The improvement of the RS3 system for drug substructure searching

For the development of a new drug, medicinal chemists perform the structure-based drug design, i.e., search the existing drugs with the chemical structure similar to the chemical structure of the target drug. In brief, researcher and developer want to know drugs to have a specific chemical structure. Therefore, from large drug databases, it is necessary to give the information of selected drugs fast, which should have the members of a set of chemical moieties matching a user-defined query moiety. Substructure searching is the process of identifying the members of a set of chemical moieties that match a specific query moiety. Testing for substructure searching was developed in the late 1950s. In graph theoretical terms, this problem corresponds to determining which graphs in a set are subgraph isomorphic to a specified query graph. Testing for subgraph isomorphism has been proved, in the general case, to be an NP-complete problem. For the purpose of overcoming this difficulty, there were computational approaches. On the 1990s, a US patent has been granted on an atom-centered indexing scheme, used by the RS3 system; this has the virtue that the indexes generated can be searched by direct text comparison. This system is commercially used(http://www.acelrys.com/rs3). We define the RS3 system's drawback and present a new indexing scheme. This system treats substructure searching with substring matching by means of expressing chemical structure as predefined strings. However, it has insufficient `recall' and `precision' because of a fatal shortage of the indexing scheme. Expressing 2D chemical structure into ID a string has limit. Therefore, we break 2D chemical structure into ID structure fragments. We present in this paper a new index technique to improve recall and precision surprisingly.