The use of novel selectivity metrics in kinase research

Bosc, Nicolas; Meyer, Christophe; Bonnet, Pascal

doi:10.1186/s12859-016-1413-y

Cited by 41 publications

(43 citation statements)

References 59 publications

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“…Alchemical free energy methods can be used to predict compound selectivity While the potency of a ligand for a single target is often quantified as a free energy of binding (Δ ,target ), there are a number of different metrics for quantifying compound selectivity [55,56]. Here, we consider the selectivity between one target and another (an antitarget) as the difference in free energy of binding for a given ligand between the two,…”

Section: Resultsmentioning

confidence: 99%

Is structure based drug design ready for selectivity optimization?

Albanese

Chodera

Volkamer

et al. 2020

Preprint

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AbstractAlchemical free energy calculations are now widely used to drive or maintain potency in small molecule lead optimization with a roughly 1 kcal/mol accuracy. Despite this, the potential to use free energy calculations to drive optimization of compound selectivity among two similar targets has been relatively unexplored in published studies. In the most optimistic scenario, the similarity of binding sites might lead to a fortuitous cancellation of errors and allow selectivity to be predicted more accurately than affinity. Here, we assess the accuracy with which selectivity can be predicted in the context of small molecule kinase inhibitors, considering the very similar binding sites of human kinases CDK2 and CDK9, as well as another series of ligands attempting to achieve selectivity between the more distantly related kinases CDK2 and ERK2. Using a Bayesian analysis approach, we separate systematic from statistical error and quantify the correlation in systematic errors between selectivity targets. We find that, in the CDK2/CDK9 case, a high correlation in systematic errors suggests free energy calculations can have significant impact in aiding chemists in achieving selectivity, while in more distantly related kinases (CDK2/ERK2), the correlation in systematic error suggests fortuitous cancellation may even occur between systems that are not as closely related. In both cases, the correlation in systematic error suggests that longer simulations are beneficial to properly balance statistical error with systematic error to take full advantage of the increase in apparent free energy calculation accuracy in selectivity prediction.

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Section: Resultsmentioning

confidence: 99%

Is structure based drug design ready for selectivity optimization?

Albanese

Chodera

Volkamer

et al. 2020

Preprint

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“…We sent FP1 for kinome profiling against 403 wild-type (WT) kinases at DiscoverX at 1 μM. FP1 demonstrated good selectivity with an S 10 (1 μM) = 0.035 (61), corresponding to 14 kinases with a PoC < 10 at 1 μM ( Fig. 7C ).…”

Section: Resultsmentioning

confidence: 99%

Protein proximity networks and functional evaluation of the Casein Kinase 1 γ family reveals unique roles for CK1γ3 in WNT signaling

Agajanian

Potjewyd

Bowman

et al. 2021

Preprint

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The WNT/β-catenin signaling pathway is evolutionarily conserved and controls normal embryonic development, adult tissue homeostasis and regeneration. Aberrant activation or suppression of WNT signaling contributes to cancer initiation and progression, developmental disorders, neurodegeneration, and bone disease. Despite great need and more than 40 years of research, targeted therapies for the WNT pathway have yet to be fully realized. Kinases are exceptionally druggable and occupy key nodes within the WNT signaling network, but several pathway-relevant kinases remain understudied and ‘dark’. Here we studied the function of the CSNK1γ subfamily of human kinases. miniTurbo-based proximity biotinylation and mass spectrometry analysis of CSNK1γ1, CSNK1γ2, and CSNK1γ3 revealed numerous established components of the β-catenin- dependent and independent WNT signaling pathway, as well as novel interactors. In gain-of- function experiments leveraging a panel of transcriptional reporters, CSNK1γ3 but not CSNK1γ1 or CSNK1γ2 activated β-catenin-dependent WNT signaling and the Notch pathway. Within the family, CSNK1γ3 expression uniquely induced LRP6 phosphorylation. Conversely, siRNA- mediated silencing of CSNK1γ3 alone had no impact on WNT signaling, though co-silencing of all three family members decreased WNT pathway activity. We characterized two moderately selective and potent small molecule inhibitors of the CSNK1γ family. These inhibitors and a CSNK1γ3 kinase dead mutant suppressed but did not eliminate WNT-driven LRP6 phosphorylation and β-catenin stabilization. Our data suggest that while CSNK1γ3 expression uniquely drives pathway activity, potential functional redundancy within the family necessitates loss of all three family members to suppress the WNT signaling pathway.

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“…5 B). Kinome-wide selectivity as well as biochemical potency on BRSK2 and related CAMK family kinases has been published for all except Arcyriaflavin A and K-252c 33 , 34 . In those cases where broad kinase screening data was available in the literature, we calculated the S 10 selectivity scores corresponding to the percentage of kinases inhibited > 90% at the concentration shown is included for each compound versus GW296115 (Fig.…”

Section: Resultsmentioning

confidence: 99%

PKIS deep dive yields a chemical starting point for dark kinases and a cell active BRSK2 inhibitor

Tamir

Drewry

Wells

et al. 2020

Sci Rep

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The Published Kinase Inhibitor Set (PKIS) is a publicly-available chemogenomic library distributed to more than 300 laboratories by GlaxoSmithKline (GSK) between 2011 and 2015 and by SGC-UNC from 2015 to 2017. Screening this library of well-annotated, published kinase inhibitors has yielded a plethora of data in diverse therapeutic and scientific areas, funded applications, publications, and provided impactful pre-clinical results. GW296115 is a compound that was included in PKIS based on its promising selectivity following profiling against 260 human kinases. Herein we present more comprehensive profiling data for 403 wild type human kinases and follow-up enzymatic screening results for GW296115. This more thorough investigation of GW296115 has confirmed it as a potent inhibitor of kinases including BRSK1 and BRSK2 that were identified in the original panel of 260 kinases as well as surfaced other kinases that it potently inhibits. Based on these new kinome-wide screening results, we report that GW296115 is an inhibitor of several members of the Illuminating the Druggable Genome (IDG) list of understudied dark kinases. Specifically, our results establish GW296115 as a potent lead chemical tool that inhibits six IDG kinases with IC50 values less than 100 nM. Focused studies establish that GW296115 is cell active, and directly engages BRSK2. Further evaluation showed that GW296115 downregulates BRSK2-driven phosphorylation and downstream signaling. Therefore, we present GW296115 as a cell-active chemical tool that can be used to interrogate the poorly characterized function(s) of BRSK2.

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The use of novel selectivity metrics in kinase research

Cited by 41 publications

References 59 publications

Is structure based drug design ready for selectivity optimization?

Is structure based drug design ready for selectivity optimization?

Protein proximity networks and functional evaluation of the Casein Kinase 1 γ family reveals unique roles for CK1γ3 in WNT signaling

PKIS deep dive yields a chemical starting point for dark kinases and a cell active BRSK2 inhibitor

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