Mouna Choura

Receptor tyrosine kinases: from biology to pathology

Receptor tyrosine kinases (RTKs) are transmembrane proteins involved in the control of fundamental cellular processes in metazoans. RTKs possess a general structure that includes an extracellular domain, a transmembrane domain and a highly conserved tyrosine kinase domain. RTKs are classified according to their variable extracellular ligand-binding domain. Studies of human RTK members have yielded a wealth of information elucidating their importance. Improper functioning of these enzymes due to mutations, mainly in the kinase domain, is often manifested in various human diseases and is known to be involved in several types of cancer. Here we summarize most of human RTKs, their cognate ligands, as well as related diseases and discuss the eventual use of certain RTKs as new therapeutic targets.

Application of computational approaches to study signalling networks of nuclear and Tyrosine kinase receptors

BackgroundNuclear receptors (NRs) and Receptor tyrosine kinases (RTKs) are essential proteins in many cellular processes and sequence variations in their genes have been reported to be involved in many diseases including cancer. Although crosstalk between RTK and NR signalling and their contribution to the development of endocrine regulated cancers have been areas of intense investigation, the direct coupling of their signalling pathways remains elusive. In our understanding of the role and function of nuclear receptors on the cell membrane the interactions between nuclear receptors and tyrosine kinase receptors deserve further attention.ResultsWe constructed a human signalling network containing nuclear receptors and tyrosine kinase receptors that identified a network topology involving eleven highly connected hubs.We further developed an integrated knowledge database, denominated NR-RTK database dedicated to human RTKs and NRs and their vertebrate orthologs and their interactions. These interactions were inferred using computational tools and those supported by literature evidence are indicated. NR-RTK database contains links to other relevant resources and includes data on receptor ligands. It aims to provide a comprehensive interaction map that identifies complex dynamics and potential crosstalk involved.Availability: NR-RTK database is accessible at http://www.bioinfo-cbs.org/NR-RTK/ConclusionsWe infer that the NR-RTK interaction network is scale-free topology. We also uncovered the key receptors mediating the signal transduction between these two types of receptors. Furthermore, NR-RTK database is expected to be useful for researchers working on various aspects of the molecular basis of signal transduction by RTKs and NRs.ReviewersThis article was reviewed by Professor Paul Harrison (nominated by Dr. Mark Gerstein), Dr. Arcady Mushegian and Dr. Anthony Almudevar.

Exploring charged biased regions in the human proteome.

There has been an increasing interest in biased regions in proteins especially ever since it was shown that such regions are frequently associated with a structural role in the cell, or with protein disorder. In this study, we focus on charged biased protein sequences in human genome. We have identified 446 charged biased proteins within human proteome, 70% of them constitute proteins harboring negative run that correspond to transcription factor zinc finger proteins, importins and some protein kinases involving acidic activating domains. Basic charge clusters are often associated with DNA-binding, zinc-finger, basic-leucine zipper and homeobox domains. The data show that significant positive clusters correspond to ribosomal proteins. Most of proteins with zinc-binding fingers have a mixed positive and negative charged biased regions. Altogether, the Gene Ontology analysis revealed that the charged proteins are involved mainly in regulatory functions.

Topological features of cancer proteins in the human NR-RTK interaction network.

Protein–protein interaction (PPI) network analysis has been considered as a useful approach to explore the mechanisms of complex diseases, such as cancer. To date, many proteins have been reported to involve in the development of cancer. Exploration of cancer proteins in the human PPI network may provide important biological information to uncover molecular mechanisms of cancer. Here, we have explored network characteristics (including degree, betweenness, clustering coefficient and shortest-path distance) of cancer proteins of the human nuclear and tyrosine kinases receptors network (NR-RTK) constructed in our earlier work. We found that the network topology of cancer proteins in this network have some specific features. Relative to the non-cancer proteins, the cancer proteins have likely higher degree, higher betweenness, similar clustering coefficient and similar shortest-path distance. Finally, we found that the cancer proteins were involved mainly in signalling pathways which dysfunction is directly related to cancer onset. These findings are helpful for cancer candidate protein prioritization and verification, and identification of key pathways involved in cancer disease.

