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Search Results: 1 - 10 of 20437 matches for " Dongsup Kim "
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Inference of Protein Complex Activities from Chemical-Genetic Profile and Its Applications: Predicting Drug-Target Pathways
Sangjo Han,Dongsup Kim
PLOS Computational Biology , 2008, DOI: 10.1371/journal.pcbi.1000162
Abstract: The chemical-genetic profile can be defined as quantitative values of deletion strains' growth defects under exposure to chemicals. In yeast, the compendium of chemical-genetic profiles of genomewide deletion strains under many different chemicals has been used for identifying direct target proteins and a common mode-of-action of those chemicals. In the previous study, valuable biological information such as protein–protein and genetic interactions has not been fully utilized. In our study, we integrated this compendium and biological interactions into the comprehensive collection of ~490 protein complexes of yeast for model-based prediction of a drug's target proteins and similar drugs. We assumed that those protein complexes (PCs) were functional units for yeast cell growth and regarded them as hidden factors and developed the PC-based Bayesian factor model that relates the chemical-genetic profile at the level of organism phenotypes to the hidden activities of PCs at the molecular level. The inferred PC activities provided the predictive power of a common mode-of-action of drugs as well as grouping of PCs with similar functions. In addition, our PC-based model allowed us to develop a new effective method to predict a drug's target pathway, by which we were able to highlight the target-protein, TOR1, of rapamycin. Our study is the first approach to model phenotypes of systematic deletion strains in terms of protein complexes. We believe that our PC-based approach can provide an appropriate framework for combining and modeling several types of chemical-genetic profiles including interspecies. Such efforts will contribute to predicting more precisely relevant pathways including target proteins that interact directly with bioactive compounds.
Transient Protein-Protein Interaction of the SH3-Peptide Complex via Closely Located Multiple Binding Sites
Seungsoo Hahn, Dongsup Kim
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0032804
Abstract: Protein-protein interactions play an essential role in cellular processes. Certain proteins form stable complexes with their partner proteins, whereas others function by forming transient complexes. The conventional protein-protein interaction model describes an interaction between two proteins under the assumption that a protein binds to its partner protein through a single binding site. In this study, we improved the conventional interaction model by developing a Multiple-Site (MS) model in which a protein binds to its partner protein through closely located multiple binding sites on a surface of the partner protein by transiently docking at each binding site with individual binding free energies. To test this model, we used the protein-protein interaction mediated by Src homology 3 (SH3) domains. SH3 domains recognize their partners via a weak, transient interaction and are therefore promiscuous in nature. Because the MS model requires large amounts of data compared with the conventional interaction model, we used experimental data from the positionally addressable syntheses of peptides on cellulose membranes (SPOT-synthesis) technique. From the analysis of the experimental data, individual binding free energies for each binding site of peptides were extracted. A comparison of the individual binding free energies from the analysis with those from atomistic force fields gave a correlation coefficient of 0.66. Furthermore, application of the MS model to 10 SH3 domains lowers the prediction error by up to 9% compared with the conventional interaction model. This improvement in prediction originates from a more realistic description of complex formation than the conventional interaction model. The results suggested that, in many cases, SH3 domains increased the protein complex population through multiple binding sites of their partner proteins. Our study indicates that the consideration of general complex formation is important for the accurate description of protein complex formation, and especially for those of weak or transient protein complexes.
