Conventional protein docking methods use rigid docking algorithms but the results have been unsatisfactory, because protein structures are flexible in live environments. In this study, the side-chain flexibility is introduced into protein docking. First, the Morse theory is applied to curvature labelling and region-growing for segmenting the protein surface into smaller patches. The surface critical points are then extracted for each surface region which has been obtained in the segmentation, and a list of more precise and smaller surface patches can be obtained. Secondly, based on the segmented surface, we propose to describe the protein with an ensemble of conformations which incorporate the flexibility of interface side-chains by sampling their conformations using rotamers. We define a 3D rotation invariant shape descriptor based on the Spherical Harmonics Descriptor to deal with the flexible protein surface patches. The signature for each surface patch can be more accurately described and easily compared for the similarity between the signatures. The pairwise complementarity matching is needed only between the convex patches of the ligand with concave patches of the receptor and vice versa, thus the computational cost is greatly reduced. Finally, we are able to use the iterative closest point (ICP) algorithm, thanks to the advantage of our matching method that is able to pre-compute and store the transformation invariant, fast Fourier transform (FFT) docking correlation based representation of each flexible surface patch. Compared with the global geometric matching algorithm and other methods, our FlexDock system generates much less false positive docking candidates, it shows promising advantages in identification of the complementary candidates.