OptDesign: extending optimizable k-dissimilarity selection to combinatorial library design

Generation of a Small Library of Natural Products Designed to Cover Chemical Space Inexpensively

Natural products space includes at least 200,000 compounds and the structures of most of these compounds are available in digital format. Previous analyses showed (i) that although they were capable of taking up synthetic pharmaceutical drugs, such exogenous molecules were likely the chief ‘natural’ substrates in the evolution of the transporters used to gain cellular entry by pharmaceutical drugs, and (ii) that a relatively simple but rapid clustering algorithm could produce clusters from which individual elements might serve to form a representative library covering natural products space. This exploited the fact that the larger clusters were likely to be formed early in evolution (and hence to have been accompanied by suitable transporters), so that very small clusters, including singletons, could be ignored. In the latter work, we assumed that the molecule chosen might be that in the middle of the cluster. However, this ignored two other criteria, namely the commercial availability and the financial cost of the individual elements of these clusters. We here develop a small representative library in which we to seek to satisfy the somewhat competing criteria of coverage (‘representativeness’), availability and cost. It is intended that the library chosen might serve as a testbed of molecules that may or may not be substrates for known or orphan drug transporters. A supplementary spreadsheet provides details, and their availability via a particular supplier.

A recognition-mediated reaction drives amplification within a dynamic library

A single, appropriately designed, recognition event targets and transforms one of two reactive members of an exchanging pool of compounds through a recognition-mediated irreversible cycloaddition reaction, altering dramatically the final composition and kinetic behaviour of the dynamic library.

Application of a sparse matrix design strategy to the synthesis of dos libraries

We have implemented an interactive and practical sparse matrix design strategy for the synthesis of DOS libraries, which facilitates the selection of diverse library members within a user-defined range of physicochemical properties while still maintaining synthetic efficiency. The utility of this approach is illustrated with the synthesis of an 8000-membered library of stereochemically diverse medium-sized rings accessible via a build/couple/pair DOS strategy. Diverse library members were selected from a virtual library by applying the maximum dissimilarity method, while the selection of similar analogs around each diverse product was ensured by picking near neighbors algorithmically based on fingerprint comparison. Adjustable filters on compound properties, which can be tailored to suit the needs of the target biology, facilitated subset selection from the synthetically accessible compounds.

Synthesis of a stereochemically diverse library of medium-sized lactams and sultams via S(N)Ar cycloetherification

We have implemented an aldol-based "build/couple/pair" (B/C/P) strategy for the synthesis of stereochemically diverse 8-membered lactam and sultam scaffolds via S(N)Ar cycloetherification. Each scaffold contains two handles, an amine and aryl bromide, for solid-phase diversification via N-capping and Pd-mediated cross coupling. A sparse matrix design strategy that achieves the dual objective of controlling physicochemical properties and selecting diverse library members was implemented. The production of two 8000-membered libraries is discussed including a full analysis of library purity and property distribution. Library diversity was evaluated in comparison to the Molecular Library Small Molecule Repository (MLSMR) through the use of a multifusion similarity (MFS) map and principal component analysis (PCA).

New directions in library design and analysis

The high costs associated with high-throughput screening (HTS) coupled with the limited coverage and bias of current screening collections is such that diversity analysis continues to be an important criterion in lead generation. Whereas early approaches to diversity analysis were based on traditional descriptors such as two-dimensional fingerprints a recent emphasis has been on assessing scaffold coverage to ensure that a variety of different chemotypes are represented. Moreover, whether designing diverse or focused libraries, it is widely recognised that designs should aim to achieve a balance in a number of different properties and multiobjective optimisation provides an effective way of achieving such designs.

Explicit Diversity Index (EDI): a novel measure for assessing the diversity of compound databases

A novel diversity assessment method, the Explicit Diversity Index (EDI), is introduced for druglike molecules. EDI combines structural and synthesis-related dissimilarity values and expresses them as a single number. As an easily interpretable measure, it facilitates the decision making in the design of combinatorial libraries, and it might assist in the comparison of compound sets provided by different manufacturers. Because of its rapid calculation algorithm, EDI enables the diversity assessment of in-house or commercial compound collections.

Balancing focused combinatorial libraries based on multiple GPCR ligands

G-Protein coupled receptors (GPCRs) are important targets for drug discovery, and combinatorial chemistry is an important tool for pharmaceutical development. The absence of detailed structural information, however, limits the kinds of combinatorial design techniques that can be applied to GPCR targets. This is particularly problematic given the current emphasis on focused combinatorial libraries. By linking an incremental construction method (OptDesign) to the very fast shape-matching capability of ChemSpace, we have created an efficient method for designing targeted sublibraries that are topomerically similar to known actives. Multi-objective scoring allows consideration of multiple queries (actives) simultaneously. This can lead to a distribution of products skewed towards one particular query structure, however, particularly when the ligands of interest are quite dissimilar to one another. A novel pivoting technique is described which makes it possible to generate promising designs even under those circumstances. The approach is illustrated by application to some serotonergic agonists and chemokine antagonists.

Integrating cheminformatic analysis in combinatorial chemistry

Cheminformatic analysis of drug-related compound databases has enabled the identification of the physicochemical properties that have the greatest influence on determining the drug-like characteristics of a compound. This enables definition of the parameters and profiles used in constructing a high-quality combinatorial library. Awareness of the multi-objective nature of combinatorial library construction has also given rise to techniques designed to enhance the likelihood of including the best compounds in a given library.

Applying data mining techniques to library design, lead generation and lead optimization

Many data mining techniques have been applied to activity and ADMET datasets and the resulting models are being used to understand quantitative structure-activity relationships and design new libraries. This review summarizes data mining concepts and discuss their application to library design, lead generation (particularly for sequential screening) and lead optimization (specifically for generating and interpreting QSAR models). Also, this review discusses recent comparative studies between data mining techniques and draws some conclusions about the patterns emerging in the drug discovery data mining field.