Carcinogenic Activity of 2-N,N-Dimethylamino-5-phenylazopyridine<sup>1</sup>

Brown, Ellis V.; Smetana, Andrew F.; Hamdan, Ali

doi:10.1021/jm00326a024

Cited by 4 publications

(1 citation statement)

References 2 publications

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“…Algorithms to perform diverse molecular selection, traditionally using dissimilarity, clustering, or partitioning approaches, have been reviewed and discussed previously in the literature. − Commonly used methods are the MaxMin dissimilarity-based selection, Sphere Exclusion clustering, and k-Means clustering. , These methods, however, are not typically used for R-groups and tend to use topological descriptors which do not explicitly describe the placements of pharmacophore features in 3D Euclidean space, so are not well suited for the purpose outlined here. Furthermore, dissimilarity-based approaches have been found to select compounds from the “edges” of chemical space, resulting in sets with high complexity .…”

Section: Introductionmentioning

confidence: 99%

bbSelect – An Open-Source Tool for Performing a 3D Pharmacophore-Driven Diverse Selection of R-Groups

Rianjongdee,

Palmer,

Pickett

et al. 2024

J. Chem. Inf. Model.

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The design of compounds during hit-to-lead often seeks to explore a vector from a core scaffold to form additional interactions with the target protein. A rational approach to this is to probe the region of a protein accessed by a vector with a systematic placement of pharmacophore features in 3D, particularly when bound structures are not available. Herein, we present bbSelect, an open-source tool built to map the placements of pharmacophore features in 3D Euclidean space from a library of R-groups, employing partitioning to drive a diverse and systematic selection to a user-defined size. An evaluation of bbSelect against established methods exemplified the superiority of bbSelect in its ability to perform diverse selections, achieving high levels of pharmacophore feature placement coverage with selection sizes of a fraction of the total set and without the introduction of excess complexity. bbSelect also reports visualizations and rationale to enable users to understand and interrogate results. This provides a tool for the drug discovery community to guide their hit-to-lead activities.

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