Understanding Of Kinases Research Articles

The Conformational Transition Pathways and Hidden Intermediates in DFG-Flip Process of c-Met Kinase Revealed by Metadynamics Simulations.

Protein kinases intrinsically translate their conformations between active and inactive states, which is key to their enzymatic activities. The conformational flipping of the three-residue conservative motif, Asp-Phe-Gly (DFG), is crucial for many kinases' biological functions. Obtaining a detailed demonstration of the DFG flipping process and its corresponding dynamical and thermodynamical features could broaden our understanding of kinases' conformation-activity relationship. In this study, we employed metadynamics simulation, a widely used enhanced sampling technique, to analyze the conformational transition pathways of the DFG flipping for the c-Met kinase. The corresponding free energy landscape suggested two distinct transition pathways between the "DFG-in" and "DFG-out" states of the DFG-flip from c-Met. On the basis of the orientation direction of the F1223 residue, we correspondingly named the two pathways the "DFG-up" path, featuring forming a commonly discovered "DFG-up" transition state, and the "DFG-down" path, a unique transition pathway with F1223 rotating along the opposite direction away from the hydrophobic cavity. The free energies along the two pathways were then calculated using the Path Collective Variable (PCV) metadynamics simulation. The simulation results showed that, though having similar free energy barriers, the free energy cuve for the DFG-down path suggested a two-step conformational transition mechanism, while that for the DFG-up path showed the one-step transition feature. The c-Met DFG flipping mechanism and the new intermediate state discovered in this work could provide a deeper understanding of the conformation-activity relationship for c-Met and, possibly, reveal a new conformational state as the drug target for c-Met and other similar kinases.

Pan-Cancer Analysis of Human Kinome Gene Expression and Promoter DNA Methylation Identifies Dark Kinase Biomarkers in Multiple Cancers

Simple SummaryDue to their central role in many biological processes, studies on protein kinases are an area of active research. In the last few decades, several inhibitors that target kinases have been approved by U.S. Food and Drug Administration (FDA). However, a large proportion of kinases remain uncharacterized, with very little information on their functionality. Variations in genome-wide DNA methylation and gene expression pattern have been extensively studied in many cancers. However, an extensive kinome-centered pan-cancer methylation and expression analysis are still lacking. This study aims to identify prognostic and diagnostic biomarkers, focusing on uncharacterized (dark) kinases to further encourage their research as therapeutic targets.Kinases are a group of intracellular signaling molecules that play critical roles in various biological processes. Even though kinases comprise one of the most well-known therapeutic targets, many have been understudied and therefore warrant further investigation. DNA methylation is one of the key epigenetic regulators that modulate gene expression. In this study, the human kinome’s DNA methylation and gene expression patterns were analyzed using the level-3 TCGA data for 32 cancers. Unsupervised clustering based on kinome data revealed the grouping of cancers based on their organ level and tissue type. We further observed significant differences in overall kinase methylation levels (hyper- and hypomethylation) between the tumor and adjacent normal samples from the same tissue. Methylation expression quantitative trait loci (meQTL) analysis using kinase gene expression with the corresponding methylated probes revealed a highly significant and mostly negative association (~92%) within 1.5 kb from the transcription start site (TSS). Several understudied (dark) kinases (PKMYT1, PNCK, BRSK2, ERN2, STK31, STK32A, and MAPK4) were also identified with a significant role in patient survival. This study leverages results from multi-omics data to identify potential kinase markers of prognostic and diagnostic importance and further our understanding of kinases in cancer.

Negative regulation of initial steps in skeletal myogenesis by mTOR and other kinases.

The transition from a committed progenitor cell to one that is actively differentiating represents a process that is fundamentally important in skeletal myogenesis. Although the expression and functional activation of myogenic regulatory transcription factors (MRFs) are well known to govern lineage commitment and differentiation, exactly how the first steps in differentiation are suppressed in a proliferating myoblast is much less clear. We used cultured mammalian myoblasts and an RNA interference library targeting 571 kinases to identify those that may repress muscle differentiation in proliferating myoblasts in the presence or absence of a sensitizing agent directed toward CDK4/6, a kinase previously established to impede muscle gene expression. We identified 55 kinases whose knockdown promoted myoblast differentiation, either independently or in conjunction with the sensitizer. A number of the hit kinases could be connected to known MRFs, directly or through one interaction node. Focusing on one hit, Mtor, we validated its role to impede differentiation in proliferating myoblasts and carried out mechanistic studies to show that it acts, in part, by a rapamycin-sensitive complex that involves Raptor. Our findings inform our understanding of kinases that can block the transition from lineage commitment to a differentiating state in myoblasts and offer a useful resource for others studying myogenic differentiation.

