The problem of receptor-ligand recognition and binding is encountered in a very large number of biological processes. The behavior of the molecules depends both on their geometric shape and on the chemical interactions among their atoms. This work addresses only the geometrical (key-in-lock) aspect of the problem, where acceptable solutions should exhibit shape complementarity. The problem we are faced with here is reminiscent of partial 3-D surface matching problems in computer vision. Here we present a new 3-D molecular surface representation by (hundreds of) sparse interest (critical) points with associated normals and a subsequent matching approach which is based on the Geometric Hashing paradigm originally developed for Computer Vision motivated object recognition applications. Potential solutions resulting in the interpenetration of the molecules are discarded by a subsequent verification procedure. Numerous examples of the successful geometric prediction of our technique are presented. In all cases the performance of our algorithm has been by several orders of magnitude faster than of other state-of-the-art docking algorithms.