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Molecular basis for specificity in the druggable kinome: sequence-based analysis.

ABSTRACT: Rational design of kinase inhibitors remains a challenge partly because there is no clear delineation of the molecular features that direct the pharmacological impact towards clinically relevant targets. Standard factors governing ligand affinity, such as potential for intermolecular hydrophobic interactions or for intermolecular hydrogen bonding do not provide good markers to assess cross reactivity. Thus, a core question in the informatics of drug design is what type of molecular similarity among targets promotes promiscuity and what type of molecular difference governs specificity. This work answers the question for a sizable screened sample of the human pharmacokinome including targets with unreported structure.We show that drug design aimed at promoting pairwise interactions between ligand and kinase target actually fosters promiscuity because of the high conservation of the partner groups on or around the ATP-binding site of the kinase. Alternatively, we focus on a structural marker that may be reliably determined from sequence and measures dehydration propensities mostly localized on the loopy regions of kinases. Based on this marker, we construct a sequence-based kinase classifier that enables the accurate prediction of pharmacological differences. Our indicator is a microenvironmental descriptor that quantifies the propensity for water exclusion around preformed polar pairs. The results suggest that targeting polar dehydration patterns heralds a new generation of drugs that enable a tighter control of specificity than designs aimed at promoting ligand-kinase pairwise interactions.The predictor of polar hot spots for dehydration propensity, or solvent-accessible hydrogen bonds in soluble proteins, named YAPView, may be freely downloaded from the University of Chicago website http://protlib.uchicago.edu/dloads.html.Supplementary data are available at Bioinformatics online.

SUBMITTER: Chen J

PROVIDER: S-EPMC1950445 | biostudies-literature | 2007 Mar

REPOSITORIES: biostudies-literature

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Molecular basis for specificity in the druggable kinome: sequence-based analysis.

Chen Jianping J Zhang Xi X Fernández Ariel A

Bioinformatics (Oxford, England) 20070125 5

<h4>Motivation</h4>Rational design of kinase inhibitors remains a challenge partly because there is no clear delineation of the molecular features that direct the pharmacological impact towards clinically relevant targets. Standard factors governing ligand affinity, such as potential for intermolecular hydrophobic interactions or for intermolecular hydrogen bonding do not provide good markers to assess cross reactivity. Thus, a core question in the informatics of drug design is what type of mole ...[more]

PMID: 17255140

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Project description:Human cytomegalovirus (HCMV) is a significant cause of disease in immune-compromised adults and immune naïve newborns. No vaccine exists to prevent HCMV infection, and current antiviral therapies have toxic side effects that limit the duration and intensity of their use. There is thus an urgent need for new strategies to treat HCMV infection. Repurposing existing drugs as antivirals is an attractive approach to limit the time and cost of new antiviral drug development. Virus-induced changes in infected cells are often driven by changes in cellular kinase activity, which led us to hypothesize that defining the complement of kinases (the kinome), whose abundance or expression is altered during infection would identify existing kinase inhibitors that could be repurposed as new antivirals. To this end, we applied a kinase capture technique, multiplexed kinase inhibitor bead-mass spectrometry (MIB-MS) kinome, to quantitatively measure perturbations in >240 cellular kinases simultaneously in cells infected with a laboratory-adapted (AD169) or clinical (TB40E) HCMV strain. MIB-MS profiling identified time-dependent increases and decreases in MIB binding of multiple kinases including cell cycle kinases, receptor tyrosine kinases, and mitotic kinases. Based on the kinome data, we tested the antiviral effects of kinase inhibitors and other compounds, several of which are in clinical use or development. Using a novel flow cytometry-based assay and a fluorescent reporter virus we identified three compounds that inhibited HCMV replication with IC50 values of <1 μm, and at doses that were not toxic to uninfected cells. The most potent inhibitor of HCMV replication was OTSSP167 (IC50 <1.2 nm), a MELK inhibitor, blocked HCMV early gene expression and viral DNA accumulation, resulting in a >3 log decrease in virus replication. These results show the utility of MIB-MS kinome profiling for identifying existing kinase inhibitors that can potentially be repurposed as novel antiviral drugs.

Project description:Multiple sequence alignments (MSAs) are a fundamental analysis tool used throughout biology to investigate relationships between protein sequence, structure, function, evolutionary history, and patterns of disease-associated variants. However, their widespread application in systems biology research is currently hindered by the lack of user-friendly tools to simultaneously visualize, manipulate and query the information conceptualized in large sequence alignments, and the challenges in integrating MSAs with multiple orthogonal data such as cancer variants and post-translational modifications, which are often stored in heterogeneous data sources and formats. Here, we present the Multiple Sequence Alignment Ontology (MSAOnt), which represents a profile or consensus alignment in an ontological format. Subsets of the alignment are easily selected through the SPARQL Protocol and RDF Query Language for downstream statistical analysis or visualization. We have also created the Kinome Viewer (KinView), an interactive integrative visualization that places eukaryotic protein kinase cancer variants in the context of natural sequence variation and experimentally determined post-translational modifications, which play central roles in the regulation of cellular signaling pathways. Using KinView, we identified differential phosphorylation patterns between tyrosine and serine/threonine kinases in the activation segment, a major kinase regulatory region that is often mutated in proliferative diseases. We discuss cancer variants that disrupt phosphorylation sites in the activation segment, and show how KinView can be used as a comparative tool to identify differences and similarities in natural variation, cancer variants and post-translational modifications between kinase groups, families and subfamilies. Based on KinView comparisons, we identify and experimentally characterize a regulatory tyrosine (Y177PLK4) in the PLK4 C-terminal activation segment region termed the P+1 loop. To further demonstrate the application of KinView in hypothesis generation and testing, we formulate and validate a hypothesis explaining a novel predicted loss-of-function variant (D523NPKCβ) in the regulatory spine of PKCβ, a recently identified tumor suppressor kinase. KinView provides a novel, extensible interface for performing comparative analyses between subsets of kinases and for integrating multiple types of residue specific annotations in user friendly formats.

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Molecular basis for specificity in the druggable kinome: sequence-based analysis.

Publications

Molecular basis for specificity in the druggable kinome: sequence-based analysis.

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