Academic institutions and pharmaceutical companies have designed large synthetically accessible virtual combinatorial libraries, and commercial players offer on-demand synthesis of individual library compounds. The size of synthetically accessible compounds has continued to grow rapidly in recent years, with suppliers like Enamine that are capable of reliably synthesizing compounds from their Enamine REAL space, 2 currently containing 30 billion structures. To answer the need, more efficient algorithms for searching large combinatorial spaces have been developed, which process reactant structures and connection rules instead of processing all enumerated structures. In 2001 Rarey and Stahl published a method to retrieve similar molecules based on feature tree similarity. In 2009 Yu and Bakken employ a method called 'Monomer-based Similarity Searching (MoBSS)' that calculates atom pair descriptors from the reactant structures to locate matching combinatorial products. More recent papers describe other methods for performing similarity and substructure searches in combinatorial spaces. Recently, Schmidt, Klein and Rarey presented a fast algorithm locating similar compounds from combinatorial libraries based on the maximum common induced substructure (MCIS). Library molecules are considered matches if they contain a substructure, which exactly matches a large part of the query structure. For the special case where the MCIS size is required to match the entire query structure, the result is equivalent to a substructure search, therefore the algorithm can also be used to search for substructures. The problem of computing the MCIS in general is much harder than the problem to search for a substructure, but an excellent option if the goal is to locate similar compounds sharing some substructure.