DomainFinder
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DomainFinder

DomainFinder is an interactive program for the determination and characterization of dynamical domains in proteins. Its key features are

  • computational efficiency: even large proteins can be analyzed using a desktop computer in a few minutes
  • ease of use: a state-of-the-art graphical user interface
  • export of results for visualization and further analysis (VRML, PDB, and MMTK object format)

Dynamical domains are an important concept in the description of protein dynamics. A dynamical domain is a region in a protein which can move essentially like a rigid body relative to other regions. Many, but not all, proteins have dynamical domains, and if they do, the relative movements of the domains are usually related to the function of the protein. The identification of dynamical domains is therefore useful in understanding the function of the protein. However, there are other situations in which the knowledge of dynamical domains is helpful. In structure determination, it can help to predict whether complexation with a ligand, crystal packing, or other external influences can lead to important conformational changes. In protein engineering, it can indicate whether a given modification is likely to change the dynamical behavior of the protein. In experimental observations of protein motion, it can suggest regions of particular interest. In numerical simulations, it can point out the slow motions whose correct sampling must be verified.

DomainFinder is written in Python, a high-level object programming language that is particularly well suited to the demands of scientific computations. The speed-critical parts are implemented in C. For common operations it makes use of the Molecular Modeling Toolkit, a library of Python code for molecular modelling and simulation applications. The results of a domain analysis can be saved with all details in an MMTK data file, which permits all kinds of further analysis.

Acknowledgement

The development of DomainFinder and the theoretical methods it is based on was made possible by a postdoctoral fellowship from the Human Frontier Science Program Organization.