Identifying representative kinases for inhibitor evaluation via systematic analysis of compound-based target relationships

Laufkötter, Oliver; Laufer, Stefan; Bajorath, Jürgen

doi:10.1016/j.ejmech.2020.112641

Cited by 6 publications

(13 citation statements)

References 31 publications

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“…The source of multi-kinase inhibitor data set was an in-house compiled database of human kinase inhibitors assembled from public repositories comprising 112,624 unique inhibitors with activity against 426 kinases [1] . As potency measurements, IC 50 , K i , or K d values were mostly used.…”

Section: Experimental Design Materials and Methodsmentioning

confidence: 99%

“… A large set of multi-kinase inhibitors with high-confidence activity data was assembled and used to generate network representations revealing kinase relationships based upon shared inhibitors [1] . Compounds and activity annotations were originally selected from public repositories and organized in an in-house database from which the data set was extracted and curated.…”

mentioning

confidence: 99%

“…The new data set comprises more than 36,000 inhibitors with multiple activity annotations for a total of 420 human kinases (providing 81% coverage of the human kinome), representing a total of ∼127,000 kinase-inhibitor interactions. Use of the data is not limited to the network application reported in [1] . It can also be used, for example, for different types of compound promiscuity analysis or machine learning (such a multi-task modeling).…”

mentioning

confidence: 99%

“…Value of the Data The large curated set of multi-kinase inhibitors with 81% coverage of the human kinome provides an extensive resource for promiscuity analysis and the exploration of inhibitor-based kinase relationships. Systematic organization of these relationships enabled the identification of small sets of kinases whose inhibitor binding profiles are representative of many others [1] . The data set is designed to complement kinase drug discovery projects in academia and the pharmaceutical industry by providing a wealth of inhibitor information for kinases of interest as well as template compounds for multi-kinase drug design.…”

mentioning

confidence: 99%

“…The large curated set of multi-kinase inhibitors with 81% coverage of the human kinome provides an extensive resource for promiscuity analysis and the exploration of inhibitor-based kinase relationships. Systematic organization of these relationships enabled the identification of small sets of kinases whose inhibitor binding profiles are representative of many others [1] .…”

mentioning

confidence: 99%

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Kinase inhibitor data set for systematic analysis of representative kinases across the human kinome

2020

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A large set of multi-kinase inhibitors with high-confidence activity data was assembled and used to generate network representations revealing kinase relationships based upon shared inhibitors [1] . Compounds and activity annotations were originally selected from public repositories and organized in an in-house database from which the data set was extracted and curated. The new data set comprises more than 36,000 inhibitors with multiple activity annotations for a total of 420 human kinases (providing 81% coverage of the human kinome), representing a total of ∼127,000 kinase-inhibitor interactions. Use of the data is not limited to the network application reported in [1] . It can also be used, for example, for different types of compound promiscuity analysis or machine learning (such a multi-task modeling). In addition, the data set provides a large resource for complementing kinase drug discovery projects with external compound information.

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Section: Experimental Design Materials and Methodsmentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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Kinase inhibitor data set for systematic analysis of representative kinases across the human kinome

2020

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PT-Finder: A multi-modal neural network approach to target identification

Nada,

Kim,

Lee

2024

Computers in Biology and Medicine

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Design and Optimization of Novel Benzimidazole- and Imidazo[4,5-b]pyridine-Based ATM Kinase Inhibitors with Subnanomolar Activities

Dimitrov,

Moschopoulou,

Seidel

et al. 2023

J. Med. Chem.

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The ATM kinase is a promising target in cancer treatment as an important regulator of the cellular response to DNA double-strand breaks. In this work, we present a new class of specific benzimidazole-based ATM inhibitors with picomolar potency against the isolated enzyme and favorable selectivity within relative PIKK and PI3K kinases. We could identify two promising inhibitor subgroups with significantly different physicochemical properties, which we developed simultaneously. These efforts lead to numerous highly active inhibitors with picomolar enzymatic activities. Furthermore, initial low cellular activities on A549 cells could be increased significantly in numerous examples resulting in cellular IC50 values in the subnanomolar range. Further characterization of the highly potent inhibitors 90 und 93 revealed promising pharmacokinetic properties and strong activities in organoids in combination with etoposide. Additionally, 93 showed no off-target activities within a kinome-representative mini kinase panel, with favorable selectivities within the PIKK- and PI3K-families.

show abstract

Identifying representative kinases for inhibitor evaluation via systematic analysis of compound-based target relationships

Cited by 6 publications

References 31 publications

Kinase inhibitor data set for systematic analysis of representative kinases across the human kinome

Kinase inhibitor data set for systematic analysis of representative kinases across the human kinome

PT-Finder: A multi-modal neural network approach to target identification

Design and Optimization of Novel Benzimidazole- and Imidazo[4,5-b]pyridine-Based ATM Kinase Inhibitors with Subnanomolar Activities

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