A framework for the evaluation of chemical structure databases

Access to desk-top structure and reaction databases through applications such as Chemical Abstracts' SciFinder, MDL's Beilstein CrossFire, and ISIS Reaction Browser has led to changes in information seeking habits of research chemists, the impact of which has implications when database purchasing decisions are made. A semiquantitative assessment is proposed which takes into account key aspects of structure and reaction databases. Assessment criteria are identified which can be weighted according to an organization's information needs. Values are then assigned to criteria for each data source, after which a formula is applied which leads to an indication of the relative value of systems under consideration. The formula takes into account the cost of database products and also the incremental benefit of adding a new system to an existing collection. This work is presented as a generic approach to the evaluation of databases and is not limited in scope to only structure and reactions databases.     

Review of chemical signature databases

This review assesses the current state of chemical signature databases, the primary characteristics that determine their applicability, characterization of their capability to support spectral identifications, and the target audience to which they are directed. Database file formats, spectrometer operating conditions, and spectral matching tools are found to be primary characteristics that determine the applicability of databases and their ability to support spectral identifications. Chemical signature databases have evolved in two very different directions. One movement offers a single portal for chemical signature determinations by multiple analytical techniques. The other movement is toward highly specialized databases that address narrow scientific disciplines. Both movements are necessary, and serve distinctly different needs in the analytical community.     

The chemical information system and spectral databases

From 1970 to 1984, the U.S. Government cooperated with various organizations in the support of the development, maintenance, and distribution of a computer-based chemical information system of spectral and other numeric databases, known as the NIH/EPA Chemical Information System (CIS). This presentation discusses the history of the project and related activities in the area of numeric database activities and summarizes the current state of the project.     

Secure analysis of distributed chemical databases without data integration

We present a method for performing statistically valid linear regressions on the union of distributed chemical databases that preserves confidentiality of those databases. The method employs secure multi-party computation to share local sufficient statistics necessary to compute least squares estimators of regression coefficients, error variances and other quantities of interest. We illustrate our method with an example containing four companies' rather different databases.     

Scaffold topologies. 2. Analysis of chemical databases

We have systematically enumerated graph representations of scaffold topologies for up to eight-ring molecules and four-valence atoms, thus providing coverage of the lower portion of the chemical space of small molecules (Pollock et al. J. Chem. Inf. Model., this issue). Here, we examine scaffold topology distributions for several databases: ChemNavigator and PubChem for commercially available chemicals, the Dictionary of Natural Products, a set of 2742 launched drugs, WOMBAT, a database of medicinal chemistry compounds, and two subsets of PubChem, "actives" and DSSTox comprising toxic substances. We also examined a virtual database of exhaustively enumerated small organic molecules, GDB (Fink et al. Angew. Chem., Int. Ed. 2005, 44, 1504-1508), and we contrast the scaffold topology distribution from these collections to the complete coverage of up to eight-ring molecules. For reasons related, perhaps, to synthetic accessibility and complexity, scaffolds exhibiting six rings or more are poorly represented. Among all collections examined, PubChem has the greatest scaffold topological diversity, whereas GDB is the most limited. More than 50% of all entries (13 000 000+ actual and 13 000 000+ virtual compounds) exhibit only eight distinct topologies, one of which is the nonscaffold topology that represents all treelike structures. However, most of the topologies are represented by a single or very small number of examples. Within topologies, we found that three-way scaffold connections (3-nodes) are much more frequent compared to four-way (4-node) connections. Fused rings have a slightly higher frequency in biologically oriented databases. Scaffold topologies can be the first step toward an efficient coarse-grained classification scheme of the molecules found in chemical databases.     

Advanced exact structure searching in large databases of chemical compounds

Efficient recognition of tautomeric compound forms in large corporate or commercially available compound databases is a difficult and labor intensive task. Our data indicate that up to 0.5% of commercially available compound collections for bioscreening contain tautomers. Though in the large registry databases, such as Beilstein and CAS, the tautomers are found in an automated fashion using high-performance computational technologies, their real-time recognition in the nonregistry corporate databases, as a rule, remains problematic. We have developed an effective algorithm for tautomer searching based on the proprietary chemoinformatics platform. This algorithm reduces the compound to a canonical structure. This feature enables rapid, automated computer searching of most of the known tautomeric transformations that occur in databases of organic compounds. Another useful extension of this methodology is related to the ability to effectively search for different forms of compounds that contain ionic and semipolar bonds. The computations are performed in the Windows environment on a standard personal computer, a very useful feature. The practical application of the proposed methodology is illustrated by several examples of successful recovery of tautomers and different forms of ionic compounds from real commercially available nonregistry databases.     

Characterising the geometric diversity of functional groups in chemical databases

Summary We have developed a program, HookSpace, which provides a simplistic approach to assessing the diversity of molecular databases. The spatial relationship between pairs of intramolecular functional groups can be analysed in a variety of ways to provide both qualitative and quantitative measures of diversity. Results are described and contrasted for two commercially available databases and a combinatorial library of benzodiazepam derivatives. HookSpace highlights the main differences in molecular content of these data sets.     

The publication speed of information in bibliographic chemical databases.

The quality of bibliographic databases depends very much on the reliably fast follow-up of the pertinent literature. We have studied this quality feature of two important chemical bibliographic databases: Chemical Abstracts (CA) and Analytical Abstracts (AA). The follow-up rate (speed of information) of these databases has been determined with respect to 10 core journals in analytical chemistry. On the average the performance of Chemical Abstracts has been good over the past decade, while the formerly poor performance of Analytical Abstracts has improved considerably. Some quite unexpected nonuniformities can, however, still be detected in the publication time distributions of both databases.     

Clustering chemical databases using adaptable projection cells and MCS similarity values

In this paper we propose a new method based on measurements of the structural similarity for the clustering of chemical databases. The proposed method allows the dynamic adjustment of the size and number of cells or clusters in which the database is classified. Classification is carried out using measurements of structural similarity obtained from the matching of molecular graphs. The classification process is open to the use of different similarity indexes and different measurements of matching. This process consists of the projection of the obtained measures of similarity among the elements of the database in a new space of similarity. The possibility of the dynamic readjustment of the dimension and characteristic of the projection space to adapt to the most favorable conditions of the problem under study and the simplicity and computational efficiency make the proposed method appropriate for its use with medium and large databases. The clustering method increases the performance of the screening processes in chemical databases, facilitating the recovery of chemical compounds that share all or subsets of common substructures to a given pattern. For the realization of the work a database of 498 natural compounds with wide molecular diversity extracted from SPECS and BIOSPECS B.V. free database has been used.     

How to add chemical abstracts service registry numbers and structures to databases via chemical names comparison

For the conversion of nonstructural chemical databases to structure databases, a series of algorithms to find the closest match between existing names to names in a reference database are described. On the basis of the best match, new fields such as the Chemical Abstracts Service Registry Number (CASRN) or structures were added to the database.     

Fast 3D shape screening of large chemical databases through alignment-recycling

Background  

Large chemical databases require fast, efficient, and simple ways of looking for similar structures. Although such tasks are now fairly well resolved for graph-based similarity queries, they remain an issue for 3D approaches, particularly for those based on 3D shape overlays. Inspired by a recent technique developed to compare molecular shapes, we designed a hybrid methodology, alignment-recycling, that enables efficient retrieval and alignment of structures with similar 3D shapes.