CS Fingerprints
The Connected Subgraph Fingerprint (CSFP) is a novel fingerprint method which, in contrast to other methods, captures all connected subgraphs as structural features of a compound. This property gives the CSFP a complete feature space and high adaptive potential. Apart from surpassing common methods in standard similarity-driven virtual screening settings, the CSFP has substantial structural advantages when applied to combinatorial fragment spaces or in machine learning.
CS FingerprintsPublikationen
- Bellmann, L.; Penner, P.; Rarey, M. (2019) Connected Subgraph Fingerprints: Representing Molecules Using Exhaustive Subgraph Enumeration . Journal of Chemical Information and Modeling, 59 (11):4625-4635.
SpaceCompare
SpaceCompare is a novel tool for the comparison and analysis of ultra-large combinatorial chemical spaces. It enables the complete examination of trillion-sized chemical spaces for the first time by employing a combinatorial algorithmic approach. The tool has three modes of operation
- overlap calculation of two combinatorial spaces
- distribution computation for five well-known physicochemical properties
- chemical space optimization by removal of fragments with undesired properties
SpaceLight
SpaceLight is a novel search method for similarity-driven virtual screening in large combinatorial fragment spaces using topological fingerprints. It utilizes the well-known ECFP and the Connected Subgraph Fingerprint (CSFP) to describe molecular similarity. In contrast to existing workflows using fingerprint methods, the SpaceLight approach is able to exploit the combinatorial character of fragment spaces and consequently can conduct similarity searches considering billions of compounds within seconds on a standard PC. In addition fragments forming scaffolds can be retreived to identify reaction routes for compounds and custom fragment spaces can be generated.
SpaceLightPublikationen
- Bellmann, L.; Penner, P.; Rarey, M. (2021) Topological Similarity Search in Large Combinatorial Fragment Spaces . Journal of Chemical Information and Modeling, 61(1):238-251.