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National Center for Supercomputing Applications - Bulgaria
Supercomputing Applications in Life Science
Prof. Stoyan Markov
Dr. Peicho Petkov
Georgi Prangov
ISC’2013, Leipzig, 18 June 2013
Bulgaria – fact sheet
Population: 7 364 570
Area: 110,994 km2
Capital city: Sofia
Alphabet: Cyrillic
Language: Bulgarian
Religion: Eastern Orthodox Christianity
Gross Domestic Product/capita: $ 7,033
Internet Usage: 50.3%
Broadband access (households): 50.8%
Broadband access (companies): 76.2%
Blue Gene/P system and software enabling
Since Spring 2009 supporting for the application provisions and software enabling, preparation of training materials and organization of training events
35 software packages, including: GROMACS; NAMD; LAMMPS; CPMD; CP2K; NWChem; MMFF94; Quantum Espresso; GAMESS; DALTON; Qbox; DOCK 6.3; ROSETTA 3; SPECFEM3D; Computational Fluid Dynamics code Saturne/ Syrthes1.3.2; Aster; Code Salome; Salomé-Meca platform; PETSc-FEM, ELMER and other
In the last 4 years the users basis is 93 scientists, researchers and students
••• 5
The European HPC Ecosystem - PRACE
National Roadmap for Research
Infrastructures of the Republic of
Bulgaria (2010) – Scientific and
Technical Coordinator
Other partnering research teams from:
Institute of Information and
Communication Technology of BAS
Sofia University “St. Kliment
Ohridski”
Institute of Molecular Biology of
BAS
Technical University – Sofia
Medical University – Sofia
Other organizations
Industrial Collaborations
Working on specific tasks
with social and economic
impacts – life science and
medicine as well as
engineering
Working together with
companies on software
enabling and trainings;
Organizing industrial
seminars and conferences;
••• 7
Supporting in organizing HPC training for the
needs of Bulgarian science and education system
Meeting the needs of high tech sectors and
competitive economy
Providing novel courses and on-
demand HPC trainings
Working throughout education system –
from secondary to higher educations and
research institutions
HPC Trainings and Outreach
Cooperation in HPC
Cooperate in HPC development (Applications, Benchmarking and etc.)
Exchange of information on HPC policies and share best practices
Trainings and outreach
Enhance Cooperation
Engagement Applications Trainings Traditions New systems
- Empirical parameters
(pk)
2021 θθθ aa kv 202
1 rrkrv bb 0φφcos1φ nkv dd
k
kkN pxVxxxV ;,,, 21
Potential – force field
Parameterization of chemical bonds
6
6
12
12
ij
ij
ij
ij
r
C
r
C
ijlj rV ij
ji
r
ijc rV0πε4
Parameterization of the other interactions
- Empirical parameters
(pk)
k
kkN pxvxxxV ;,,, 21
Task 1: Potential – force field
AMBER, CHARMM, GROMOS, GROMACS, LAMMPS, NAMD, VMD
Calculation of Free energy
The free energy is the amount of energy in a system that
can be entirely transformed into work
In statistical mechanics:
Z is the ensemble partition function
The free energy provides full characterization of a
physical/chemical system and drives it from one state to
another, lower energy state
It determines the direction and the rate/speed of a
physical/chemical/biochemical process
ZTkF B ln
B
AB
Z
ZTkF ln
rUdrZ exp
N-terminus N-terminus
C-terminus
C-terminus
122-143
Active site
Res 18-26 Active site
Res 18-26
Task 1: Human Interferon Gamma
Task 1: What is our goal?
Aberrant IFNγ expression is associated with many
autoinflammatory and autoimmune diseases
The task is to find a possible way to inhibit its
activity by:
Blocking the binding sites of hIFNγ :
Find a ligand binding hIFNγ and blocking its activity
Blocking the binding receptors (hIFNγ Rα ) on the cell
surface:
With mutated hIFNγ proteins, lacking biological
activity
With some other ligand
IFNγ accomplishes its multiple
biological effects by activating
STAT transcription factors, which
are translocated to the nucleus
through a specific nuclear
localization sequence (NLS) in
the IFNγ molecule. Two putative
NLS have been pointed out in the
hIFNg, one of which is located in
helix E (residues 83-89).
