Toward General Methods of Targeted Library Design:  Topomer Shape Similarity Searching with Diverse Structures as Queries

Abstract

A promising strategy for selecting synthetic targets is similarity-based searching of very large "virtual libraries", which comprise all structures accessible by linking two or three commercially available building blocks with combinatorial syntheses. To assess the general applicability of this strategy, leading structures taken from each of 34 recent medicinal chemistry publications were used as queries to search a virtual library containing 2.6 x 10(13) products from seven reactions, using a topomer shape similarity metric. Eighty-five percent of these searches succeeded, by yielding, with a search radius no greater than 120 topomer shape units, either at least 400 hits or hits from at least six sublibraries. From these 34 sets of search results, 122 representative structures were selected, illustrating potential "lead hops", or otherwise novel structures. Overall shape similarity to the query structure was confirmed for up to 95% of these representative structures, according to FLEXS, an algorithmically distinct program. Experimentally, there were 28 structures among those reported in the 34 query publications that were identified within the virtual library. Among these, the frequency of high activity was 87% for the 16 structures whose similarity to their query was 90 topomer units or less, compared to a frequency of 50% for the other 12 structures.

Balancing focused combinatorial libraries based on multiple GPCR ligands

“…The core structure (scaffold) for each target library was created separately, but the initial lists of commercially available reagents defining the extent of the full combinatorial libraries were shared. These lists were drawn from ChemSpace [18], which is a discovery research platform developed at Tripos for building, managing, filtering and searching sets of large combinatorial libraries [12,19,20].…”

“…Distances are computed from the squared field differences across the lattice, summed across the cores and all substituents. The piecemeal distances are relatively large in most cases, so great swaths of the product space can quickly be excluded from further consideration: if the difference between a core subquery and a library core is larger than the designated search radius r p , there is no reason to consider any product from the corresponding library for that particular query fragmentation pattern [19,20].…”

AllChem: generating and searching 1020 synthetically accessible structures

“…AllChem is intended as a successor to ChemSpace [25,26], which has for 10 years provided TDR with similar access to~10 14 structures by manipulating conventional combinatorial libraries, composed of chemist-proposed scaffolds and commercially offered side chains linked together by standard combinatorial chemistry protocols. The most important ChemSpace limitation is that most structures found in the medicinal chemistry literature are not such simple assemblies.…”

Pushing the boundaries of 3D-QSAR

“…First, the cost and time of trying 3D-QSAR on a data set almost disappear (for example, replicating Table 1, starting with only the simple ''2D'' structure activity tables in computer readable form, takes only a few minutes, surely many orders of magnitude less time and effort than the original publications' 3D-QSAR investigations required). Second, topomer-based 3D-QSAR models immediately become search queries into databases composed of other topomer fragments, obtaining results in a few hours with engines such as dbtop [18] (10 6 candidate structures, whose topomer fragments are generated on the fly), ChemSpace [19] (10 13 candidates, each a combination of available topomerized building blocks), and AllChem [20] (10 20 candidates, whose topomerized building blocks are produced by applying short sequences of reactions to available building blocks). Finally, this standardized protocol for generating 3D-QSAR alignments, by eliminating the highly variable and subjective current alignment process along with its time and cost, provides a consistent starting point for addressing other 3D-QSAR issues in greater depth.…”