There is a newer version of the record available.

Published April 15, 2023 | Version v1
Dataset Open

Kinase ChemoGenomic Set (KCGS) v 2.0 data set

  • 1. The University of North Carolina at Chapel Hill

Description

Here we briefly describe the latest iteration of our kinase chemogenomic set, progressing toward eventual total kinome coverage. This new edition is called KCGS2.0.

Our kinase chemogenomic set (KCGS) comprises well-annotated inhibitors that target kinases with potent activity but have what we consider narrow-spectrum activity across the kinome. Our goal is to continue growing the set until we have one to three inhibitors for each human kinase. When we reach this point, the set can in principle, be used to determine the relevance and/or function of each kinase in the context of interest. Individually each inhibitor is not promiscuous, and each has defined activity on a narrow set of kinases. When the set is screened in disease-relevant phenotypic assays, one can infer kinase vulnerability based on the results and follow up with more detailed experiments on kinases of interest to confirm the hypothesized dependence.

We have now added additional compounds to KCGS1.0 and created KCGS2.0 affording expanded breadth (more kinases covered) and depth (additional chemotypes for kinase) of coverage. The set is being distributed through cancertools.org, Cancer Research UK's research tools arm. Follow this link (https://www.cancertools.org/tools ) and search for KCGS at this tools page.

Frequently Asked Questions

In the summary spreadsheet, what does the S10 (1 mM) mean?

S10 (1 mM) is a selectivity metric generated from Discoverx broad kinome screening data. It is the number of kinases with PoC<10 (equivalent to 90%I) divided by the number of wild type (non-mutant) kinases screened (generally 403 kinases here). In our case we screened inhibitors at a concentration of 1 micromolar, thus, the S10 (1 mM). Smaller S10 values represent a more selective compound. Of course, this is an imperfect selectivity measure.

Do you have the same data on all the compounds?

We don’t. Compounds that ended up in KCGS2.0 but started in PKIS may only have data from the Nanosyn panel of assays we ran at that time. In that PKIS experiment we screened compounds at 100 nM and 1 micromolar. In the spreadsheet of KCGS2.0 summary data, any reference to Nanosyn is talking about the data from the 1 micromolar screening at Nanosyn. Please check out the PKIS paper and supplemental information for more information on the Nanosyn data. Here is the pubmed link: https://pubmed.ncbi.nlm.nih.gov/26501955/

Compounds from PKIS2 that ended up in KCGS2.0 have broad screening data from the Discoverx panel of assays. The work around KCGS is described here: https://pubmed.ncbi.nlm.nih.gov/33429995/. Please refer to this paper for more detail on the design of KCGS and the use of KCGS. These same guidelines were used in expanding to KCGS2.0; so many of your KCGS2.0 questions may be answered by reading through that paper.

The brand-new compound additions that turn KCGS into KCGS2.0 comes with new, and for the most part unpublished, Discoverx kinome scan data. We have added compounds that cover new kinases (increased breadth of coverage) as well as adding new chemotypes for some kinases (increased depth of coverage).

Are all the compounds exquisitely selective?

Initially we strived for S10 (1 mM) < 0.03 or so. Many of the compounds only had Nanosyn data initially. We have now tested many of those in the kinomescan assay, and that is reflected in the screening column (KCGS2.0 data overview spreadsheet) if it says “Nanosyn, Discoverx”. These two assay panels are different (but with many overlapping kinases) and completely different assay formats. In some cases, testing in the Discoverx panel has surfaced additional kinase targets, meaning that compounds with less-than-ideal selectivity are in the set. This just means users of the set need to take this into account as hits from phenotypic screens are followed up.

What are the references you provide in the “reference” column?

When we started building kinase chemogenomic sets and designing new kinase inhibitors, our premise was that we could use kinase inhibitors made for one target as starting points for other kinase targets. The "reference" column provides the original med chem references that report a number of these compounds. If one of these compounds hits in your assay, I encourage you to check out the original paper in case it offers any additional insights. Apologies if we have missed some references. This exercise has demonstrated that useful inhibitors for "other", often unrelated, kinases can be identified by broad screening of compounds made in medicinal campaigns for another kinase.

If I get a hit from compound do I know with certainty that the target is critical for my phenotype?

Screening the set will generate hypotheses for you to explore. Any hit in a phenotypic assay needs to be followed up carefully. Of course, looking at the list of targets in row I (target data: generally, Kd<100 nM and/or %I>90 (screened at 1 mM)) is a great place to start. Remember there COULD be other targets. We have not screened all kinases, for example. In addition, S10 (1 mM) is an imperfect selectivity metric. We have highlighted targets with Kd or IC50 < 100 nM, or with >90%I at 1 uM. Targets just slightly weaker than this could also lead to (or contribute to) a phenoytpe. Of course, there may be a chance a compound binds to a nonkinase target. For hits of interest, ALL possibilities should be considered as you seek to link compound to target to mechanism and phenotype.

----------------------------------------------

For additional information and to leave feedback, click here: openlabnotebooks

----------------------------------------------

Files

Files (87.2 kB)

Additional details

Funding

National Institutes of Health
Illuminating Function of the Understudied Druggable Kinome 1U24DK116204-01
European Commission
ULTRA-DD - Unrestricted Leveraging of Targets for Research Advancement and Drug Discovery 115766