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Dive into the research topics where Zexian Liu is active.

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Featured researches published by Zexian Liu.


PLOS ONE | 2014

HemI: A Toolkit for Illustrating Heatmaps

Wankun Deng; Yongbo Wang; Zexian Liu; Han Cheng; Yu Xue

Recent high-throughput techniques have generated a flood of biological data in all aspects. The transformation and visualization of multi-dimensional and numerical gene or protein expression data in a single heatmap can provide a concise but comprehensive presentation of molecular dynamics under different conditions. In this work, we developed an easy-to-use tool named HemI (Heat map Illustrator), which can visualize either gene or protein expression data in heatmaps. Additionally, the heatmaps can be recolored, rescaled or rotated in a customized manner. In addition, HemI provides multiple clustering strategies for analyzing the data. Publication-quality figures can be exported directly. We propose that HemI can be a useful toolkit for conveniently visualizing and manipulating heatmaps. The stand-alone packages of HemI were implemented in Java and can be accessed at http://hemi.biocuckoo.org/down.php.


Nucleic Acids Research | 2014

GPS-SUMO: a tool for the prediction of sumoylation sites and SUMO-interaction motifs

Qi Zhao; Yubin Xie; Yueyuan Zheng; Shuai Jiang; Wenzhong Liu; Weiping Mu; Zexian Liu; Yong Zhao; Yu Xue; Jian Ren

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.


Protein Engineering Design & Selection | 2011

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

Yu Xue; Zexian Liu; Jun Cao; Qian Ma; Xinjiao Gao; Qingqi Wang; Changjiang Jin; Yanhong Zhou; Longping Wen; Jian Ren

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.


PLOS ONE | 2010

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

Yu Xue; Zexian Liu; Xinjiao Gao; Changjiang Jin; Longping Wen; Xuebiao Yao; Jian-Song Ren

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/.


Molecular & Cellular Proteomics | 2012

Systematic Analysis of Protein Phosphorylation Networks From Phosphoproteomic Data

Chunxia Song; Mingliang Ye; Zexian Liu; Han Cheng; Xinning Jiang; Guanghui Han; Zhou Songyang; Yexiong Tan; Wang H; Jian Ren; Yu Xue; Hanfa Zou

In eukaryotes, hundreds of protein kinases (PKs) specifically and precisely modify thousands of substrates at specific amino acid residues to faithfully orchestrate numerous biological processes, and reversibly determine the cellular dynamics and plasticity. Although over 100,000 phosphorylation sites (p-sites) have been experimentally identified from phosphoproteomic studies, the regulatory PKs for most of these sites still remain to be characterized. Here, we present a novel software package of iGPS for the prediction of in vivo site-specific kinase-substrate relations mainly from the phosphoproteomic data. By critical evaluations and comparisons, the performance of iGPS is satisfying and better than other existed tools. Based on the prediction results, we modeled protein phosphorylation networks and observed that the eukaryotic phospho-regulation is poorly conserved at the site and substrate levels. With an integrative procedure, we conducted a large-scale phosphorylation analysis of human liver and experimentally identified 9719 p-sites in 2998 proteins. Using iGPS, we predicted a human liver protein phosphorylation networks containing 12,819 potential site-specific kinase-substrate relations among 350 PKs and 962 substrates for 2633 p-sites. Further statistical analysis and comparison revealed that 127 PKs significantly modify more or fewer p-sites in the liver protein phosphorylation networks against the whole human protein phosphorylation network. The largest data set of the human liver phosphoproteome together with computational analyses can be useful for further experimental consideration. This work contributes to the understanding of phosphorylation mechanisms at the systemic level, and provides a powerful methodology for the general analysis of in vivo post-translational modifications regulating sub-proteomes.