AtRTPrimer: database for Arabidopsis genome-wide homogeneous and specific RT-PCR primer-pairs
Sangjo Han, Dongsup Kim
BMC Bioinformatics , 2006, DOI: 10.1186/1471-2105-7-179
Abstract: We considered the homogeneous physical and chemical properties of each primer (homogeneity) of a gene, non-specific binding against all other known genes (specificity), and other possible amplicons from its corresponding genomic DNA or similar cDNAs (additional information). Then, we evaluated the reliability of our database with selected primer pairs from 15 genes using conventional and real time RT-PCR.Approximately 97% of 28,952 genes investigated were finally registered in AtRTPrimer. Unlike other freely available primer databases for Arabidopsis thaliana, AtRTPrimer provides a large number of reliable primer pairs for each gene so that researchers can perform various types of RT-PCR experiments for their specific needs. Furthermore, by experimentally evaluating our database, we made sure that our database provides good starting primer pairs for Arabidopsis researchers to perform various types of RT-PCR experiments.In the post-genome era, microarray technology becomes a powerful tool for global gene expression profiling. However, some genes show significant variability in their expressions. These observed differences should be validated through more accurate tools. In addition, microarray methodology can not credibly monitor the low levels of expression from certain genes such as, transcription factors [1]. Quantitative RT-PCR methods (i.e. real-time RT-PCR) have been adopted to overcome the stated drawbacks [2]. For researchers, RT-PCR is useful and, moreover essential, for accurately measuring quantitative transcriptional levels of particular genes.Primer design is a critical step in all kinds of RT-PCR methods to guarantee specificity and efficiency of a target amplicon. However, most traditional primer design programs suggest primers on a single template of limited genetic complexity [3]. Although several online RT-PCR primer databases have been established as repositories for empirically validated primer sequences submitted by researchers [4], unfortunately
Regulatory patterns of histone modifications to control the DNA methylation status at CpG islands
Inkyung Jung,Dongsup Kim
Interdisciplinary Bio Central , 2009,
Abstract: Introduction: Histone modifications and DNA methylation are the major factors in epigenetic gene regulation. Especially, revealing how histone modifications are related to DNA methylation is one of the challenging problems in this field. In this paper, we address this issue and propose several plausible mechanisms for precise controlling of DNA methylation status at CpG islandsMaterials and Methods: To establish the regulatory relationships, we used 38 histone modification types including H2A.Z and CTCF, and DNA methylation status at CpG islands across chromosome 6, 20, and 22 of human CD4+ T cell. We utilized Bayesian network to construct regulatory network.Results and Discussion: We found several meaningful relationships supported by previous studies. In addition, our results show that histone modifications can be clustered into several groups with different regulatory properties. Based on those findings we predicted the status of methylation level at CpG islands with high accuracy, and suggested core-regulatory network to control DNA methylation status.
SH3 Domain-Peptide Binding Energy Calculations Based on Structural Ensemble and Multiple Peptide Templates
Seungpyo Hong,Taesu Chung,Dongsup Kim
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0012654
Abstract: SH3 domains mediate signal transduction by recognizing short peptides. Understanding of the driving forces in peptide recognitions will help us to predict the binding specificity of the domain-peptide recognition and to understand the molecular interaction networks of cells. However, accurate calculation of the binding energy is a tough challenge. In this study, we propose three ideas for improving our ability to predict the binding energy between SH3 domains and peptides: (1) utilizing the structural ensembles sampled from a molecular dynamics simulation trajectory, (2) utilizing multiple peptide templates, and (3) optimizing the sequence-structure mapping. We tested these three ideas on ten previously studied SH3 domains for which SPOT analysis data were available. The results indicate that calculating binding energy using the structural ensemble was most effective, clearly increasing the prediction accuracy, while the second and third ideas tended to give better binding energy predictions. We applied our method to the five SH3 targets in DREAM4 Challenge and selected the best performing method.