Investigating the Function of Three Non-Synonymous SNPs in EGFR Gene: Structural Modelling and Association With Breast Cancer

Non-synonymous single nucleotide polymorphisms (nsSNPs) represent common genomic variations that alter protein sequence and function. Some nsSNPs affecting conserved amino acids have been reported to be associated with cancer susceptibility. Interestingly, Epidermal Growth Factor Receptor (EGFR) is commonly overexpressed and mutated in many cancers. In this study, we investigated the structural effect of three deleterious nsSNPs: rs17337451 (R962G), rs1140476 (R977C) and rs17290699 (H988P) within EGFR using computational tools. The modelled mutant dimers showed less stability than wild type EGFR dimer. Furthermore, we showed the important role of R962 and H988 residues in the EGFR dimer formation. We also report preliminary experimental data for SNP R977C suggesting that the variant C977 might confer greater risk for breast cancer. These results contribute to an improved understanding of the EGFR dimer stability and provide new elements for understanding the relationship between EGFR and cancer.

Applications of computational tools to predict functional SNPs effects in human ErbB genes.

Understanding the functions of single nucleotide polymorphisms (SNPs) can greatly help to understand the genetic basis of human complex diseases such as cancer. However, identifying functional SNPs among the huge number of available SNPs is challenging. In this study, we analyzed the genetic variations that can alter the expression and function of ErbB proteins using different computational tools. For noncoding SNP, we found that one SNP located in 59UTR of ErbB1 gene might change protein expression level and two SNPS located in regulatory regions might affect transcriptional regulation of Erbb1 and Erbb4. For coding SNPs we predicted that 25 nonsynonymous SNPs (most of them in ErbB1 gene) might disrupt the protein function among which 22 might alter protein structure. Prediction regarding the potential effect of the SNPs showed that 13 of them located within the tyrosine kinase or the ligand binding domain are likely to be associated with cancer.

Exploring disorder in the human charged biased proteins

Abstract A considerable interest has been put in the identification of biased regions in proteins. These regions are frequently associated with a structural role in the cell and particularly with protein disorder. Here, we have investigated the intrinsically disordered regions (IDRs) in the human charged biased proteins identified in our earlier work. We found that 65% of charged biased proteins contained significant IDRs involved particularly in DNA and RNA binding. Also, we have observed that these proteins are well conserved in metazoans and more particularly in mammalian. In addition, the IDRs are located largely in N-terminal, C-terminal sequence flanking the functional domains (FD) and slightly less in (FD) itself. Our work also supports the association between protein disorder and protein–protein/DNA interaction. An example will be described.

Structural and functional characterisation of two novel durum wheat annexin genes in response to abiotic stress

Abiotic stress results in massive loss of crop productivity throughout the world. Understanding the plant gene regulatory mechanisms involved in stress responses is very important. Annexins are a conserved multigene family of Ca-dependent, phospholipid-binding proteins with suggested functions in response to environmental stresses and signalling during plant growth and development. Annexins function to counteract oxidative stress, maintain cell redox homeostasis and enhance drought tolerance. A full-length cDNA of two genes (TdAnn6 and TdAnn12) encoding annexin proteins were isolated and characterised from Tunisian durum wheat varieties (Triticum turgidum L. subsp. durum cv. Mahmoudi). Analyses of the deduced proteins encoded by annexin cDNAs (TdAnn6 and TdAnn12) indicate the presence of the characteristic four repeats of 70-75 amino acids and the motifs proposed to be involved in Ca2+ binding. Gene expression patterns obtained by real-time PCR revealed differential temporal and spatial regulation of the two annexin genes in durum wheat under different abiotic stress conditions such as salt (NaCl 150mM), osmotic (10% polyethylene glycol 8000), ionic (LiCl 10mM), oxidative (H2O2), ABA (100µM), salicylic acid (10mM), cold (4°C) and heat (37°C) stress. The two annexin genes were not regulated by heavy metal stress (CdCl2 150µM). Moreover, heterologous expression of TdAnn6 and TdAnn12 in yeast improves its tolerance to abiotic stresses, suggesting annexins involvement in theses stress tolerance mechanisms. Taken together, our results show that the two newly isolated wheat annexin might play an active role in modulating plant cell responses to abiotic stress responses.

From FHB Resistance QTLs to Candidate Genes Identification in Triticum aestivum L.

Fusarium head blight (FHB) caused by Fusarium graminearum is a worldwide destructive disease affecting cereals such as wheat. FHB resistance is a quantitative trait, and information for FHB resistance QTLs in wheat is available. However, little is known about genes underlying the FHB resistance QTL regions. Using a computational approach in this study, we have mined eight FHB resistance QTLs in wheat and predicted the candidate genes falling within these QTL intervals based on the available sequences and markers. A total of 18 genomic scaffolds located at chromosomes 2AL, 2DL, 3B and 4BS were prioritized to harbor FHB-resistant candidate genes. These genes are mainly involved in plant defense response, immune regulation and cellular detoxification. We believe that our results constitute a starting point for further validation to improve FHB-resistant bread wheat varieties.