The protein 3D structure contains crucial information for understanding biological systems and       also essential for protein design and rational drug design. Protein structural bioinformatics is        an active research area that develops and applies computational techniques for analyzing            protein structures.

     Protein structural bioinformatics is facing new challenges raised from needs of analyzing an        increasing number of solved protein structures, low-resolution structural data from electron          microscopy or tomography, predicted structures, as well as structures of unknown function. To       enable efficient global and local protein structure analysis, our group has been using a protein       surface representation with the 3D Zernike descriptors (3DZD). The 3DZD are series              expansion of a three dimensional mathematical function that can represent a 3D object in a        rotation and translational invariant fashion. In this talk we will discuss several applications of       the protein surface representation. First, we will introduce on our method named 3D-SURFER,       for real-time searching of global protein structures, which can be in low-resolution. Next,           application to local pocket matching for binding ligand prediction will be discussed. Finally,        we applied 3DZD for shape-based protein-protein docking. Our new docking algorithm, LZerD (local 3D       Zernike descriptor-based Docking algorithm), uses the 3DZD for capturing local shape complementarity       of interacting protein surfaces. LZerD has been further extended recently for multiple protein docking       and also for fitting multiple protein structures into a density map of electron microscopy.