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A structural hierarchy for virtual library screening and as a tool for data analysis

Shane Weaver, A. Peter Johnson, Andrew Leach
School of Chemistry
University of Leeds
Leeds, LS2 9JT
United Kingdom
Poster presented at:
3rd Joint Sheffield Conference on Chemoinformatics
April 2004, Sheffield, United Kingdom

Currently the pharmaceutical industry has at its disposal several computational techniques for the discovery of lead compounds. These include methods such as library docking and structure based de novo drug design. Inherent with many of these techniques is a large library of drug-like molecules which has to be processed sequentially each time a new drug is sought. Reducing the number of molecules which need to be analysed in the library without missing any leads is the aim of this project. This can be achieved by arranging the library of molecules into a hierarchy based on 3D structure. The relationships can be used in several ways which are being investigated in this project. The first was to implement the hierarchy into SynSPROUT [1], a structure generation program for de novo design. At each step of structure growth a synthetic reaction is used to join a new starting material from the library. The result of the docking phase of the unified species decides if superstructures of that starting material should be joined or screened out.

The hierarchy is also being used for replacement of starting materials within the finished structure, i.e. where monomers of a generated or imported ligand are replaced by sub- and super-structures which may better complement the boundary of the protein cavity.

A tool has been developed that can organise a molecular series into a 2D structural hierarchy. By allowing the medicinal chemist to visualise the structural relationships in the series, this tool can be useful for analysing structure-activity relationships and may also aid in activity prediction.

Once the main hierarchy has been constructed an optimization step can be performed to detect relationships between root nodes (molecules that are not substructures of any other). The optimization step was implemented in order to cluster those structures belonging to the same congeneric series. This was achieved by recursively removing terminal atoms from all root nodes to create frameworks [2]. A further optimization is a similarity test which groups those frameworks within a predefined tolerance.

[1] Bodo, K.; SynSPROUT: Generating synthetically accessible ligands by de novo design, Ph.D. Thesis, University of Leeds, Chemistry Department, 2002

[2] Xu, J.; A New Approach to Finding Natural Chemical Structure Classes, J. Med. Chem., 2002, 45, 5311-5320