Molecular fingerprints are an efficient and widely used method for similarity-driven virtual screening. Most fingerprint methods can be distinguished by the class of structural features considered. The Connected Subgraph Fingerprint (CSFP) overcomes this limitation and regards all structural features of a compound. This results in a more complete feature space and high adaptive potential to certain application scenarios. The novel descriptor surpasses widely used fingerprint methods in some cases and opens the way for topological search in combinatorial fragment spaces.