Despite the success of tyrosine kinase-based cancer therapeutics, for most solid tumors the tyrosine kinases that drive disease remain unknown, limiting our ability to identify drug targets and predict response. Here we present the first large-scale survey of tyrosine kinase activity in lung cancer. Using a phosphoproteomic approach, we characterize tyrosine kinase signaling across 41 non-small cell lung cancer (NSCLC) cell lines and over 150 NSCLC tumors. Profiles of phosphotyrosine signaling are generated and analyzed to identify known oncogenic kinases such as EGFR and c-Met as well as novel ALK and ROS fusion proteins. Other activated tyrosine kinases such as PDGFRalpha and DDR1 not previously implicated in the genesis of NSCLC are also identified. By focusing on activated cell circuitry, the approach outlined here provides insight into cancer biology not available at the chromosomal and transcriptional levels and can be applied broadly across all human cancers.

Identification of protein phosphorylation sites with their cognate protein kinases (PKs) is a key step to delineate molecular dynamics and plasticity underlying a variety of cellular processes. Although nearly 10 kinase-specific prediction programs have been developed, numerous PKs have been casually classified into subgroups without a standard rule. For large scale predictions, the false positive rate has also never been addressed. In this work, we adopted a well established rule to classify PKs into a hierarchical structure with four levels, including group, family, subfamily, and single PK. In addition, we developed a simple approach to estimate the theoretically maximal false positive rates. The on-line service and local packages of the GPS (Group-based Prediction System) 2.0 were implemented in Java with the modified version of the Group-based Phosphorylation Scoring algorithm. As the first stand alone software for predicting phosphorylation, GPS 2.0 can predict kinase-specific phosphorylation sites for 408 human PKs in hierarchy. A large scale prediction of more than 13,000 mammalian phosphorylation sites by GPS 2.0 was exhibited with great performance and remarkable accuracy. Using Aurora-B as an example, we also conducted a proteome-wide search and provided systematic prediction of Aurora-B-specific substrates including protein-protein interaction information. Thus, the GPS 2.0 is a useful tool for predicting protein phosphorylation sites and their cognate kinases and is freely available on line. Molecular & Cellular Proteomics 7:1598 -1608, 2008.Post-translational modification of proteins provides reversible means to regulate the function of a protein in space and time. Recently computational studies of post-translational modifications (PTMs) 1 of proteins have attracted much attention. Various PTMs regulate the functions and dynamics of proteins through specific modifications and are implicated in almost all cellular processes. In contrast to the labor-intensive and expensive experimental methods, in silico prediction of PTM-specific substrates with their sites has emerged as a popular alternative approach. To date, more than 32 computational prediction tools have been developed (1). In the field of computational PTMs, protein phosphorylation is the most studied example. To predict general phosphorylation sites, several tools have been developed, such as DISPHOS (2), NetPhos (3), NetPhosYeast (4), and GANNPhos (5). As the need for performing large scale predictions and constructing reliable phosphorylation networks evolves, robust prediction of kinase-specific phosphorylation sites has become necessary and challenging. For example, Neuberger et al. ) developed NetworKIN and constructed a human phosphorylation network, which has gained diversified interest not only for human phosphorylation network prediction but also for general implication in cell biology. To predict kinase-specific phosphorylation sites, several on-line Web services have been implemented using various algorithms, including our previ...

Summary: Biological sequence diagrams are fundamental for visualizing various functional elements in protein or nucleotide sequences that enable a summarization and presentation of existing information as well as means of intuitive new discoveries. Here, we present a software package called illustrator of biological sequences (IBS) that can be used for representing the organization of either protein or nucleotide sequences in a convenient, efficient and precise manner. Multiple options are provided in IBS, and biological sequences can be manipulated, recolored or rescaled in a user-defined mode. Also, the final representational artwork can be directly exported into a publication-quality figure.Availability and implementation: The standalone package of IBS was implemented in JAVA, while the online service was implemented in HTML5 and JavaScript. Both the standalone package and online service are freely available at http://ibs.biocuckoo.org.Contact: renjian.sysu@gmail.com or xueyu@hust.edu.cnSupplementary information: Supplementary data are available at Bioinformatics online.

Protein palmitoylation is an essential post-translational lipid modification of proteins, and reversibly orchestrates a variety of cellular processes. Identification of palmitoylated proteins with their sites is the foundation for understanding molecular mechanisms and regulatory roles of palmitoylation. Contrasting to the labor-intensive and time-consuming experimental approaches, in silico prediction of palmitoylation sites has attracted much attention as a popular strategy. In this work, we updated our previous CSS-Palm into version 2.0. An updated clustering and scoring strategy (CSS) algorithm was employed with great improvement. The leave-one-out validation and 4-, 6-, 8- and 10-fold cross-validations were adopted to evaluate the prediction performance of CSS-Palm 2.0. Also, an additional new data set not included in training was used to test the robustness of CSS-Palm 2.0. By comparison, the performance of CSS-Palm was much better than previous tools. As an application, we performed a small-scale annotation of palmitoylated proteins in budding yeast. The online service and local packages of CSS-Palm 2.0 were freely available at: http://bioinformatics.lcd-ustc.org/css_palm.

