Issues Surrounding the Use of Open-Source PyMOL to Visualize Large Complexes

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Issues Surrounding the Use of Open-Source PyMOL
to Visualize Large Complexes

• Warren L. DeLano, Ph.D.
• DeLano Scientific LLC

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Overview

1. Project Overview
2. Some Biggish examples
3. Animations
4. Intro/Demo (if theres time)

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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.

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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.

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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.

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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.

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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.

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Visualization of Large Complexes

• Can combine molecular data with volumetric data.
• Can compute volumes from atomic coordinates.
• Can compute isosurfaces and color-by-potential
  (no volume rendering yet)

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Can PyMOL Visualize Large Complexes?

• Wellmaybe. Lets try some

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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.

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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.

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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

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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 hasnt yet bumped up against
  PyMOLs limits but it may happen.

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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.

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Animations

1. Rendered Movies
2. Real Time OpenGL Movies

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Real Time Animations
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Demo