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2018 ; 19
(2
): 277-285
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English Wikipedia
Data-driven approaches used for compound library design, hit triage and
bioactivity modeling in high-throughput screening
#MMPMID27789427
Paricharak S
; Méndez-Lucio O
; Chavan Ravindranath A
; Bender A
; IJzerman AP
; van Westen GJP
Brief Bioinform
2018[Mar]; 19
(2
): 277-285
PMID27789427
show ga
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.