A good picture is worth a thousand words. Schematic diagram of protein domain structures with functional motifs/sites in a concise and illustrative drawing is greatly helpful for a broad readership to grasp the old and novel functions of proteins rapidly. To estimate how many papers contain protein domain graphs, we went through all original research papers (excluding reviews and other articles) in five leading journals in this field, namely

Small ubiquitin-like modifiers (SUMOs) regulate a variety of cellular processes through two distinct mechanisms, including covalent sumoylation and non-covalent SUMO interaction. The complexity of SUMO regulations has greatly hampered the large-scale identification of SUMO substrates or interaction partners on a proteome-wide level. In this work, we developed a new tool called GPS-SUMO for the prediction of both sumoylation sites and SUMO-interaction motifs (SIMs) in proteins. To obtain an accurate performance, a new generation group-based prediction system (GPS) algorithm integrated with Particle Swarm Optimization approach was applied. By critical evaluation and comparison, GPS-SUMO was demonstrated to be substantially superior against other existing tools and methods. With the help of GPS-SUMO, it is now possible to further investigate the relationship between sumoylation and SUMO interaction processes. A web service of GPS-SUMO was implemented in PHP + JavaScript and freely available at http://sumosp.biocuckoo.org.

To ensure survival in the face of genomic insult, cells have evolved complex mechanisms to respond to DNA damage, termed the DNA damage checkpoint. The serine/threonine kinases ataxia telangiectasia-mutated (ATM) and ATM and Rad3-related (ATR) activate checkpoint signaling by phosphorylating substrate proteins at SQ/TQ motifs. Although some ATM/ATR substrates (Chk1, p53) have been identified, the lack of a more complete list of substrates limits current understanding of checkpoint pathways. Here, we use immunoaffinity phosphopeptide isolation coupled with mass spectrometry to identify 570 sites phosphorylated in UV-damaged cells, 498 of which are previously undescribed. Semiquantitative analysis yielded 24 known and 192 previously uncharacterized sites differentially phosphorylated upon UV damage, some of which were confirmed by SILAC, Western blotting, and immunoprecipitation/ Western blotting. ATR-specific phosphorylation was investigated by using a Seckel syndrome (ATR mutant) cell line. Together, these results provide a rich resource for further deciphering ATM/ATR signaling and the pathways mediating the DNA damage response.DNA damage ͉ mass spectrometry ͉ phosphorylation M aintaining the integrity of the genome is of utmost importance for cellular survival. For this reason, cells have evolved complex mechanisms to inhibit cell cycle progression in response to genomic insult, termed the DNA damage checkpoint (1). Activating checkpoint mechanisms gives cells time to repair or bypass the damage using specialized DNA polymerases or, in cases of high levels of damage, to activate apoptotic pathways (2). Elucidating pathways involved in checkpoint activation and maintenance continues to be an active area of research.A family of phosphoinositol-3-phosphate kinase-like kinases are critical to the proper function of the DNA damage checkpoint. The two central kinases involved are ataxia telangiectasiamutated (ATM) and ATM and Rad3-related (ATR). This kinase family also includes DNA-dependent protein kinase (DNA-PK) and a more recently discovered member of the family, SMG1 (3). These kinases are activated in response to DNA damage and subsequently phosphorylate targets responsible for such diverse activities as blocking cell cycle progression, coordinating DNA repair activities, and affecting transcription of DNA damage response genes. ATR is activated in response to a variety of damaging agents: UV light, alkylating agents such as methyl methanesulfonate (MMS), and chemical inhibitors of DNA replication such as aphidicolin and hydroxyurea (4, 5). ATM, however, is primarily involved in the response to double-strand breaks, such as those caused by gamma irradiation (IR) (6). Deficiency in ATM/R, as well as other components of the DNA damage checkpoint, has been found to cause debilitating diseases such as ataxia telangiectasia (ATM mutants), Fanconi's anemia, Seckel syndrome (ATR mutants), and the avoidance of checkpoint activation to allow cancer progression.In response to DNA damage, ATM/R phosphorylate checkpoint k...

Receptor tyrosine kinases (RTKs) activate pathways mediated by serine/threonine (Ser/Thr) kinases such as the PI3K (phosphatidylinositol 3-kinase)-Akt pathway, the Ras-MAPK (mitogen-activated protein kinase)-RSK pathway, and the mTOR (mammalian target of rapamycin)-p70 S6 pathway that control important aspects of cell growth, proliferation, and survival. The Akt, RSK, and p70 S6 family of protein kinases transmit signals by phosphorylating substrates on a RxRxxS/T motif. Here, we developed a large-scale proteomic approach to identify over 200 substrates of this kinase family in cancer cell lines driven by the c-Met, epidermal growth factor receptor (EGFR), or platelet-derived growth factor receptor a (PDGFRα) RTKs. We identified a subset of proteins with RxRxxS/T sites for which phosphorylation was decreased by RTKIs as well as by inhibitors of the PI3K, mTOR, and MAPK pathways and determined the effects of siRNA directed against these substrates on cell viability. We found that phosphorylation of the protein chaperone SGTA (small glutamine-rich tetratricopeptide repeat-containing protein alpha) at Ser305 is essential for PDGFRα stabilization and cell survival in PDGFRα-dependent cancer cells. Our approach provides a new view of RTK and Akt-RSK-S6 kinase signaling, revealing many previously unidentified Akt-RSK-S6 kinase substrates that merit further consideration as targets for combination therapy with RTKIs.