Dataset from the global phosphoproteomic mapping of early mitotic exit in human cells.

The presence or absence of a phosphorylation on a substrate at any particular point in time is a functional readout of the balance in activity between the regulatory kinase and the counteracting phosphatase. Understanding how stable or short-lived a phosphorylation site is required for fully appreciating the biological consequences of the phosphorylation. Our current understanding of kinases and their substrates is well established; however, the role phosphatases play is less understood. Therefore, we utilized a phosphatase dependent model of mitotic exit to identify potential substrates that are preferentially dephosphorylated. Using this method, we identified >16,000 phosphosites on >3300 unique proteins, and quantified the temporal phosphorylation changes that occur during early mitotic exit (McCloy et al., 2015 [1]). Furthermore, we annotated the majority of these phosphorylation sites with a high confidence upstream kinase using published, motif and prediction based methods. The results from this study have been deposited into the ProteomeXchange repository with identifier PXD001559. Here we provide additional analysis of this dataset; for each of the major mitotic kinases we identified motifs that correlated strongly with phosphorylation status. These motifs could be used to predict the stability of phosphorylated residues in proteins of interest, and help infer potential functional roles for uncharacterized phosphorylations. In addition, we provide validation at the single cell level that serine residues phosphorylated by Cdk are stable during phosphatase dependent mitotic exit. In summary, this unique dataset contains information on the temporal mitotic stability of thousands of phosphorylation sites regulated by dozens of kinases, and information on the potential preference that phosphatases have at both the protein and individual phosphosite level. The compellation of this data provides an invaluable resource for the wider research community.

Abstract A4: Two dimensional chemical interrogation of oncogenic systems and multi-omics integration of signatures reveals novel signaling pathways involved in the pathophysiology of cancer

Abstract Oncogenic events involve activation of kinases either in case of direct mutation or as a secondary event as recipients and mediators of oncogenic signals. Kinases transduce signals that lead to cell proliferation or inhibition of programmed cell death by activating transcription factors and inhibiting pro apoptotic molecules. Despite the knowledge and huge market for the kinases as targets, small molecule modulators have failed repeatedly to deliver as cancer therapeutics. Primarily, the failure is thought to stem from the lack of kinase discovery platforms that enable a mechanistic understanding of signaling pathways involving transmembrane and cytoplasmic kinases. The Berg Interrogative Biology® Kinase Discovery Platform offers novel technology driven solutions for understanding of kinases in oncogenesis. The approach is powered by “two-dimensional chemical interrogation” where in vitro cancer and control models were interrogated by a kinase inhibitor (sorafenib) in the first dimension. Overall changes in kinase activity were captured by a second dimension of chemical interrogation employing activity-based kinase enrichment probes. Kinases were identified by LC-MS based mass spectrometry. In addition, changes in phospho proteome in response to kinase inhibitor were captured using a phosphoprotein enrichment method followed by LC-MS for identification of proteins. Finally quantitative changes in total protein expression were obtained. Multi-omics data collated from the above mentioned approach was integrated using an AI-based informatics tool leading to generation of data-driven inference of causal networks representing differential kinase activity driving phosphorylation of proteins that are operational in cancer and not in normal models. The technology platform led to discovery of novel kinases that are mechanistically relevant to pathophysiology of cancer. Citation Format: Vivek K. Vishnudas, Min Du, Viatscheslav Akmaev, Rangaprasad Sarangarajan, Niven R. Narain. Two dimensional chemical interrogation of oncogenic systems and multi-omics integration of signatures reveals novel signaling pathways involved in the pathophysiology of cancer [abstract]. In: Proceedings of the AACR Special Conference on Chemical Systems Biology: Assembling and Interrogating Computational Models of the Cancer Cell by Chemical Perturbations; 2012 Jun 27-30; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2012;72(13 Suppl):Abstract nr A4.