Simulation Environment for Life Sciences @ BSC

Objective: Overview of simulation technologies used in Life Sciences and their specific adaptation to HPC environment.

Zoom link: https://us06web.zoom.us/j/86855207021?pwd=dTBwT21tamZTR2dwdjBxWEkvanNRdz09

Agenda

13 March 14 March
09.00 - 10.30 Welcome & Introduction (JLG) 09.00 - 10.30  Simulation DBs and simulation data management (DB)
10.30 - 11.00  Break 10.30 - 11.00  Break
11.00 - 11.45  Atomistic MD Algorithm (JLG) 11.00 - 11.45 Machine Learning MD applications (MW)
11.45 - 12.30  Algorithm improvements & HPC (JLG) 11.45 - 12.30  Application Examples (MW)
12.30 - 14.00   Break 12.30 - 14.00  Break
14.00 - 15.15  Simulation Setup (FB) 14.00 - 15.00  Trajectory visualization (AH)
15.15 - 15.30   Setup and Analysis Hands On (Installation) (AH) 15.00 - 16.00  Trajectory analysis (AH)
15.30 - 16.00  Break 16.00 - 16.30  Break
16.00 - 18.00  Setup and Analysis Hands On (AH) 16.30 - 18.00  Q&A session and Survey

JLG: Josep Ll. Gelpi (BSC - UB), MW: Miłosz Wieczór (IRB), FB: Federica Battistini (IRB - UB), AH: Adam Hospital (IRB), BD: Daniel Beltran (IRB)

Software to be installed locally

  • Linux (any distribution):
    • Download and Install: Anaconda package manager
    • Clone repository: git clone https://github.com/bioexcel/biobb_wf_md_setup.git
    • Change to the directory: cd biobb_wf_md_setup
    • Install the environment: conda env create -f conda_env/environment.yml
    • Activate environment: conda activate biobb_GMX_MDsetup_tutorial
    • Enable extension: jupyter nbextension enable python-markdown/main
    • Enable extension: jupyter-nbextension enable --py --user widgetsnbextension
    • Enable extension: jupyter-nbextension enable --py --user nglview
    • Run Jupyter Notebook: jupyter-notebook biobb_wf_md_setup/notebooks/biobb_MDsetup_tutorial.ipynb
    • Install VMD: conda install -c conda-forge vmd

  • MacOS:
    • Download and Install: Anaconda package manager
    • Clone repository: git clone https://github.com/bioexcel/biobb_wf_md_setup.git
    • Change to the directory: cd biobb_wf_md_setup
    • Install the environment: conda env create -f conda_env/environment.yml
    • Activate environment: conda activate biobb_GMX_MDsetup_tutorial
    • Enable extension: jupyter nbextension enable python-markdown/main
    • Enable extension: jupyter-nbextension enable --py --user widgetsnbextension
    • Enable extension: jupyter-nbextension enable --py --user nglview
    • Run Jupyter Notebook: jupyter-notebook biobb_wf_md_setup/notebooks/biobb_MDsetup_tutorial.ipynb
    • Download and Install: VMD

Selected references & URLs

General Review

Hospital, A, Battistini, F, Soliva, R, Gelpí, JL, Orozco, M. Surviving the deluge of biosimulation data. WIREs Comput Mol Sci. 2020; e1449. https://doi.org/10.1002/wcms.1449

Hospital, Adam, Goñi Josep Ramon, Orozco Modesto, and Gelpí Josep-Lluis. Molecular dynamics simulations: advances and applications. Adv Appl Bioinform Chem 2015, 10:37-47.

Orozco M, Orellana L, Hospital A, Naganathan AN, Emperador A, Carrillo O, Gelpi JL. Coarse-grained representation of protein flexibility. Foundations, successes, and shortcomings. Adv Protein Chem Struct Biol 2011, 85:183-215.

Orozco M, Luque FJ. Theoretical Methods for the Description of the Solvent Effect in Biomolecular Systems. Chem Rev 2000, 100:4187-4226.

Larsson P, Hess B, Lindahl E. Algorithm improvements for molecular dynamics simulations. Wiley Interdisciplinary Reviews-Computational Molecular Science 2010, 1:93-108.

Buch I, Harvey MJ, Giorgino T, Anderson DP, De Fabritiis G. High-throughput all-atom molecular dynamics simulations using distributed computing. J Chem Inf Model 2010, 50:397-403.

Hospital, A, Gelpi, J.L. High-throughput molecular dynamics simulations. Toward a dynamic PDB. WIRE 2013 (Early view) DOI: 10.1002/wcms.1142

Force-fields

Mackerell AD, Wiorkiewiczkuczera J, Karplus M. An all-atom empirical energy function for the simulation of nucleic-acids. Journal of the American Chemical Society 1995, 117:11946-11975.

