Longping Wen

GPS 2.0, a Tool to Predict Kinase-specific Phosphorylation Sites in Hierarchy

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.

CSS-Palm 2.0: an updated software for palmitoylation sites prediction

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.

Targeting cancer cells with biotin–dendrimer conjugates

Star-burst dendrimers represent a superior carrier platform for targeted drug delivery. Partially acetylated generation 5 (G5) polyamidoamine (PAMAM) dendrimer was conjugated with the targeting moiety (biotin) and the imaging moiety (fluoresceinisothiocyanate, FITC), and the resulting dendrimer-biotin conjugate was characterized by (1)H NMR, UV-vis spectrum. As revealed by flow cytometry and confocal microscopy, the bifunctional conjugate (dendrimer-biotin-FITC) exhibited much higher cellular uptake into HeLa cells than the conjugate without biotin. The uptake was energy-dependent, dose-dependent, and could be effectively blocked by dendrimer-conjugated biotin. Our results indicated that the biocompatible biotin-dendrimer conjugate might be a promising nano-platform for cancer therapy and cancer diagnosis.

Systematic study of protein sumoylation: Development of a site‐specific predictor of SUMOsp 2.0

Protein sumoylation is an important reversible post‐translational modification on proteins, and orchestrates a variety of cellular processes. Recently, computational prediction of sumoylation sites has attracted much attention for its cost‐efficiency and power in genomic data mining. In this work, we developed SUMOsp 2.0, an accurate computing program with an improved group‐based phosphorylation scoring algorithm. Our analysis demonstrated that SUMOsp 2.0 has greater prediction accuracy than SUMOsp 1.0 and other existing tools, with a sensitivity of 88.17% and a specificity of 92.69% under the medium threshold. Previously, several large‐scale experiments have identified a list of potential sumoylated substrates in Saccharomyces cerevisiae and Homo sapiens; however, the exact sumoylation sites in most of these proteins remain elusive. We have predicted potential sumoylation sites in these proteins using SUMOsp 2.0, which provides a great resource for researchers and an outline for further mechanistic studies of sumoylation in cellular plasticity and dynamics. The online service and local packages of SUMOsp 2.0 are freely available at: http://sumosp.biocuckoo.org/.

Transdermal protein delivery by a coadministered peptide identified via phage display

Efficient transdermal drug delivery of large hydrophilic drugs is challenging. Here we report that the short synthetic peptide, ACSSSPSKHCG, identified by in vivo phage display, facilitated efficient transdermal protein drug delivery through intact skin. Coadministration of the peptide and insulin to the abdominal skin of diabetic rats resulted in elevated systemic levels of insulin and suppressed serum glucose levels for at least 11 h. Significant systemic bioavailability of human growth hormone was also achieved when topically coadministered with the peptide. The transdermal-enhancing activity of the peptide was sequence specific and dose dependent, did not involve direct interaction with insulin and enabled penetration of insulin into hair follicles beyond a depth of 600 μm. Time-lapse studies suggested that the peptide creates a transient opening in the skin barrier to enable macromolecular drugs to reach systemic circulation.

GPS 2.1: enhanced prediction of kinase-specific phosphorylation sites with an algorithm of motif length selection

As the most important post-translational modification of proteins, phosphorylation plays essential roles in all aspects of biological processes. Besides experimental approaches, computational prediction of phosphorylated proteins with their kinase-specific phosphorylation sites has also emerged as a popular strategy, for its low-cost, fast-speed and convenience. In this work, we developed a kinase-specific phosphorylation sites predictor of GPS 2.1 (Group-based Prediction System), with a novel but simple approach of motif length selection (MLS). By this approach, the robustness of the prediction system was greatly improved. All algorithms in GPS old versions were also reserved and integrated in GPS 2.1. The online service and local packages of GPS 2.1 were implemented in JAVA 1.5 (J2SE 5.0) and freely available for academic researches at: http://gps.biocuckoo.org.

