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Current approaches to the design of combinatorial libraries assume that structural diversity in the reactant pools corresponds to structural diversity in the combinatorial libraries that result from reacting these pools together. In experiments with three different published libraries, dissimilarity-based compound selection (DBCS) is applied at two levels. First, the DBCS algorithm is applied at the reactant level, a library is built, and its diversity is measured. Second, the DBCS algorithm is applied to the full set of products generated by enumeration of all the reactants and the diversity of the subset is measured. Results show that reactant-based selection, which attempts to maximize diversity in the pools, results in noticeably less diverse libraries than if the selection is performed at the product level. Experiments are reported to estimate the upperbound to diversity achievable using DBCS, and it appears that DBCS is very effective at finding maximally diverse subsets. However, applying DBCS sele...

A substructural analysis approach is used to calculate biological activity profiles, which contain weights that describe the differential occurrences of generic features (specifically, the numbers of hydrogen-bond donors and acceptors, the numbers of rotatable bonds and aromatic rings, the molecular weights, and the 2κα shape descriptors) in active molecules taken from the World Drug Index and in (presumed) inactive molecules taken from the SPRESI database. Even with such simple structural descriptors, the profiles discriminate effectively between active and inactive compounds. The effectiveness of the approach is further increased by using a genetic algorithm for the calculation of the weights comprising a profile. The methods have been successfully applied to a number of different data sets.

The program SELECT is presented for the design of combinatorial libraries. SELECT is based on a genetic algorithm with a multi-objective fitness function. Any number of objectives can be included, provided that they can be readily calculated. Typically, the objectives would be to maximize structural diversity while ensuring that the compounds in the library have “drug-like” properties. In the examples given, structural diversity is measured using Daylight fingerprints as descriptors and either the normalized sum of pairwise dissimilarities, calculated with the cosine coefficient, or the average nearest neighbor distance, calculated with the Tanimoto coefficient, as the measure of diversity. The objectives are specified at run time. Combinatorial libraries are selected by analyzing product space, which gives significant advantages over methods that are based on analyzing reactant space. SELECT can also be used to choose an optimal configuration for a multicomponent library. The performance of SELECT is dem...

This paper compares the effectiveness of similarity measures based on two-dimensional fingerprints and on molecular fields for identifying pairs of bioisosteric molecules in the BIOSTER database. The results suggest that the two types of descriptor are complementary in nature, each finding some bioisosteric pairs that are not found by the other. This conclusion is confirmed by studies of groups of BIOSTER molecules that share the same activity characteristics, and by experiments that involve combining the two types of similarity measure.

Two methods are described for biasing conformational search during pharmacophore elucidation using a multiobjective genetic algorithm (MOGA). The MOGA explores conformation on-the-fly while simultaneously aligning a set of molecules such that their pharmacophoric features are maximally overlaid. By using a clique detection method to generate overlays of precomputed conformations to initialize the population (rather than starting from random), the speed of the algorithm has been increased by 2 orders of magnitude. This increase in speed has enabled the program to be applied to greater numbers of molecules than was previously possible. Furthermore, it was found that biasing the conformations explored during search time to those found in the Cambridge Structural Database could also improve the quality of the results.

Three field-based similarity methods are compared in retrospective virtual screening experiments. The methods are the CatShape module of CATALYST, ROCS, and an in-house program developed at the University of Sheffield called FBSS. The programs are used in both rigid and flexible searches carried out in the MDL Drug Data Report. UNITY 2D fingerprints are also used to provide a comparison with a more traditional approach to similarity searching, and similarity based on simple whole-molecule properties is used to provide a baseline for the more sophisticated searches. Overall, UNITY 2D fingerprints and ROCS with the chemical force field option gave comparable performance and were superior to the shape-only 3D methods. When the flexible methods were compared with the rigid methods, it was generally found that the flexible methods gave slightly better results than their respective rigid methods; however, the increased performance did not justify the additional computational cost required.

Reduced graphs provide summary representations of chemical structures. Here, a variety of different types of reduced graphs are compared in similarity searches. The reduced graphs are found to give comparable performance to Daylight fingerprints in terms of the number of active compounds retrieved. However, no one type of reduced graph is found to be consistently superior across a variety of different data sets. Consequently, a representative set of reduced graphs was chosen and used together with Daylight fingerprints in data fusion experiments. The results show improved performance in 10 out of 11 data sets compared to using Daylight fingerprints alone. Finally, the potential of using reduced graphs to build SAR models is demonstrated using recursive partitioning. An SAR model consistent with a published model is found following just two splits in the decision tree.

This paper addresses a major issue in library design, namely how to efficiently optimize the library size (number of products) and configuration (number of reagents at each position) simultaneously with other properties such as diversity, cost, and drug-like physicochemical property profiles. These objectives are often in competition, for example, minimizing the number of reactants while simultaneously maximizing diversity, and thus present difficulties for traditional optimization methods such as genetic algorithms and simulated annealing. Here, a multiobjective genetic algorithm (MOGA) is used to vary library size and configuration simultaneously with other library properties. The result is a family of solutions that explores the tradeoffs in the objectives. This is achieved without the need to assign relative weights to the objectives. The user is then able to make an informed choice on an appropriate compromise solution. The method has been applied to two different virtual libraries: a two-component aminothiazole library and a four-component benzodiazepine library.

This paper considers the problems associated with processing planar (two-dimensional) representations of three-dimensional structures. To overcome the ambiguity of such representations, a new ring set is defined in terms of simple faces and cut faces. The concept of a cut-vertex graph is introduced to explain the combinatorial relationship between the number of simple faces and the number of planar embedments

Current ring perception algorithms for use on chemical graphs concentrate on processing specific structures. In this review, the various published ring perception algorithms are classified according to the initial ring set obtained, and each algorithm or method of perception is described in detail. The final ring sets obtained are discussed in terms of their suitability for use in representing the ring systems in structurally explicit parts of generic chemical structures.