• Journal of the Korean Data and Information Science Society
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• v.16 no.3
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• pp.683-693
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• 2005

This paper presents a new transmembrane Protein topology prediction method which is an attempt to model the topological rules governing the topogenesis of transmembrane proteins. Context-dependent structural regions of the transmembrane protein are used as basic modeling units in order to effectively represent their topogenic roles during transmembrane protein assembly. These modeling units are modeled by means of a tied-state hidden Markov model, which can express the position-specific effect of amino acids during ransmembrane protein assembly. The performance of prediction improves with these modeling approaches. In particular, marked improvement of orientation prediction shows the validity of the proposed modeling. The proposed method is available at http://bioroutine.com/TRAPTOP.

• Journal of the Korean Data and Information Science Society
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• v.15 no.4
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• pp.1019-1031
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• 2004

This paper describes a new modeling method for the prediction of transmembrane protein topology. The structural regions of the transmembrane protein have been modeled by means of a multiple state hidden Markov model that has provided for the detailed modeling of the heterogeneous amino acid distributions of each structural region. Grammatical constraints have been incorporated to the prediction method in order to capture the biological order of membrane protein topology. The proposed method correctly predicted 76% of all membrane spanning regions and 92% sidedness of the integration when all membrane spanning regions were found correctly.

• The KIPS Transactions:PartD
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• v.11D no.3
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• pp.519-532
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• 2004

With the explosion of bioinformatics data such proteins and genes, biologists need a integrated system to analyze and organize large datasets that interact with heterogeneous types of biological data. In this paper, we propose a integration system based on a mediated data warehouse architecture using a XML model in order to combine protein related data at biology laboratories. A fact constellation model in this system is used at a common model for integration and an integrated schema it translated to a XML schema. In addition, to track source changes and provenance of data in an integrated database employ incremental update and management of sequence version. This paper shows modeling of integration for protein structures, sequences and classification of structures using the proposed system.

• The KIPS Transactions:PartB
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• v.12B no.2 s.98
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• pp.209-214
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• 2005

The use of protein interaction data is highly reliable for predicting functions to proteins without function in proteomics study. The computational studies on protein function prediction are mostly based on the concept of guilt-by-association and utilize large-scale interaction map from revealed protein-protein interaction data. This study compares graph-based approaches such as neighbor-counting and $\chi^2-statistics$ methods using protein-protein interaction data and proposes an approach that is effective in analyzing large-scale protein interaction data. The proposed approach is also based protein interaction map but sequence similarity and heuristic knowledge to make prediction results more reliable. The test result of the proposed approach is given for KDD Cup 2001 competition data along with those of neighbor-counting and $\chi^2-statistics$ methods.

• Molecules and Cells
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• v.25 no.3
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• pp.397-406
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• 2008

Computational modeling of signal transduction is currently attracting much attention as it can promote the understanding of complex signal transduction mechanisms. Although several mathematical models have been used to examine signaling pathways, little attention has been given to crosstalk mechanisms. In this study, an attempt was made to develop a computational model for the pathways involving growth-factor-mediated mitogen-activated protein kinase (MAPK) and phosphatidylinositol 3'-kinase/protein kinase B (PI3K/Akt). In addition, the dynamics of the protein activities were analyzed based on a set of kinetic data. The simulation approach integrates the information on several levels and predicts systems behavior. The in-silico analysis conducted revealed that the Raf and Akt pathways act independently.

• Journal of the Korean Magnetic Resonance Society
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• v.20 no.4
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• pp.102-108
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• 2016

With the rapid increase of data on protein-protein interactions, the need for delineating the 3D structures of huge protein complexes has increased. The protocols for determining nuclear magnetic resonance (NMR) structure can be applied to modeling complex structures coupled with sparse experimental restraints. In this report, I suggest the use of multiple rigid bodies for improving the efficiency of NMR-assisted structure modeling of huge complexes using CYANA. By preparing a region of known structure as a new type of residue that has no torsion angle, one can facilitate the search of the conformational spaces. This method has a distinct advantage over the rigidification of a region with synthetic distance restraints, particularly for the calculation of huge molecules. I have demonstrated the idea with calculations of decaubiquitins that are linked via Lys6, Lys11, Lys27, Lys29, Lys33, Lys48, or Lys63, or head to tail. Here, the ubiquitin region consisting of residues 1-70 was treated as a rigid body with a new residue. The efficiency of the calculation was further demonstrated in Lys48-linked decaubiquitin with ambiguous distance restraints. The approach can be readily extended to either protein-protein complexes or large proteins consisting of several domains.

