fPOP: footprinting functional pockets of proteins by comparative spatial patterns

摘要: fPOP (footprinting Pockets Of Proteins, http://pocket.uchicago.edu/fpop/) is a relational database of the protein functional surfaces identified by analyzing shapes binding sites in approximately 42,700 structures, including both holo and apo forms. We previously used purely geometric method to extract spatial patterns (split pockets) 19,000 bound structures constructed database, SplitPocket (http://pocket.uchicago.edu/). These are now as templates predict unbound structures. To conduct shape comparison, we use Smith-Waterman algorithm footprint an pocket fragment with those SplitPocket. The pairwise alignment fragments evaluate local structural similarity via matching. final results our large-scale computation, 90,000 or predicted surfaces, stored fPOP. This provides easily accessible resource for studying assessing conformational changes between forms divergence. Moreover, it may facilitate exploration physicochemical textures molecules inference function. Finally, approach framework classification proteins into families on basis their surfaces.