אירועים והרצאות בפקולטה למדעי המחשב ע"ש הנרי ומרילין טאוב

The availability of three dimensional (3D) protein structures has increased dramatically over the past years. While at the start of the millennium, the Protein DataBank (PDB) held approximately 14,000 (3D) structures of biological macromolecules to-date this database holds 95,000 structures, 25,000 of those added during the last four years. As the total number of structures increased, the number of structures that cannot be classified by established bioinformatics methods has grown dramatically.

My thesis presents a new approach for analyzing a 3D protein structure by looking at the local geometry of a protein's surface. Using a discrete three-dimensional point-mesh to approximate the protein accessible surface, it is possible to define a neighborhood of arbitrary size around each point on the mesh and calculate its local curvature. When applied to a dataset consisting of DNA binding proteins, this method reveals that the distribution of curvature values on the surface of a protein is not dictated by the protein fold and is not directly correlated to fold family membership. Nevertheless, we found that proteins with similar surface-curvature distributions tend to exhibit common functional characteristics, despite the fact that they have evolved independently. Specifically we show that transcription factors are accurately distinguished from other DNA binding proteins which possess enzymatic activity. Overall, our method provides an additional insight regarding the tight relationship between the protein structure and its function.

M.Sc. thesis lecture supervised by Yael Mandel-Gutfreund