• Journal of KIISE:Databases
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• v.30 no.6
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• pp.573-584
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• 2003

Recent massive data generation by genomics and proteomics requires bioinformatic tools to extract the biological meaning from the massive results. Here we introduce ROSPath, a database system to deal with information on reactive oxygen species (ROS)-mediated cell signaling pathways. It provides a structured repository for handling pathway related data and tools for querying, displaying, and analyzing pathways. ROSPath data model provides the extensibility for representing incomplete knowledge and the accessibility for linking the existing biochemical databases via the Internet. For flexibility and efficient retrieval, hierarchically structured data model is defined by using the object-oriented model. There are two major data types in ROSPath data model: ‘bio entity’ and ‘interaction’. Bio entity represents a single biochemical entity: a protein or protein state involved in ROS cell-signaling pathways. Interaction, characterized by a list of inputs and outputs, describes various types of relationship among bio entities. Typical interactions are protein state transitions, chemical reactions, and protein-protein interactions. A complex network can be constructed from ROSPath data model and thus provides a foundation for describing and analyzing various biochemical processes.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.32 no.2
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• pp.165-169
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• 1999

Experiments were conducted to evaluate a experimental model developed for the protein removal by foam separation. The foam separator was operated in well-mixed tank which would be considered as a completely mixed condition. The feasibility of foam separation to remove protein from sea water was investigated. Protein removal characteristics of the foam separator were obtained by batch experiments. To find the effect of the operating parameter to protein removal rate, the foam separation was carried with variation of initial protein concentration and superficial air velocity. The result indicated that the protein removal efficiency was increased with increasing protein concentration and superficial air velocity. The relationship between operation parameters and protein removal rate were evaluated by non-linear regression as the form of exponential function, Using both relationships, the simplified model was determined. The simplified foam separator operation model was verified by the batch operation. The simulation results showed a good relationship with the experimental data.

• Genomics & Informatics
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• v.19 no.4
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• pp.43.1-43.12
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• 2021

Campylobacter jejuni is one of the most prevalent organisms associated with foodborne illness across the globe causing campylobacteriosis and gastritis. Many proteins of C. jejuni are still unidentified. The purpose of this study was to determine the structure and function of a non-annotated hypothetical protein (HP) from C. jejuni. A number of properties like physiochemical characteristics, 3D structure, and functional annotation of the HP (accession No. CAG2129885.1) were predicted using various bioinformatics tools followed by further validation and quality assessment. Moreover, the protein-protein interactions and active site were obtained from the STRING and CASTp server, respectively. The hypothesized protein possesses various characteristics including an acidic pH, thermal stability, water solubility, and cytoplasmic distribution. While alpha-helix and random coil structures are the most prominent structural components of this protein, most of it is formed of helices and coils. Along with expected quality, the 3D model has been found to be novel. This study has identified the potential role of the HP in 2-methylcitric acid cycle and propionate catabolism. Furthermore, protein-protein interactions revealed several significant functional partners. The in-silico characterization of this protein will assist to understand its molecular mechanism of action better. The methodology of this study would also serve as the basis for additional research into proteomic and genomic data for functional potential identification.

• Genomics & Informatics
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• v.21 no.3
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• pp.41.1-41.11
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• 2023

The Dengue virus M protein is a 75 amino acid polypeptide with two helical transmembranes (TM). The TM domain oligomerizes to form an ion channel, facilitating viral release from the host cells. The M protein has a critical role in the virus entry and life cycle, making it a potent drug target. The oligomerization of the monomeric protein was studied using ab initio modeling and molecular dynamics simulation in an implicit membrane environment. The representative structures obtained showed pentamer as the most stable oligomeric state, resembling an ion channel. Glutamic acid, threonine, serine, tryptophan, alanine, isoleucine form the pore-lining residues of the pentameric channel, conferring an overall negative charge to the channel with approximate length of 51.9 Å. Residue interaction analysis for M protein shows that Ala94, Leu95, Ser112, Glu124, and Phe155 are the central hub residues representing the physicochemical interactions between domains. The virtual screening with 165 different ion channel inhibitors from the ion channel library shows monovalent ion channel blockers, namely lumacaftor, glipizide, gliquidone, glisoxepide, and azelnidipine to be the inhibitors with high docking scores. Understanding the three-dimensional structure of M protein will help design therapeutics and vaccines for Dengue infection.