Application of nonnegative matrix factorization to improve profile-profile alignment features for fold recognition and remote homolog detection
Inkyung Jung, Jaehyung Lee, Soo-Young Lee, Dongsup Kim
BMC Bioinformatics , 2008, DOI: 10.1186/1471-2105-9-298
Abstract: The performance of fold recognition and remote homolog detection using NMF features is compared to that of the unmodified profile-profile alignment (PPA) features by estimating Receiver Operating Characteristic (ROC) scores. The overall performance is noticeably improved. For fold recognition at the fold level, SVM with NMF features recognize 30% of homolog proteins at > 0.99 ROC scores, while original PPA feature, HHsearch, and PSI-BLAST recognize almost none. For detecting remote homologs that are related at the superfamily level, NMF features also achieve higher performance than the original PPA features. At > 0.90 ROC50 scores, 25% of proteins with NMF features correctly detects remotely related proteins, whereas using original PPA features only 1% of proteins detect remote homologs. In addition, we investigate the effect of number of positive training examples and the number of basis vectors on performance improvement. We also analyze the ability of NMF to extract essential features by comparing NMF basis vectors with functionally important sites and structurally conserved regions of proteins. The results show that NMF basis vectors have significant overlap with functional sites from PROSITE and with structurally conserved regions from the multiple structural alignments generated by MUSTANG. The correlation between NMF basis vectors and biologically essential parts of proteins supports our conjecture that NMF basis vectors can explicitly represent important sites of proteins.The present work demonstrates that applying NMF to profile-profile alignments can reveal essential features of proteins and that these features significantly improve the performance of fold recognition and remote homolog detection.Nonnegative matrix factorization (NMF) is a feature extraction method that has a property of intuitive part-based representation of the original feature [1]. Due to the non-negativity constraint, the parts produced by NMF can be interpreted as subsets of elements
Predicting and improving the protein sequence alignment quality by support vector regression
Minho Lee, Chan-seok Jeong, Dongsup Kim
BMC Bioinformatics , 2007, DOI: 10.1186/1471-2105-8-471
Abstract: In this work, we develop a method to predict the quality of the alignment between a query and a template. We train the support vector regression (SVR) models to predict the MaxSub scores as a measure of alignment quality. The alignment between a query protein and a template of length n is transformed into a (n + 1)-dimensional feature vector, then it is used as an input to predict the alignment quality by the trained SVR model. Performance of our work is evaluated by various measures including Pearson correlation coefficient between the observed and predicted MaxSub scores. Result shows high correlation coefficient of 0.945. For a pair of query and template, 48 alignments are generated by changing alignment options. Trained SVR models are then applied to predict the MaxSub scores of those and to select the best alignment option which is chosen specifically to the query-template pair. This adaptive selection procedure results in 7.4% improvement of MaxSub scores, compared to those when the single best parameter option is used for all query-template pairs.The present work demonstrates that the alignment quality can be predicted with reasonable accuracy. Our method is useful not only for selecting the optimal alignment parameters for a chosen template based on predicted alignment quality, but also for filtering out problematic templates that are not suitable for structure prediction due to poor alignment accuracy. This is implemented as a part in FORECAST, the server for fold-recognition and is freely available on the web at http://pbil.kaist.ac.kr/forecast webciteAs the number of protein sequences is exponentially growing, knowledge on their structures and functions is lagging far behind the growth rate of the number of new protein sequences because the experiments to determine structures and functions are difficult and time-consuming. One way to resolve this problem is computational methods such as structure and function prediction. In the case of protein structure p
Inferring Relative Activity between Pathway and Downstream Genes to Classify Melanoma Cancer Progression
Inkyung Jung,Jungsul Lee,Chulhee Choi,Dongsup Kim
Interdisciplinary Bio Central , 2011,
Abstract: Introduction: Many signal transduction pathways mediate cell’s behavior by regulating expression level of involved genes. Abnormal behavior indicates loss of regulatory potential of pathways, and this can be attributed to loss of expression regulation of downstream genes. Therefore, function of pathways should be assessed by activity of a pathway itself and relative activity between a pathway and downstream genes, simultaneously. Results and Discussion: In this study, we suggested a new method to assess pathway’s function by introducing concept of ‘responsiveness’. The responsiveness was defined as a relative activity between a pathway itself and its downstream genes. The expression level of a downstream gene as a function of an upstream pathway activation characterizes disease status. In this aspect, by using the responsiveness we predicted potential progress in cancer development. We applied our method to predict primary and metastatic status of melanoma cancer. The result shows that the responsiveness-based approach achieves better performance than using gene or pathway information alone. The mean of ROC scores in the responsiveness-based approach was 0.90 for GSE7553 data set, increased more than 40% compared to a gene-based method. Moreover, identifying the abnormal regulatory patterns between pathway and its downstream genes provided more biologically interpretable information compared to gene or pathway based approaches.