These residues do not take part in the interaction between hIFNγ and its cell-surface receptor, but participate in inducing biological effect in the cell.
100 random mutations
Task 1: Mutation site – 87Lys-88Lys-89Lys
Task 1: Folding the С-termini with MD
• PBC • 100 х 120 х 130 Å3
• Explicit solvent • NVT , T=310K • dt = 2fs • PME • 200 ns
GROMACS 4.5.3 NAMD 2.9
GROMOS 53a6 CHARMM 22
Ribosome is a complex
molecular machine translated
the genetic code of its
provisional form - information
RNA to proteins that are key
building material for living cell
and are catalysts in the
metabolic pathways providing
the exchange of matter and
energy between living cell and
inanimate nature 1. Voet, D.;Voet, J.; Pratt, C, Biochemical Interactions, Wiley, 1999
Task 2: Ribosome – machine for proteins synthesis. Antibiotics Target
Task 2: Ribosome – X-ray structure without H-bonds and monomers
Ribosome from E. Coli PDB ID: 3FIK and 3FIH 152 250 heavy atoms
The ribosome is mainly composed of RNA chains leading to a huge amount of negatively charged phosphate groups in the PDB X-Ray Structures. In nature they are neutralized by Na+, Mg2+ ions and limited amount of positively charged amino acid residues incorporated in polypeptide chains.
Task 2: Ribosome – charges
Task 2: Ribosome studies
K. Y. Sanbonmatsu and C.-S. Tung1. Journal of Physics: Conference Series 46 (2006) 334–342
Los Alamos National Laboratory, MS K710, Los Alamos, New Mexico 87545,USA
Ions:
Placed randomly in a
box around the solute at
concentrations of 0.1 M
KCl and 7 mM MgCl2
Equilibrated with the
NAMD molecular dynamics
simulation code and AMBER
force field
Task 2: Ribosome – charges neutralisation
Two nearby Na+ ions are replace with a Mg2+.
Determining the position of the Na+ ions to phosphate groups
The Na+ ions located between the phosphate group and the negatively charged group of polypeptide chains (ASP, GLU) are replaced with Mg2+
ions.
Removing the Na+ ions near the positively charged groups of polypeptide chains (LYS, ARG)
Task 2: Molecular dynamics of the complete structure of the ribosome
0
1
2
3
4
5
6
0 2 4 6 8
t [ns]
RM
SD
[A
ng
]
8ns MD simulation of ribosome (water molecules are hidden for clarity)
Task 3: G protein-coupled receptors
G protein-coupled receptors (GPCRs) belong to a super family of cell
surface signaling proteins
GPCRs are expressed in every type of cell in the body where their function
is to transmit signals from outside the cell to signaling pathways within the
cell, result a profound effects between cells and between organ systems
There are over 375 non-chemosensory GPCRs encoded in the human
genome, of which 225 have known ligands and 150 are orphan targets
GPCRs are the site of action of 25-30% of currently approved drugs,
providing worldwide sales of over $20 billion
Task 3: Ligands binding to a specific G-receptor
Procedure for selection by Andrew Binkowski and Michael Kubal
Free Energy Perturbation computation -Grand Canonical Monte Carlo
GCCM
Typical Workload: Application Size: 7MB; Input data: 45MB; Output data: 10KB; Expected execution time: 5~5000 seconds; Parameter space: 1 billion tasks
2M+ ligands Protein x
target(s)
(Mike Kubal, Benoit Roux, and others)
Task 3: Identifying Potential Drug Targets
Thank you for your attention!
National Centre for Supercomputing Applications – Bulgaria
http://www.scc.acad.bg/ncsa/index.php/en/
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