Transcript PyMOL: Opinions & Experiences

Issues Surrounding the Use of
Open-Source PyMOL to
Visualize Large Complexes
Warren L. DeLano, Ph.D.
DeLano Scientific LLC
Overview
1.
2.
3.
4.
Project Overview
Some “Biggish” examples
Animations
Intro/Demo (if there’s time)
What is DeLano Scientific LLC?
• LLC = Limited Liability Company
• Mission: to create, share, and support molecular
software for all research scientists, students, and
educators, with minimal restrictions on usage.
• DeLano Scientific can be thought of as:
– A private software company with an independent
quasi-academic, scientific focus.
or
– An independent quasi-academic laboratory funded as
a private scientific software company.
Open-Source vs.
Free for Academics
• PyMOL is true Open-source in that it does not
discriminate against commercial entities – it is
free for all for unrestricted reuse.
• However, extra benefits are provided to those
individuals, laboratories, schools, and
companies who voluntarily sponsor the effort
with their contributions.
How are the Bills Paid?
• Sustainable funding now derived from purchases
of PyMOL licenses and support agreements.
• Therefore, we are directly accountable to
hundreds (eventually thousands?) of users in
Academia and Industry for our continued
existence and growth.
• To survive as a business, we must rapidly come
up with practical solutions to broad visualization
needs for today and the future.
Visualization of Large
Complexes
• Software Issues
– What can you do with PyMOL?
– Where does PyMOL break down?
– What can be done about it?
• Data Format Issues
– Existing limitations in the data files.
– PyMOL is a mostly a follower/consumer in this
area.
PyMOL Is a General Tool
• PyMOL is good for many things, but not great
for very many of them.
• User base spans the full range: students,
small molecule chemists, crystallographers,
up through CryoEM.
• Best uses of PyMOL at present:
– Communication of “molecular scenes”.
– Generation of high quality images.
– Scripting and generation of animations.
Visualization of Large
Complexes
• Can combine molecular data with volumetric
data.
• Can compute volumes from atomic
coordinates.
• Can compute isosurfaces and color-bypotential (no “volume” rendering yet)
Can PyMOL Visualize Large
Complexes?
• Well…maybe.
Let’s try some…
Limits of PyMOL
• There are some practical limits…
– Maximum = 1 million atoms on a 1 GB machine.
– The comfortable limit on Linux is about a 1/4 of that.
– The practical limit on Windows is only about 150,000
atoms per GB of RAM due to VM problems.
• PyMOL is optimized for performance and image
quality, but not memory usage.
Outlook for Improvement?
• Unless specifically prioritized by users, memory
usage is not likely to improve much due to
architectural constraints in the code.
• However, it may be possible to improve Windows memory
behavior to approach that of Unix.
• 8+ GB RAM should become attainable over the
next several years as 64-bit computers become
more common.
• G5, Athlon64, Itanium2, etc.
Map File Formats:
• PyMOL does has volume data support:
– Electronic density
• XPLOR, CCP4, O/Brix
– EM reconstructions
• No specific file formats yet
– Electrostatic Potentials
• Delphi/Grasp, Biosym Grids, Mead AVS Grids
Limits on PyMOL Map Handling
• Fast but wasteful
– PyMOL currently stores vertices and levels
– 4 * sizeof(float) = 16 bytes/voxel
– Largest practical map with 1 GB RAM
200 ^ 3 ?
• Current user base hasn’t yet bumped up
against PyMOL’s limits – but it may
happen.
Summary on Large Complexes
•
PyMOL may be useful for working with
asymmetric units.
•
However, more specialized tools will
probably be needed for visualization of
million-atom biological-units.
Animations
1) Rendered Movies
2) Real Time OpenGL Movies
Real Time Animations
Demo