Thesis (Ph.D.)--Boston University / PLEASE NOTE: Boston University Libraries did not receive an Authorization To Manage form for this thesis or dissertation. It is therefore not openly accessible, though it may be available by request. If you are the author or principal advisor of this work and would like to request open access for it, please contact us at open-help@bu.edu. Thank you. / Ligand binding sites in proteins generally include "hot spots" that contribute a large fraction of the binding free energy and, therefore, are of prime interest in drug design. To find hot spots on the protein surface, a protein can be screened against libraries of small organic molecules to identify interaction sites using nuclear magnetic resonance (NMR) spectroscopy or the X-ray crystallographic technique Multiple Solvent Crystal Structures (MSCS). Small organic molecules can bind at several locations on the surface of a protein, but many different molecules congregate only in "consensus sites" identifying the hot spots. The mapping algorithm FTMAP is a computational analogue of experimental fragment screening methods. The principles of computational mapping were used for the development and testing of the binding site identification algorithm FTSITE, implemented as a web-based server. Finding ligand binding sites in silico is a classical challenge, and the success rate of identifying the ligand binding site as the first predicted site has increased to 83% during the last decade. FfSITE, based on biophysical modeling of protein-ligand interactions, increased the success rate to 94% on the same established test sets. Critical to the success of FfSITE is the use of multiple small molecules as probes; screening by X-ray crystallography and NMR spectroscopy had demonstrated a tendency of ligand binding sites to bind small organic compounds ranging 1n shapes, sizes, and polarities. Further, FfSITE does not use surrogate measures of ligand binding propensity such as site geometries and dimensions. It was shown that FTSITE can also successfully identify allosteric ligand binding sites that can serve as candidates for drug design. Furthermore, the hot spot information provided by FfMAP was shown to guide the development of core fragments, found by experimental fragment screening , into optimal ligands for a number of drug target proteins. Computational mapping can also be used for fragment-based drug design by finding fragments with preference for some regions of the binding site. To facilitate this analysis , a server enabling the fast generation of force field parameters for user-specified small molecules or fragments was developed. / 2031-01-02
| Identifer | oai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/32040 |
| Date | January 2012 |
| Creators | Ngan, Chi Ho |
| Publisher | Boston University |
| Source Sets | Boston University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
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