Data mining in biological structure libraries can be a powerful tool to better understand biochemical processes. This article introduces the LISA algorithm which enables the researcher to search substructures in PDB files describing the 3D structure of protein molecules. The use of constraints such as atomic distances, torsion angles, or the distance of residues within the linear amino acid sequence, allows for great flexibility in defining and searching specific structures, which could not be found with other tools. Data mining in biological databases, e.g. scanning the entire PDB database for structures that match user-defined criteria, is a massively computation-intensive task. Thus, we present a parallel implementation of LISA and show that the algorithm achieves good parallel efficiency on homogeneous clusters.