Talk A Software Library for Monte Carlo-Based Rigid Body Modelling Against Small Angle Scattering Data

Presented by Christian Meesters in Scientific Applications 2009 on 2009/07/26 from 11:45 to 12:30

Rigid body modelling of protein complexes based on small angle scattering (SAS) data is a niche in structural biology with rising importance. The sas_rigid software package tries to combine several strategies to trace conformational changes followed by SAS, e. g. induced by ligand binding. The software is intended as a` proof of concept-software: The aim was to enable a screen of parameters to describe the conformational change within a reasonable time frame. This goal is reached by a built-in Monte Carlo algorithm with simulated annealing. The software allows for arbitrary symmetries & relations of protein chains. Its scripting interface ensures that even "exotic cases" can be handled. A new feature is the representation of protein complex conformation as probability distributions in 3D.
Software Description

The software was intentionally written as a library in the Python programming language and not as a stand alone program. This way rapid prototyping was granted, while potential users are enabled to easily write flexible scripts. Care was taken to have a simple & flexible user interface, while preventing the user to take nonsensical steps. The design strictly follows an object oriented paradigm throughout the construction of this library: At the heart of the library is a base class from which a class for holding atomic models is derived. This class makes use of PDB functionality provided by the biopython project [1]. An additional derived class can hold electron densities of medium resolution (e. g. from electron microscopy or crystallographic densities of large protein complexes).

Some central algorithms are outsourced to C/C++ to gain speed. SWIG [6], the "Simplified Wrapper and Interface Generator", is used to generate the interface to Python.
Modelling Strategy

The programs CRYSOL & CRYSON [5] serve as plugins for calculating theoretical scattering curves, I(q), for X-rays and neutrons, respectively. In addition users can calculate the distance distribution function, P(r) see [2]. For both cases, I(q) & P(r), a quality factor (x^2) can be calculated. To fit atomic 3D models to the experimental data the parameter space given by rotations and translations for each independent body is screen by different algorithms (either grid search or Monte Carlo). The user is asked to specify geometrical restraints and movement limits in advance. The software provides options for defining bodies arbitrarily. It is possible to limit the number of atoms used for calculating the P(r), while a smooth P(r) is warranted. Additional scripting capabilities are provided by using free features of YASARA [4] within its Python interface.
Future Prospects

Currently the project homepage can be found at As Python is an operating system independent language, installing Python ( along with some freely available modules (see the documentation of the software) is sufficient to get started. - Together with the authors of UltraScan [7], the "Swiss knife software in hydrodynamics", we try to translate the essential algorithms into C++ and provide the functionality of the sas_rigid software as a part UltraScan.

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2. H. Hartmann and H. Decker, All hierarchical levels are involved in conformational transitions of the 4 x 6-meric tarantula hemocyanin upon oxygenation, Biochimica et Biophysica Acta 1601(2), 132-137, 2002
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4. E. Krieger, G. Koraimann, and G. Vriend, Increasing the precision of comparative models with YASARA NOVA-a self-parameterizing force field, Proteins 47(3), 393-402, 2002
5. D. Svergun, C. Barberato, and M. H. J. Koch, CRYSOL - a Programm to Evaluate X-ray Solution Scattering of Biological Macromolecules from Atomic Coordinates, Journal of Applied Crystallography 28, 768-773, 1995
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7. B. Demeler UltraScan A Comprehensive Data Analysis Software Package for Analytical Ultracentrifugation Experiments. Modern Analytical Ultracentrifugation: Techniques and Methods, (D. J. Scott, S. E. Harding and A. J. Rowe. Eds. Royal Society of Chemistry (UK) (2005) 210-229)
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