1. Co-ordination & Harmonisation of Advanced e-Infrastructures for Research and Education Data Sharing Research Infrastructures – Proposal n. 306819 Gromacs & Plantisc Searching for uses cases, improvements and realization of portlets

2. Team  Marco Rinaldi  Livio Saluci  Alessandro Brischetto  Valeria Di Mauro  Rossella Biondi  Anastasia Scandurra

3. Outline  Gromacs  Searching for use cases to facilitate demo on the Science Gateway  Improvements of the existing portlet on Science Gateway  Plantisc  Creation of the portlet for the Science Gateway

4. Co-ordination & Harmonisation of Advanced e-Infrastructures for Research and Education Data Sharing Research Infrastructures – Proposal n. 306819 GROMACS GROningen MAchine for Chemical Simulations

5. Application description  GROMACS is a versatile package to perform molecular dynamics, i.e. simulate the Newtonian equations of motion for systems with hundreds to millions of particles.  It is primarily designed for biochemical molecules like proteins, lipids and nucleic acids that have a lot of complicated bonded interactions, but since GROMACS is extremely fast at calculating the non-bonded interactions (that usually dominate simulations) many groups are also using it for research on non-biological systems, e.g. polymers.

6. Use cases  We tried a lot of use cases to find the most interesting for a portlet example execution http://www.bevanlab.biochem.vt.edu/Pages/Personal/justin/gmx-tutorials/

7. Integration strategy  mdrun is the main command of the AutoDock portfolio. It begins the basic molecular dynamics calculus after all the other parameters have been set.  GRID infrastructure is perfect for the execution of a mdrun command line:.TPR FILE SG GRID.EDR FILE Input file generated by user with GROMACS that contains a description of the system Execute the mdrun, a time consuming operation Output file that can be used to generate an xvg (plottable file)

8. Orchestration of SG comp. + ext. components  We improved the SG portlet with a new pilot script capable to automatically generate also the xvg and a jpg plot of the output result  to do the jpg plot we integrated octave SG GRID.EDR FILE.XVG.JPG PLOT TYPE.TPR FILE

9. Orchestration of SG comp. + ext. components.TPR.EDR mdrun g_energy OCTAVE SCIENCE GATEWAY.XVG PLOT TYPE.JPG

10. Execution workflow  Example of TPR generation:  Download the 1AKI.pdb from http://www.rcsb.org/pdb/home/home.dohttp://www.rcsb.org/pdb/home/home.do  pdb2gmx -f 1AKI.pdb -o 1AKI_processed.gro -water spce  editconf -f 1AKI_processed.gro -o 1AKI_newbox.gro -c -d 1.0 -bt cubic  genbox -cp 1AKI_newbox.gro -cs spc216.gro -o 1AKI_solv.gro -p topol.top  http://www.bevanlab.biochem.vt.edu/Pages/Personal/justin/gmx- tutorials/lysozyme/Files/ions.mdp http://www.bevanlab.biochem.vt.edu/Pages/Personal/justin/gmx- tutorials/lysozyme/Files/ions.mdp  grompp -f ions.mdp -c 1AKI_solv.gro -p topol.top -o ions.tpr  genion -s ions.tpr -o 1AKI_solv_ions.gro -p topol.top -pname NA - nname CL -nn 8  http://www.bevanlab.biochem.vt.edu/Pages/Personal/justin/gmx- tutorials/lysozyme/Files/minim.mdp http://www.bevanlab.biochem.vt.edu/Pages/Personal/justin/gmx- tutorials/lysozyme/Files/minim.mdp  grompp -f minim.mdp -c 1AKI_solv_ions.gro -p topol.top -o em.tpr

11. Execution workflow  Example of TPR upload:.TPR FILE PLOT TYPE

12. Execution workflow  Example of Gromacs mdrun result:.EDR.XVG.JPG energy minimization

13. Execution workflow  Other TPR elaborations results available from our use cases: densitypressuretemperature

14. Remaining problems  Necessary portlet modifications:  Add into UI the possibility to select the plot type (integer number) and save this information into a g_energy_input.txt file that is used by the new pilot script  Possible portlet improvements:  The generation of the TPR file must be done by the user, so he must have GROMACS installed on his machine. Add the possibility to build a TPR file inserting all the possible parameters directly on the portlet.

15. Summary and conclusion  The creation of TRP files it’s a critical part of the GROMACS workflow.  We created some TPR sample files to help people to try the GROMACS portlet and verify the functionalities (http://www.bevanlab.biochem.vt.edu/Pages/Personal/ju stin/gmx-tutorials/)http://www.bevanlab.biochem.vt.edu/Pages/Personal/ju stin/gmx-tutorials/  We suggest the implementation of TPR creation into the portlet, although it’s not easy because exists a large variety of parameters combinations.

16. Co-ordination & Harmonisation of Advanced e-Infrastructures for Research and Education Data Sharing Research Infrastructures – Proposal n. 306819 PLANTICS Plant TIssue Culture Simulation

17. Application description  Plant Tissue culture is a method for plant propagation under in vitro conditions  Different types and parts of plants (known as explants) may be cultivated in vitro. These may be organs (roots, stems, shoot tips, leaves and fruits); tissues; cells (suspension cultures) and special tissues and organs such as embryos, canthers, pollen and protoplasts  Plant tissue culture is time and material intensive, running into several months of laboratory efforts in trying to build hormonal combinations that will be best for mass propagation of a particular species

18. Application description  Potentially, modeling or computer simulation can provide a useful method for gaining insight into these complex processes by reducing the time needed to screen numerous hormonal combinations.  Plantisc is a simulation application based on multiple regression models deployed on a grid computing infrastructure  The application simulates the plant tissue culture experiments and predicts the amount and combinations of auxins and cytokinins needed to yield optimal growth of propagules  The results obtained from the simulation show over 67% prediction accuracy as compared to the laboratory experiments

19. Integration strategy  Plantics is written in Pyton, using libraries like NumPy and SciPy.  The GRID infrastructure is perfect for the execution of a time consuming computation.

20. Orchestration of SG comp. + ext. comp.  Single job using parameters selected from the portlet web interface INPUT PARAMS SG GRID OUTPUT FILE Execute the plantics computation ??

21. Orchestration of SG comp. + ext. comp.  Multi job using files uploaded by the user  we used the parametric parallel because different inputs can be executed with the same PLANTICS software and final ouputs can be compared to find the best combination of auxins and cytokinins INPUT FILE SG GRID OUTPUT FILE Execute the plantics computation ?? INPUT FILE OUTPUT FILE

22. Execution workflow  Single job

23. Execution workflow  Multi-job

24. Remaining problems  We created the portlet UI and managed the form input commands  Next steps:  Install Python on the SG machines  Install Plantics on the SG machines  Run Plantics from the portlet

25. Summary and conclusion  The Plantics portlet will be completed when the command line execution instruction will be available.  The Plantics portlet, divided into two execution mode, will be very useful to do a single test o compare a large number of tests.

26. Co-ordination & Harmonisation of Advanced e-Infrastructures for Research and Education Data Sharing Research Infrastructures – Proposal n. 306819 Questions ?