We present a hybrid parallel system based on commodity components to gain supercomputer power at low cost. The architecture is built around a coarse-grained PC-cluster linked by a high-speed network and fine-grained parallel processor arrays connected to each node. Identifying applications that profit from this kind of processing power is critical to justify the use of such a system. In this paper, we present a new approach to high performance protein database scanning with hybrid computing. To derive an efficient mapping onto this architecture, we designed an instruction systolic sequence comparison algorithm. This results in a database scanning implementation with significant runtime savings.