Geometric Matching of Protein-Ligand Binding Sites
Speaker: Tom Funkhouser , Princeton University
Date: March 24 2006
Time: 3:15PM to 4:15PM
Location: 32-G449 (Patil/ Kiva) NOTE UNUSUAL TIME AND ROOM
Host: Polina Golland and Seth Teller, CSAIL
Contact: Polina Golland, x38005, polina@csail.mit.edu
Relevant URL: The goal of our project is to develop new computational methods
for predicting the biochemical function of a protein from its 3D
structure. Given a PDB file, a multi-variate field is computed to
represent the geometric and chemical properties of its binding
site(s). Then, a shape descriptor encodes those properties in a
concise representation suitable for indexing and rapid matching with
algorithms based on the spherical harmonic and inverse Wigner-D
transforms. Finally, the similarity between shape descriptors is used
to drive a nearest-neighbor classifier that predicts the biochemical
function of the protein based on its similarities to others with known
functions. This process provides a new method for predicting protein
function that achieves higher classification rates than competing
methods for proteins with dissimilar sequences.
This is joint work with Janet Thornton, Fabian Glaser,
Roman Laskowski, Richard Morris, Irilenia Nobeli, and
Gareth Stockwell from EBI, and Michael Kazhdan from Princeton.
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