A fourier fingerprint-based method for protein surface representation.

A crucial enabling technology for structural genomics is the development of algorithms that can predict the putative function of novel protein structures: the proposed functions can subsequently be experimentally tested by functional studies. Testable assignments of function can be made if it is possible to attribute a putative, or indeed probable, function on the basis of the shapes of the binding sites on the surface of a protein structure. However the comparison of the surfaces of 3D protein structures is a computationally demanding task. Here we present four surface representations that can be used locally to describe the global shape of specifically bounded local region models. The most successful of these representations is obtained by a Fourier analysis of the distribution of surface curvature on concentric spheres around a surface point and summarizes a 24 A diameter spherically clipped region of protein surface by a fingerprint of 18 Fourier amplitude values. Searching experiments using these fingerprints on a set of 366 proteins demonstrate that this provides an effective and an efficient technique for the matching of protein surfaces.