PostMod: sequence based prediction of kinase-specific phosphorylation sites with indirect relationship
Jung Inkyung,Matsuyama Akihisa,Yoshida Minoru,Kim Dongsup
BMC Bioinformatics , 2010, DOI: 10.1186/1471-2105-11-s1-s10
Abstract: Background Post-translational modifications (PTMs) have a key role in regulating cell functions. Consequently, identification of PTM sites has a significant impact on understanding protein function and revealing cellular signal transductions. Especially, phosphorylation is a ubiquitous process with a large portion of proteins undergoing this modification. Experimental methods to identify phosphorylation sites are labor-intensive and of high-cost. With the exponentially growing protein sequence data, development of computational approaches to predict phosphorylation sites is highly desirable. Results Here, we present a simple and effective method to recognize phosphorylation sites by combining sequence patterns and evolutionary information and by applying a novel noise-reducing algorithm. We suggested that considering long-range region surrounding a phosphorylation site is important for recognizing phosphorylation peptides. Also, from compared results to AutoMotif in 36 different kinase families, new method outperforms AutoMotif. The mean accuracy, precision, and recall of our method are 0.93, 0.67, and 0.40, respectively, whereas those of AutoMotif with a polynomial kernel are 0.91, 0.47, and 0.17, respectively. Also our method shows better or comparable performance in four main kinase groups, CDK, CK2, PKA, and PKC compared to six existing predictors. Conclusion Our method is remarkable in that it is powerful and intuitive approach without need of a sophisticated training algorithm. Moreover, our method is generally applicable to other types of PTMs.
A checkpoints capturing timing-robust Boolean model of the budding yeast cell cycle regulatory network
Changki Hong, Minho Lee, Dongsup Kim, Dongsan Kim, Kwang-Hyun Cho, Insik Shin
BMC Systems Biology , 2012, DOI: 10.1186/1752-0509-6-129
Abstract: To construct a timing-robust Boolean model that preserves checkpoint conditions of the budding yeast cell cycle, we used a model verification technique, ‘model checking’. By utilizing automatic and exhaustive verification of model checking, we found that previous models cannot properly capture essential checkpoint conditions in the presence of timing variations. In particular, such models violate the M phase checkpoint condition so that it allows a division of a budding yeast cell into two before the completion of its full DNA replication and synthesis. In this paper, we present a timing-robust model that preserves all the essential checkpoint conditions properly against timing variations. Our simulation results show that the proposed timing-robust model is more robust even against network perturbations and can better represent the nature of cell cycle than previous models.To our knowledge this is the first work that rigorously examined the timing robustness of the cell cycle process of budding yeast with respect to checkpoint conditions using Boolean models. The proposed timing-robust model is the complete state-of-the-art model that guarantees no violation in terms of checkpoints known to date.A cell must undergo the process of duplicating all its components and separating them, more or less evenly, to two daughter cells such that each daughter has the information and dynamics necessary to repeat the process. Such cell cycle dynamics are known in more detail for the budding yeast, Saccharomyces cerevisiae, compared to other eukaryotic organism [1,2]. The cell cycle process of budding yeast consists of four phases: G1, S, G2, and M. Initiated by stimulation of the G1 stationary phase, the cell cycle sequence proceeds (i.e., G1→S→G2→M) and finally returns to the G1 stationary phase. It is important to reach the final phase after completing each phase properly since any mistakes can cause significant defect to the cell cycle process. Hence, a cell verifies whether es
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