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
Keyword(s):  
Computational Analysis ◽  
Kinase Inhibitors ◽  
Human Kinome ◽  
Promiscuity Cliffs

scholarly journals Insights into the binding mode of MEK type-III inhibitors. A step towards discovering and designing allosteric kinase inhibitors across the human kinome

2016 ◽  
Author(s):  
Zheng Zhao ◽  
Lei Xie ◽  
Philip E. Bourne
Keyword(s):  
Molecular Dynamics ◽  
Binding Site ◽  
Protein Kinases ◽  
Drug Targets ◽  
Kinase Inhibitors ◽  
Binding Mode ◽  
Dynamics Simulation ◽  
Allosteric Inhibitors ◽  
Type Iii ◽  
Human Kinome

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.

scholarly journals RNAi-based screening of the human kinome identifies Akt-cooperating kinases: a new approach to designing efficacious multitargeted 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 ◽  
...  
Keyword(s):  
Kinase Inhibitors ◽  
New Approach ◽  
Human Kinome

Computational analysis of benzofuran-2-carboxlic acids as potent Pim-1 kinase inhibitors

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

Technological advances for interrogating the human kinome

2017 ◽  
Vol 45 (1) ◽  
pp. 65-77 ◽  
Author(s):  
Akanksha Baharani ◽  
Brett Trost ◽  
Anthony Kusalik ◽  
Scott Napper
Keyword(s):  
High Throughput ◽  
Therapeutic Intervention ◽  
Therapeutic Efficacy ◽  
Kinase Inhibitors ◽  
Cost Effective ◽  
Disease Prognosis ◽  
Technological Advances ◽  
Human Kinome ◽  
High Throughput Manner

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.

scholarly journals Compounds from Natural Sources as Protein Kinase Inhibitors

Biomolecules ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 1546
Author(s):  
Andrea Baier ◽  
Ryszard Szyszka
Keyword(s):  
Computational Analysis ◽  
Kinase Inhibitors ◽  
Natural Compounds ◽  
Lower Number ◽  
Protein Kinase Inhibitors ◽  
The Past ◽  
Sar Studies ◽  
Naturally Occurring ◽  
Starting Point ◽  
Microbial Infections

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.

scholarly journals Data structures for compound promiscuity analysis: promiscuity cliffs, pathways and promiscuity hubs formed by inhibitors of the human kinome

2019 ◽  
Vol 5 (7) ◽  
pp. FSO404 ◽  
Author(s):  
Filip Miljković ◽  
Jürgen Bajorath
Keyword(s):  
Data Structures ◽  
Rapid Growth ◽  
Chemical Biology ◽  
Medicinal Chemistry ◽  
Kinase Inhibitor ◽  
Large Collection ◽  
Data Sparseness ◽  
Compound Promiscuity ◽  
Human Kinome ◽  
Promiscuity Cliffs

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.

scholarly journals 3P089 Computational Analysis on Selectivity of Protein Kinase Inhibitors(Protein: Function,The 48th Annual Meeting of the Biophysical Society of Japan)

2010 ◽  
Vol 50 (supplement2) ◽  
pp. S160
Author(s):  
Noriyuki Futatsugi ◽  
Noriaki Okimoto ◽  
Atsushi Suenaga ◽  
Hideyosi Fuji ◽  
Tetsu Narumi ◽  
...  
Keyword(s):  
Protein Kinase ◽  
Annual Meeting ◽  
Protein Function ◽  
Computational Analysis ◽  
Kinase Inhibitors ◽  
Protein Kinase Inhibitors ◽  
Biophysical Society

scholarly journals Exploring the understudied human kinome for research and therapeutic opportunities

2020 ◽  
Author(s):  
Nienke Moret ◽  
Changchang Liu ◽  
Benjamin M. Gyori ◽  
John A. Bachman ◽  
Albert Steppi ◽  
...  
Keyword(s):  
Drug Targets ◽  
Kinase Inhibitors ◽  
The Cancer Genome Atlas ◽  
Public Knowledge ◽  
Substantial Fraction ◽  
The Public ◽  
Cancer Genome Atlas ◽  
Automatic Reading ◽  
Human Kinome ◽  
Genome Atlas

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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