Targeting the brain with PEG-PLGA nanoparticles modified with phage-displayed peptides

The relative impermeability of the blood-brain barrier (BBB) results from tight junctions and efflux transport systems limits drug delivery to the central nervous system (CNS), and thus severely restricts the therapy of many central nervous system diseases. In order to enhance the brain-specific drug delivery, we employed a 12-mer phage display peptide library to isolate peptides that could target the drug delivery system to the brain. A 12-amino-acid-peptide (denoted as Pep TGN) which was displayed by bacteriophage Clone 12-2 was finally selected by rounds of in vivo screening. Pep TGN was covalently conjugated onto the surface of poly (ethyleneglycol)-poly (lactic-co-glycolic acid) (PEG-PLGA) based nanoparticles (NPs). The cellular uptake of Pep TGN decorated nanoparticles was significantly higher than that of unmodified nanoparticles when incubated with bEnd.3 cells. Enhanced brain accumulation efficiency together with lower accumulation in liver and spleen was observed in the nude mice intravenously injected with Pep TGN conjugated nanoparticles compared with those injected with plain nanoparticles, showing powerful brain selectivity of Pep TGN. Coumarin 6 was used as a fluorescent probe for the evaluation of brain delivery properties. The brain Drug Targeting Index (DTI) of coumarin 6 incorporated in targeted nanoparticles was significantly higher than that of coumarin 6 incorporated in plain nanoparticles. In conclusion, the Pep TGN is a motif never been reported before and Pep TGN modified nanoparticles showed great potential in targeted drug delivery across the blood brain barrier.

GPS-SNO: Computational Prediction of Protein S-Nitrosylation Sites with a Modified GPS Algorithm

As one of the most important and ubiquitous post-translational modifications (PTMs) of proteins, S-nitrosylation plays important roles in a variety of biological processes, including the regulation of cellular dynamics and plasticity. Identification of S-nitrosylated substrates with their exact sites is crucial for understanding the molecular mechanisms of S-nitrosylation. In contrast with labor-intensive and time-consuming experimental approaches, prediction of S-nitrosylation sites using computational methods could provide convenience and increased speed. In this work, we developed a novel software of GPS-SNO 1.0 for the prediction of S-nitrosylation sites. We greatly improved our previously developed algorithm and released the GPS 3.0 algorithm for GPS-SNO. By comparison, the prediction performance of GPS 3.0 algorithm was better than other methods, with an accuracy of 75.80%, a sensitivity of 53.57% and a specificity of 80.14%. As an application of GPS-SNO 1.0, we predicted putative S-nitrosylation sites for hundreds of potentially S-nitrosylated substrates for which the exact S-nitrosylation sites had not been experimentally determined. In this regard, GPS-SNO 1.0 should prove to be a useful tool for experimentalists. The online service and local packages of GPS-SNO were implemented in JAVA and are freely available at: http://sno.biocuckoo.org/.

Hydrophilic Co@Au Yolk/Shell Nanospheres: Synthesis, Assembly, and Application to Gene Delivery

[*] Prof. S.-H. Yu, Y. Lu, Y. Zhao, L. Dong, C. Shi, M.-J. Hu Division of Nanomaterials and Chemistry Hefei National Laboratory for Physical Sciences at the Microscale Department of Chemistry University of Science and Technology of China Hefei, Anhui 230026 (P. R. China) E-mail: shyu@ustc.edu.cn L. Yu, Prof. L.-P. Wen Hefei National Laboratory for Physical Sciences at the Microscale School of Life Sciences University of Science and Technology of China Hefei 230027 (P. R. China)

Autophagy-mediated chemosensitization in cancer cells by fullerene C60 nanocrystal

Autophagy may represent a common cellular response to nanomaterials, and modulation of autophagy holds great promise for improving the efficacy of cancer therapy. Fullerene C60 possesses potent anti-cancer activities, but its considerable toxicity towards normal cells may hinder its practical applications. It has been reported that fullerene C60 induces certain hallmarks of autophagy in cancer cells. Here we show that the water-dispersed nanocrystal of underivatized fullerene C60 (Nano-C60) at non-cytotoxic concentrations caused authentic autophagy and sensitized chemotherapeutic killing of both normal and drug-resistant cancer cells in a reactive oxygen species (ROS)-dependent and photo-enhanced fashion. We further demonstrated that the chemosensitization effect of Nano-C60 was autophagy-mediated and required a functional Atg5, a key gene in the autophagy signaling pathway. Our results revealed a novel biological function for Nano-C60 in enhancing the cytotoxic action of chemotherapeutic agents through autophagy modulation and may point to the potential application of Nano-C60 in adjunct chemotherapy.