Graphical tools and various useful scripts

  3. The simulation method • REMD simulation ( Replica Exchange Molecular Dynamics ) • A simplified coarse-grained potential: OPEP

  4. Why use “simulator”? • It can be used: • To study aggregation processes • To check for the stability of a particular molecular assembly • The simplified force-field allows to reach bigger time scales more efficiently: • To study long-range proteins motions • To extract accurate thermodynamics properties P. Derreumaux, N. Mousseau – J. Chem. Phys. 126, 025101 (2007)

  5. The OPEP force-field OPEP = Optimized Potential for Efficient structure Prediction • Reduced-protein model: • A 6-particle model with a detailed representation of the backbone (except for Proline) • Each side chain is represented as one particle and defined by one centroid • Implicit solvent solvent effects included in the interaction parameters Maupetit et al. - Proteins 2007; 69:394-408 / Chebaro et al. – J. Phys. Chem. B 2008

  6. The OPEP force-field • OPEP energy function: • Local Forces: Includes changes in bond lengths and valence angles for all particles and changes in improper torsions of the side chains. • Nonbonded Forces: Van der Waals, electric and hydrophobic forces  short- and long- range interactions are computed separately. Use of a pairwise contact potential between side chains represented either by a 12-6 potential or by a 6-potential. • Hydrogen-bonding Forces: 2 terms  2-body H-bonds  4-body effects = cooperative energies between H-bonds Maupetit et al. - Proteins 2007; 69:394-408 /Chebaro et al. – J. Phys. Chem. B 2008

  7. Running the “simulator” • What you need to get started: • The executable file after compilation of the code • The parameter file ‘simulator.sh’ • Your ‘.pdb’ file in an OPEP format • The corresponding topology file (.top), residue description file (.list) and ‘ichain.dat’ file • The ‘cutoff.dat’ and ‘scale.dat’ files • A link file and a qsub script

  8. The simulation step by step • Step 1:Minimization: finding a stable starting point It makes sure that the structure’s energy is minimized using ART. At the saddle point: • The 2 phases of ART: • Activation phase the structure is pushed towards a saddle point • Relaxation phase the structure is pushed slightly over the saddle point and relaxed to a new local energy minimum • Mousseau et al. – Frontiers in Bioscience 13 - 2008; 4495-4516

  9. The simulation step by step • Step 1:Minimization: the output The minimized configuration is written in the file “relaxed_conformation.pdb”. The data resulting from each minimization step is written in “log.file”: Total Energy . towards a minimum Net Force to 0 Decrease in potential energy term Velocity Decrease in kinetic energy term Rmsd value Structure is undergoing a configurational change

  10. The simulation step by step • Step 2: Thermalization: It thermalizes the configurations by heating up by stages until it reaches the target temperature. Here, in “simulator.sh”: E = T = -98.5290 0.00 K E1 = -93.859 T1 = 59.25 K E2 = -94.2221 T2 = 88.88 K E3 = -72.7113 T3 = 133.32 K E4 = 25.8615 T4 = 199.98 K E5 = 103.8417 T5 = 299.97 K Initial conformation Relaxedconformation (from minimization step) Thermalization conformations 1  5 Energies are in Kcal/mol

  11. The simulation step by step • Step 3: MD  calculation of forces: using the velocity-Verlet algorithm for integrating Newton’s equation of motion for each particle: where, the force on particle i. (Highly simplified description of MD)

  12. The simulation step by step • Step 4: Writing of the .pdb files: At each desired time step, the new configuration is written in the “min” files for each temperature.

  13. Output files The configurations are sorted by temperature.

  14. Analysis tools

  15. The PTWHAM tool • Allows a temporal correlation in the data, using autocorrelation analysis, to compute equilibrium averages.  we can derive thermodynamical properties, including data from each temperature.

  16. The PTWHAM tool • How to use it: • ./ptwham_first will read data in each pXX/min file, calculate the Rg, rmsd and end-to-end distance, and output files simXX.txt, wham_parameters.dat, beta.dat • edit wham_parameters.dat • ./ptwham_second mintime maxtime writes “averages.txt” containing U (total energy), rmsd, Cv, end-to-end distance, writes “free_energies.txt” containing Uk (average energy per replica), free energy and entropy and writes “deviations.txt” containing all the uncertainties on the above observables.

  17. The PTWHAM tool • The output: Using 2 python scripts, we obtain the following plots:

  18. The RMSD tool • Calculates the rms distance between 2 configurations or between 1 configuration and a list of configurations taking into account their individual clusters for more accuracy. • Recognizes clusters from hydrogen bonds formed using the DSSP definition of a hydrogen bond: the DSSP algorithm identifies a H-bond if E<-0.5 Kcal/mol. • The program searches all the peptides forming H-bonds and rearranges the pdb file accounting for the chain order in the clusters formed. How to use it: rmsd conf1.pdb list It needs “ichain.dat”.

  19. The RMSD tool The output files are : • rmsd.txt  containing all the rmsd values for each configuration in the list • id_order.txt containing all the clusters formed for each configuration in the list • parallel_planes.txt containing a list of all the clusters being parallel to each other

  20. The Replicas tool • A python script that generates a graph showing acceptance probability for replica exchange. • Need “log.file” and “replicas.dat”

  21. Additional useful scripts • Pymol scripts allowing to prepare the pdb files and make movies out of the configurations  unique_pymol command: unique_pymol file skip • Python scripts: • extract_confs extracts a subset of configurations from a single file containing a list of configurations. • repair_min repairs min files that are broken by a crash, removing all the incorrect lines. • Graphics scripts: • trace_averages.py ( WHAM analysis ) command: ./trace_averages.py “averages.txt” “title” “1” • trace_freeenergies.py ( WHAM analysis ) command: ./trace_freeenergies.py “free_energies.txt” “title” “1”

  22. Where to find our packages? You will find an updated version of the analysis tools on the wiki:http://riel.pmc.umontreal.ca/groups/biophysique/

  23. Thank you !

More Related