James G. Nourse

Managing the Combinatorial Explosion

Computer software designed to deal with the large amounts of data generated by chemical and biological research programs is described. The software includes methods for representation of the structural components of combinatorial libraries, enumeration of structures and structure-based searches, and comparisons within combinatorial libraries.

Over 20 years of reaction access systems from MDL: a novel reaction substructure search algorithm.

From REACCS, to MDL ISIS/Host Reaction Gateway, and most recently to MDL Relational Chemistry Server, a new product based on Oracle data cartridge technology, MDLs reaction database management and retrieval systems have undergone great changes. The evolution of the system architecture is briefly discussed. The evolution of MDL reaction substructure search (RSS) algorithms is detailed. This article mainly describes a novel RSS algorithm. This algorithm is based on a depth-first search approach and is able to fully and prospectively use reaction specific information, such as reacting center and atom-atom mapping (AAM) information. The new algorithm has been used in the recently released MDL Relational Chemistry Server and allows the user to precisely find reaction instances in databases while minimizing unrelated hits. Finally, the existing and new RSS algorithms are compared with several examples.

A first approach to the stereochemical analysis of tetraarylmethanes

Abstract A mathematical model is defined to represent tetraarylmethanes. The skeletal permutations of this model are described and analyzed in terms of mode equivalent rearrangements. This analysis is applied to an interpretation of the previously published results of a DNMR study of tetra-o-tolylsilane and analogs. A mechanism for the rearrangement is then postulated. The group of permutational flips is described and combined with the skeletal group to give the full permutation group of tetraarylmethanes.

The substance module: the representation, storage, and searching of complex structures

Chemical structures are typically represented in computer programs as simple graphs, where atoms are represented by a list of nodes and the bonds by a list of nondirectional edges. While this convention allows for the representation of a large variety of chemical structures, it does not lend itself toward the representation of many common substances such as polymers, nonstoichiometric mixtures, and formulations. An extension to this convention has been developed which allows properties to be identified with a defined subgraph in a structure, an Sgroup. This extension has been implemented in the Substance Module, a new MACCS-11 module, and is used to represent and search a much broader class of chemical substances. A description of the new representation and searching capabilities is given as well as examples of its use.

Self-contained sequence representation: bridging the gap between bioinformatics and cheminformatics.

The wide application of next-generation sequencing has presented a new hurdle to bioinformatics for managing the fast-growing sequence data. The management of biomacromolecules at the chemistry level imposes an even greater challenge in cheminformatics because of the lack of a good chemical representation of biopolymers. Here we introduce the self-contained sequence representation (SCSR). SCSR combines the best features of bioinformatics and cheminformatics notations. SCSR is the first general, extensible, and comprehensive representation of biopolymers in a compressed format that retains chemistry detail. The SCSR-based high-performance exact structure and substructure searching methods (NEMA key and SSS) offer new ways to search biopolymers that complement bioinformatics approaches. The widely used chemical structure file format (molfile) has been enhanced to support SCSR. SCSR offers a solid framework for future development of new methods and systems for managing and handling sequences at the chemistry level. SCSR lays the foundation for the integration of bioinformatics and cheminformatics.

Computer Representation and Searching of Chemical Substances

Chemical structures are typically represented in computer programs as simple graphs, where the atoms are represented by a list of nodes and the bonds by a list of non-directional edges. We will describe an extension to such a representation which allows properties to be identified with a defined subgraph in a structure; these properties are fully searchable at a substructure level. A description of the representation will be given and examples of searching capabilities will be illustrated. An implementation of these techniques has been applied to homopolymers, copolymers, non-stoichiometric mixtures, formulations, and ‘superatoms’. Other potential uses will also be discussed. These extensions to chemical representation allow us to represent and search a much broader class of chemical substances than the set of discrete chemical structures which have previously been handled.

VET: A Tool for Reaction Plausibility Checking

Production of chemical reaction databases is a multistep process, with the possibility of errors at each of these steps. VET is a tool developed to trap errors in the chemical reactions identified as a part of this process. VET has been designed to minimize the acceptance of incorrect reactions, while still supporting various common practices in reaction depiction, including unbalanced reactions, suppressed components, and reactions with alternative products. We discuss the assumptions made in its construction, a general overview of its structure, and some performance characteristics.

Modern chemical and biological databases

Chemical structure databases and information management systems are a standard item in nearly all chemical structure research environments [1]. They are used to store and retrieve chemical structures as a data type as well as data associated with them. These systems have been designed for, and are customarily used for, single chemical structures that are reasonably well characterized. The recent surge in combinatorial chemistry work has provided a challenge to these systems since the number of chemical structures involved has grown dramatically. In addition, the actual entity studied may be a mixture of tens to millions of structures or more. Such mixtures can often be represented by a generic or Markush structure. This latter challenge will be emphasized in the discussion that follows.