Nucleic Acids Research | 2014

CPLM: a database of protein lysine modifications

Zexian Liu; Yongbo Wang; Tianshun Gao; Zhicheng Pan; Han Cheng; Qing Yang; Zhongyi Cheng; An-Yuan Guo; Jian Ren; Yu Xue

We reported an integrated database of Compendium of Protein Lysine Modifications (CPLM; http://cplm.biocuckoo.org) for protein lysine modifications (PLMs), which occur at active ε-amino groups of specific lysine residues in proteins and are critical for orchestrating various biological processes. The CPLM database was updated from our previously developed database of Compendium of Protein Lysine Acetylation (CPLA), which contained 7151 lysine acetylation sites in 3311 proteins. Here, we manually collected experimentally identified substrates and sites for 12 types of PLMs, including acetylation, ubiquitination, sumoylation, methylation, butyrylation, crotonylation, glycation, malonylation, phosphoglycerylation, propionylation, succinylation and pupylation. In total, the CPLM database contained 203 972 modification events on 189 919 modified lysines in 45 748 proteins for 122 species. With the dataset, we totally identified 76 types of co-occurrences of various PLMs on the same lysine residues, and the most abundant PLM crosstalk is between acetylation and ubiquitination. Up to 53.5% of acetylation and 33.1% of ubiquitination events co-occur at 10 746 lysine sites. Thus, the various PLM crosstalks suggested that a considerable proportion of lysines were competitively and dynamically regulated in a complicated manner. Taken together, the CPLM database can serve as a useful resource for further research of PLMs.


Molecular & Cellular Proteomics | 2010

PhosSNP for Systematic Analysis of Genetic Polymorphisms That Influence Protein Phosphorylation

Jian Ren; Chunhui Jiang; Xinjiao Gao; Zexian Liu; Zineng Yuan; Changjiang Jin; Longping Wen; Zhaolei Zhang; Yu Xue; Xuebiao Yao

We are entering the era of personalized genomics as breakthroughs in sequencing technology have made it possible to sequence or genotype an individual person in an efficient and accurate manner. Preliminary results from HapMap and other similar projects have revealed the existence of tremendous genetic variations among world populations and among individuals. It is important to delineate the functional implication of such variations, i.e. whether they affect the stability and biochemical properties of proteins. It is also generally believed that the genetic variation is the main cause for different susceptibility to certain diseases or different response to therapeutic treatments. Understanding genetic variation in the context of human diseases thus holds the promise for “personalized medicine.” In this work, we carried out a genome-wide analysis of single nucleotide polymorphisms (SNPs) that could potentially influence protein phosphorylation characteristics in human. Here, we defined a phosphorylation-related SNP (phosSNP) as a non-synonymous SNP (nsSNP) that affects the protein phosphorylation status. Using an in-house developed kinase-specific phosphorylation site predictor (GPS 2.0), we computationally detected that ∼70% of the reported nsSNPs are potential phosSNPs. More interestingly, ∼74.6% of these potential phosSNPs might also induce changes in protein kinase types in adjacent phosphorylation sites rather than creating or removing phosphorylation sites directly. Taken together, we proposed that a large proportion of the nsSNPs might affect protein phosphorylation characteristics and play important roles in rewiring biological pathways. Finally, all phosSNPs were integrated into the PhosSNP 1.0 database, which was implemented in JAVA 1.5 (J2SE 5.0). The PhosSNP 1.0 database is freely available for academic researchers.


PLOS ONE | 2011

GPS-CCD: a novel computational program for the prediction of calpain cleavage sites.

Zexian Liu; Jun Cao; Xinjiao Gao; Qian Ma; Jian Ren; Yu Xue

As one of the most essential post-translational modifications (PTMs) of proteins, proteolysis, especially calpain-mediated cleavage, plays an important role in many biological processes, including cell death/apoptosis, cytoskeletal remodeling, and the cell cycle. Experimental identification of calpain targets with bona fide cleavage sites is fundamental for dissecting the molecular mechanisms and biological roles of calpain cleavage. In contrast to time-consuming and labor-intensive experimental approaches, computational prediction of calpain cleavage sites might more cheaply and readily provide useful information for further experimental investigation. In this work, we constructed a novel software package of GPS-CCD (Calpain Cleavage Detector) for the prediction of calpain cleavage sites, with an accuracy of 89.98%, sensitivity of 60.87% and specificity of 90.07%. With this software, we annotated potential calpain cleavage sites for hundreds of calpain substrates, for which the exact cleavage sites had not been previously determined. In this regard, GPS-CCD 1.0 is considered to be a useful tool for experimentalists. The online service and local packages of GPS-CCD 1.0 were implemented in JAVA and are freely available at: http://ccd.biocuckoo.org/.


