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Molecular Modeling Facility
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Reimann Building, Room R462 215 214 4230 215 728 3654 Roland.Dunbrack@fccc.edu Mark.Andrake@fccc.edu |
Function
The Molecular Modeling Facility provides state-of-the-art services in protein sequence analysis and structure prediction to FCCC investigators. These services include database search, multiple sequence alignment, phylogenetic trees, secondary structure prediction, transmembrane, coiled-coil and disordered region prediction, homology modeling of single proteins and complexes, protein-protein and protein-ligand docking, and ligand design.
Description
Currently, one-third to one-half of sequenced proteins are homologous at least in part to a protein of known structure. Homology modeling methods use known structures to build three-dimensional models of target proteins of unknown structure. These models can be used to predict functional interactions with other molecules, to explain existing experimental data, to generate testable hypotheses, and in some cases to become the basis for design of specific inhibitors for translational research. The Facility was created in April 2003, and since that time has performed services for 12 peer-reviewed funded Principal Investigators in seven Research Programs and all three Divisions of FCCC. The Facility has also developed new software for automating the modeling process to allow Facility staff more time to concentrate on the biological problem under study in collaboration with the principal investigator. This software is extensible, so that it allows new tools to be incorporated into the same graphical user interface as they become available.
As new technologies such as two-hybrid interaction mapping and two-dimensional gel electrophoresis allow investigators to identify functional and physical interactions of larger numbers of proteins in fully sequenced genomes, the demand for detailed structural information will grow rapidly. The use of this Facility is therefore expected to grow significantly over the next five years. The services of the Facility will provide increasingly important information for understanding complex biological systems.