scholarly journals Computational Analysis of Kinase Inhibitors Identifies Promiscuity Cliffs across the Human Kinome

ACS Omega ◽  
2018 ◽  
Vol 3 (12) ◽  
pp. 17295-17308 ◽  
Author(s):  
Filip Miljković ◽  
Jürgen Bajorath
2016 ◽  
Author(s):  
Zheng Zhao ◽  
Lei Xie ◽  
Philip E. Bourne

AbstractProtein kinases are critical drug targets for treating a large variety of human diseases. Type-I and type-II kinase inhibitors frequently exhibit off-target toxicity or lead to mutation acquired resistance. Two highly specific allosteric type-III MEK-targeted drugs, Trametinib and Cobimetinib, offer a new approach. Thus, understanding the binding mechanism of existing type-III kinase inhibitors will provide insights for designing new type-III kinase inhibitors. In this work we have systematically studied the binding mode of MEK-targeted type-III inhibitors using structural systems pharmacology and molecular dynamics simulation. Our studies provide detailed sequence, structure, interaction-fingerprint, pharmacophore and binding-site information on the binding characteristics of MEK type-III kinase inhibitors. We propose that the helix-folding activation loop is a hallmark allosteric binding site for type-III inhibitors. Subsequently we screened and predicted allosteric binding sites across the human kinome, suggesting other kinases as potential targets suitable for type-III inhibitors. Our findings will provide new insights into the design of potent and selective kinases inhibitors.Author SummaryHuman protein kinases represent a large protein family relevant to many diseases, especially cancers, and have become important drug targets. However, developing the desired selective kinase-targeted inhibitors remain challenging. Kinase allosteric inhibitors provide that opportunity, but, to date, few have been designed other than MEK inhibitors. To more efficiently develop kinase allosteric inhibitors, we systematically studied the binding mode of the MEK type-III allosteric kinase inhibitors using structural system pharmacology and molecular dynamics approaches. New insights into the binding mode and mechanism of type-III inhibitors were revealed that may facilitate the design of new prospective type-III kinase inhibitors.


Oncogene ◽  
2005 ◽  
Vol 25 (9) ◽  
pp. 1340-1348 ◽  
Author(s):  
S Morgan-Lappe ◽  
K W Woods ◽  
Q Li ◽  
M G Anderson ◽  
M E Schurdak ◽  
...  

2014 ◽  
Vol 52 (9) ◽  
pp. 1170-1178 ◽  
Author(s):  
Abdul Wadood ◽  
Syed Babar Jamal ◽  
Muhammad Riaz ◽  
Asif Mir

2017 ◽  
Vol 45 (1) ◽  
pp. 65-77 ◽  
Author(s):  
Akanksha Baharani ◽  
Brett Trost ◽  
Anthony Kusalik ◽  
Scott Napper

There is increasing appreciation among researchers and clinicians of the value of investigating biology and pathobiology at the level of cellular kinase (kinome) activity. Kinome analysis provides valuable opportunity to gain insights into complex biology (including disease pathology), identify biomarkers of critical phenotypes (including disease prognosis and evaluation of therapeutic efficacy), and identify targets for therapeutic intervention through kinase inhibitors. The growing interest in kinome analysis has fueled efforts to develop and optimize technologies that enable characterization of phosphorylation-mediated signaling events in a cost-effective, high-throughput manner. In this review, we highlight recent advances to the central technologies currently available for kinome profiling and offer our perspectives on the key challenges remaining to be addressed.


Biomolecules ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 1546
Author(s):  
Andrea Baier ◽  
Ryszard Szyszka

The advantage of natural compounds is their lower number of side-effects when compared to most synthetic substances. Therefore, over the past several decades, the interest in naturally occurring compounds is increasing in the search for new potent drugs. Natural compounds are playing an important role as a starting point when developing new selective compounds against different diseases. Protein kinases play a huge role in several diseases, like cancers, neurodegenerative diseases, microbial infections, or inflammations. In this review, we give a comprehensive view of natural compounds, which are/were the parent compounds in the development of more potent substances using computational analysis and SAR studies.


2019 ◽  
Vol 5 (7) ◽  
pp. FSO404 ◽  
Author(s):  
Filip Miljković ◽  
Jürgen Bajorath

Aim: A large collection of promiscuity cliffs (PCs), PC pathways (PCPs) and promiscuity hubs (PHs) formed by inhibitors of human kinases is made freely available. Methodology: Inhibitor PCs were systematically identified and organized in network representations, from which PCPs were extracted. PH compounds were classified and their neighborhoods analyzed. Data & exemplary results: Nearly 16,000 PCs covering the human kinome were identified, which yielded more than 600 PC clusters and 8900 PCPs. Moreover, 520 PHs were obtained. Limitations & next steps: PC and PCP data structures capture structure–promiscuity relationships. Promiscuity assessment is also affected by data sparseness. Given the rapid growth of kinase inhibitor data, the relevance of PC/PCP/PH information for medicinal chemistry and chemical biology applications will further increase.


2010 ◽  
Vol 50 (supplement2) ◽  
pp. S160
Author(s):  
Noriyuki Futatsugi ◽  
Noriaki Okimoto ◽  
Atsushi Suenaga ◽  
Hideyosi Fuji ◽  
Tetsu Narumi ◽  
...  

2020 ◽  
Author(s):  
Nienke Moret ◽  
Changchang Liu ◽  
Benjamin M. Gyori ◽  
John A. Bachman ◽  
Albert Steppi ◽  
...  

ABSTRACTThe functions of protein kinases have been widely studied and many kinase inhibitors have been developed into FDA-approved therapeutics. A substantial fraction of the human kinome is nonetheless understudied. In this perspective, members of the NIH Understudied Kinome Consortium mine publicly available databases to assess the functionality of these understudied kinases as well as their potential to be therapeutic targets for drug discovery campaigns. We start with a re-analysis of the kinome as a whole and describe criteria for creating an inclusive set of 710 kinase domains as well as a curated set of 557 protein kinase like (PKL) domains. We define an understudied (‘dark’) kinome by quantifying the public knowledge on each kinase with a PKL domain using an automatic reading machine. We find a substantial number are essential in the Cancer Dependency Map and differentially expressed or mutated in disease databases such as The Cancer Genome Atlas. Based on this and other data, it seems likely that the dark kinome contains biologically important genes, a subset of which may be viable drug targets.


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