Molecular BioSystems | 2011

GPS-YNO2: computational prediction of tyrosine nitration sites in proteins

Zexian Liu; Jun Cao; Qian Ma; Xinjiao Gao; Jian Ren; Yu Xue

The last decade has witnessed rapid progress in the identification of protein tyrosine nitration (PTN), which is an essential and ubiquitous post-translational modification (PTM) that plays a variety of important roles in both physiological and pathological processes, such as the immune response, cell death, aging and neurodegeneration. Identification of site-specific nitrated substrates is fundamental for understanding the molecular mechanisms and biological functions of PTN. In contrast with labor-intensive and time-consuming experimental approaches, here we report the development of the novel software package GPS-YNO2 to predict PTN sites. The software demonstrated a promising accuracy of 76.51%, a sensitivity of 50.09% and a specificity of 80.18% from the leave-one-out validation. As an example application, we predicted potential PTN sites for hundreds of nitrated substrates which had been experimentally detected in small-scale or large-scale studies, even though the actual nitration sites had still not been determined. Through a statistical functional comparison with the nitric oxide (NO) dependent reversible modification of S-nitrosylation, we observed that PTN prefers to attack certain fundamental biological processes and functions. These prediction and analysis results might be helpful for further experimental investigation. Finally, the online service and local packages of GPS-YNO2 1.0 were implemented in JAVA and freely available at: .


Oncogene | 2008

Functional characterization of TIP60 sumoylation in UV-irradiated DNA damage response.

Z Cheng; Yuwen Ke; Xia Ding; Fangjun Wang; H Wang; Wenwen Wang; K Ahmed; Zexian Liu; Y Xu; Felix O. Aikhionbare; H Yan; Jing Liu; Yu Xue; J Yu; Michael Powell; S Liang; Quan Wu; S E Reddy; Renming Hu; He Huang; Changjiang Jin; Xuebiao Yao

The histone acetyltransferase TIP60 regulates the DNA damage response following genotoxic stress by acetylating histone and remodeling chromatin. However, the molecular mechanisms underlying the TIP60-dependent response to UV-induced DNA damage remain poorly understood. To systematically analyse proteins that regulate TIP60 activity in response to UV irradiation, we performed a proteomic analysis of proteins selectively bound to TIP60 in response to UV irradiation using mass spectrometry and identified a novel regulatory mechanism by which TIP60 orchestrates transcriptional activation of p53-dependent checkpoint response in UV-irradiated cells. The initial step of this pathway involves UV-induced association of TIP60 with SUMO-conjugation enzymes and site-specific sumoylation of TIP60 at lysines 430 and 451 via Ubc9. This sumoylation initiates the relocation of TIP60 from nucleoplasm to the promyelocytic leukemia body, which is essential for the UV-irradiated DNA damage repair response via a p53-dependent pathway. Significantly, inhibition of TIP60 sumoylation by overexpression of non-sumoylatable mutant abrogates the p53-dependent DNA damage response, demonstrating the importance of TIP60 sumoylation in response to UV irradiation. Our biochemical characterization demonstrated that the sumoylation of TIP60 augments its acetyltransferase activity in vitro and in vivo. Thus, this study shed new light on the function and regulation of TIP60 activity in UV-irradiated DNA damage response.

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Yu Xue

Huazhong University of Science and Technology

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Jian Ren

Sun Yat-sen University

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Yongbo Wang

Huazhong University of Science and Technology

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Han Cheng

Huazhong University of Science and Technology

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Xinjiao Gao

University of Science and Technology of China

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Jun Cao

University of Science and Technology of China

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Zhicheng Pan

Huazhong University of Science and Technology

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Changjiang Jin

University of Science and Technology of China

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Qing Yang

Huazhong University of Science and Technology

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Tianshun Gao

Huazhong University of Science and Technology

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