MacKerell AD, Bashford D, Bellott M, Dunbrack RL, Evanseck JD, Field MJ, Fischer S, Gao J, Guo H, Ha S, et al. All-atom empirical potential for molecular modeling and dynamics studies of proteins. Journal of Physical Chemistry B 1998, 102:3586-3616.

Cornell WD, Cieplak P, Bayly CI, Gould IR, Merz KM, Ferguson DM, Spellmeyer DC, Fox T, Caldwell JW, Kollman PA. A 2nd generation force-field for the simulation of proteins, nucleic-acids, and organic-molecules. Journal of the American Chemical Society 1995, 117:5179-5197

Kaminski GA, Friesner RA, Tirado-Rives J, Jorgensen WL. Evaluation and reparametrization of the OPLS-AA force field for proteins via comparison with accurate quantum chemical calculations on peptides. Journal of Physical Chemistry B 2001, 105:6474-6487

MD Codes and helper applications

ACEMD & ACEMDtk
Harvey M, Giupponi G, De Fabritiis G. ACEMD: Accelerated molecular dynamics simulations in the microseconds timescale. J. Chem. Theory and Comput 2009, 5.
multiscalelab.org/acemd            

AMBER & AMBERTOOLS
Case DA, Darden TA, Cheatham I, T.E., Simmerling CL, Wang J, Duke RE, Luo R, Walker RC, Zhang W, Merz KM, et al. AMBER 12. University of California, San Francisco. 2012
ambermd.org

CHARMM
Brooks BR, Brooks CL, 3rd, Mackerell AD, Jr., Nilsson L, Petrella RJ, Roux B, Won Y, Archontis G, Bartels C, Boresch S, et al. CHARMM: the biomolecular simulation program. J Comput Chem 2009, 30:1545-1614.
www.charmm.org

GROMACS
Hess B, Kutzner C, van der Spoel D, Lindahl E. GROMACS 4: Algorithms for highly efficient, load-balanced, and scalable molecular simulation. Journal of Chemical Theory and Computation 2008, 4:435-447.
www.gromacs.org

Andrio, P., Hospital, A., Conejero, J. et al. BioExcel Building Blocks, a software library for interoperable biomolecular simulation workflows. Sci Data 6, 169 (2019). https://doi.org/10.1038/s41597-019-0177-4

Hospital A, Andrio P, Fenollosa C, Cicin-Sain D, Orozco M, Gelpi JL. MDWeb and MDMoby: an integrated web-based platform for molecular dynamics simulations. Bioinformatics 2012, 28:1278-1279.
mmb.irbbarcelona.org/MDWeb

NAMD
Nelson MT, Humphrey W, Gursoy A, Dalke A, Kale LV, Skeel RD, Schulten K. NAMD: A parallel, object oriented molecular dynamics program. International Journal of Supercomputer Applications and High Performance Computing 1996, 10:251-268.
www.ks.uiuc.edu/Research/namd

Trajectory Databases

Hospital, Adam, Andrio Pau, Cugnasco Cesare, Codó Laia, Becerra Yolanda, Dans Pablo D., Battistini Federica, Torres Jordi, Goni Ramon, Orozco Modesto, et al. BIGNASim: a NoSQL database structure and analysis portal for nucleic acids simulation data. Nucleic Acids Res 2016, 44:D272-8.

Rueda M, Ferrer-Costa C, Meyer T, Perez A, Camps J, Hospital A, Gelpi JL, Orozco M. A consensus view of protein dynamics. Proc Natl Acad Sci U S A 2007, 104:796-801.

Simms AM, Toofanny RD, Kehl C, Benson NC, Daggett V. Dynameomics: design of a computational lab workflow and scientific data repository for protein simulations. Protein Eng Des Sel 2008, 21:369-377.
www.dynameomics.org

Meyer T, D'Abramo M, Hospital A, Rueda M, Ferrer-Costa C, Perez A, Carrillo O, Camps J, Fenollosa C, Repchevsky D, et al. MoDEL (Molecular Dynamics Extended Library): a database of atomistic molecular dynamics trajectories. Structure 2010, 18:1399-1409.
mmb.irbbarcelona.org/MoDEL

Analysis tools

Camps J, Carrillo O, Emperador A, Orellana L, Hospital A, Rueda M, Cicin-Sain D, D'Abramo M, Gelpi JL, Orozco M. FlexServ: an integrated tool for the analysis of protein flexibility. Bioinformatics 2009, 25:1709-1710
mmb.irbbarcelona.org/FlexServ

PCAsuite. Compression based on Essential dynamics
Meyer T, Ferrer-Costa C, Perez A, Rueda M, Bidon-Chanal A, Luque FJ, Laughton CA, Orozco M. Essential dynamics: A tool for efficient trajectory compression and management. Journal of Chemical Theory and Computation 2006, 2:251-258
mmb.irbbarcelona.org/software/pcasuite/pcasuite.html