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Zheng Zhao

Publications and source records attributed to Zheng Zhao.

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

Protein 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.\n\nAuthor 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.

Pharmacology and Toxicology

Genome-wide DNA methylome analysis reveals novel epigenetically dysregulated non-coding RNAs in human breast cancer

The development of human breast cancer is driven by changes in the genetic and epigenetic landscape of the cell. Despite growing appreciation of the importance of epigenetics in breast cancers, our knowledge of epigenetic alterations of non-coding RNAs (ncRNAs) in breast cancers remains limited. Here, we explored the epigenetic patterns of ncRNAs in breast cancers via a sequencing-based comparative methylome analysis, mainly focusing on two most popular ncRNA biotypes, long non-coding RNAs (lncRNAs) and miRNAs. Besides global hypomethylation and extensive CpG islands (CGIs) hypermethylation, we observed widely aberrant methylation in the promoters of ncRNAs, which was higher than that of protein-coding genes. Specifically, intergenic ncRNAs were observed to contribute a large slice of the aberrantly methylated ncRNA promoters. Moreover, we summarized five patterns of ncRNA promoter aberrant methylation in the context of genomic CGIs, where aberrant methylation occurred not only on the CGIs, but also flanking regions and CGI sparse promoters. Integration with transcriptional datasets, we found that the ncRNA promoter methylation events were associated with transcriptional changes. Furthermore, a panel of ncRNAs were identified as biomarkers that were able to discriminate between disease phenotypes (AUCs>0.90). Finally, the potential functions for aberrantly methylated ncRNAs were predicted based on similar patterns, adjacency and/or target genes, highlighting that ncRNAs and coding genes coordinately mediated pathways dysregulation in the development and progression of breast cancers. This study presents the aberrant methylation patterns of ncRNAs, which will be a highly valuable resource for investigations at understanding epigenetic regulation of breast cancers.\n\n[Supplemental material is available online at www.genome.org.]

Bioinformatics