Chemogenomics‐Based Design of GPCR‐Targeted Libraries Using Data Mining Techniques

Balakin, Konstantin V.; Bovina, Elena

doi:10.1002/9780470567623.ch6

Cited by 1 publication

(1 citation statement)

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“…Approaches suggested for library design include focused design for target classes such as G Protein-Coupled Receptors (GPCRs) or kinases with many known active chemotypes [ 2 , 16 , 17 ], and diversity-based design for target classes with few known active chemotypes or for phenotypic assays. For the latter, structural diversity in screening libraries is preferred, as this can increase the chances of finding multiple promising scaffolds for further development across a wide range of assays [ 18 , 19 ].…”

Section: Introductionmentioning

confidence: 99%

Data-driven approaches used for compound library design, hit triage and bioactivity modeling in high-throughput screening

et al. 2016

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High-throughput screening (HTS) campaigns are routinely performed in pharmaceutical companies to explore activity profiles of chemical libraries for the identification of promising candidates for further investigation. With the aim of improving hit rates in these campaigns, data-driven approaches have been used to design relevant compound screening collections, enable effective hit triage and perform activity modeling for compound prioritization. Remarkable progress has been made in the activity modeling area since the recent introduction of large-scale bioactivity-based compound similarity metrics. This is evidenced by increased hit rates in iterative screening strategies and novel insights into compound mode of action obtained through activity modeling. Here, we provide an overview of the developments in data-driven approaches, elaborate on novel activity modeling techniques and screening paradigms explored and outline their significance in HTS.

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