Biomedical subjects

Kyungsook Han

Publications and source records attributed to Kyungsook Han.

13 recordsLinked to original sources

PubMed2004

Predicting genes expressed via -1 and +1 frameshifts.

Computational identification of ribosomal frameshift sites in genomic sequences is difficult due to their diverse nature, yet it provides useful information for understanding the underlying mechanisms and discovering new genes. We have developed an algorithm that searches entire genomic or mRNA sequences for frameshifting sites, and implements the algorithm as a web-based program called FSFinder (Frameshift Signal Finder). The current version of FSFinder is capable of finding -1 frameshift sites on heptamer sequences X XXY YYZ, and +1 frameshift sites for two genes: protein chain release factor B (prfB) and ornithine decarboxylase antizyme (oaz). We tested FSFinder on approximately 190 genomic and partial DNA sequences from a number of organisms and found that it predicted frameshift sites efficiently and with greater sensitivity and specificity than existing approaches. It has improved sensitivity because it considers many known components of a frameshifting cassette and searches these components on both + and - strands, and its specificity is increased because it focuses on overlapping regions of open reading frames and prioritizes candidate frameshift sites. FSFinder is useful for discovering unknown genes that utilize alternative decoding, as well as for analyzing frameshift sites. It is freely accessible at http://wilab.inha.ac.kr/FSFinder/.

Algorithms↗

PubMed2004

Isolation of specific and high-affinity RNA aptamers against NS3 helicase domain of hepatitis C virus.

Hepatitis C virus (HCV)-encoded nonstructural protein 3 (NS3) possesses protease, NTPase, and helicase activities, which are considered essential for viral proliferation. Thus, HCV NS3 is a good putative therapeutic target protein for the development of anti-HCV agents. In this study, we isolated specific RNA aptamers to the helicase domain of HCV NS3 from a combinatorial RNA library with 40-nucleotide random sequences using in vitro selection techniques. The isolated RNAs were observed to very avidly bind the HCV helicase with an apparent Kd of 990 pM in contrast to original pool RNAs with a Kd of >1 microM. These RNA ligands appear to impede binding of substrate RNA to the HCV helicase and can act as potent decoys to competitively inhibit helicase activity with high efficiency compared with poly(U) or tRNA. The minimal binding domain of the ligands was determined to evaluate the structural features of the isolated RNA molecules. Interestingly, part of binding motif of the RNA aptamers consists of similar secondary structure to the 3'-end of HCV negative-strand RNA. Moreover, intracellular NS3 protein can be specifically detected in situ with the RNA aptamers, indicating that the selected RNAs are very specific to the HCV NS3 helicase. Furthermore, the RNA aptamers partially inhibited RNA synthesis of HCV subgenomic replicon in Huh-7 hepatoma cell lines. These results suggest that the RNA aptamers selected in vitro could be useful not only as therapeutic and diagnostic agents of HCV infection but also as a powerful tool for the study of HCV helicase mechanism.

Adenosine Triphosphatases↗

PubMed2004

WebInterViewer: visualizing and analyzing molecular interaction networks.

Molecular interaction networks, such as those involving protein-protein and protein-DNA interactions, often consist of thousands of nodes or even more, which severely limits the usefulness of many graph drawing tools because they become too slow for interactive analysis of the networks and because they produce cluttered drawings with many edge crossings. We present a new, fast-layout algorithm and its implementation called WebInterViewer for visualizing large-scale molecular interaction networks. WebInterViewer (i) finds a layout of the connected components of an entire network, (ii) finds a global layout of nodes with respect to pivot nodes within the connected components and (iii) refines the local layout of each connected component by first relocating midnodes with respect to their cutvertices and the direct neighbors of the cutvertices, and then relocating all nodes with respect to their neighbors within distance 2. The advantages of WebInterViewer over classical graph drawing methods include the facts that (i) it is an order of magnitude faster, (ii) it can visualize data directly from protein interaction databases and (iii) it provides several abstraction and comparison operations for analyzing large-scale biological networks effectively. WebInterViewer is accessible at http://interviewer.inha.ac.kr/.

Computer Graphics↗

PubMed2004

HPID: the Human Protein Interaction Database.

UNLABELLED: The Human Protein Interaction Database (http://www.hpid.org) was designed (1) to provide human protein interaction information pre-computed from existing structural and experimental data, (2) to predict potential interactions between proteins submitted by users and (3) to provide a depository for new human protein interaction data from users. Two types of interaction are available from the pre-computed data: (1) interactions at the protein superfamily level and (2) those transferred from the interactions of yeast proteins. Interactions at the superfamily level were obtained by locating known structural interactions of the PDB in the SCOP domains and identifying homologs of the domains in the human proteins. Interactions transferred from yeast proteins were obtained by identifying homologs of the yeast proteins in the human proteins. For each human protein in the database and each query submitted by users, the protein superfamilies and yeast proteins assigned to the protein are shown, along with their interacting partners. We have also developed a set of web-based programs so that users can visualize and analyze protein interaction networks in order to explore the networks further. AVAILABILITY: http://www.hpid.org.

Algorithms↗

PubMed2004

Three-dimensional visualization of protein interaction networks.

Protein interaction networks provide us with contextual information within which protein function can be interpreted and will assist many biomedical studies. We have developed a new force-directed layout algorithm for visualizing protein interactions in three-dimensional space. Our algorithm divides nodes into three groups based on their interacting properties: bi-connected sub-graph in the center, terminal nodes at the outermost region, and the rest in between them. Experimental results show that our algorithm efficiently generates a clear and aesthetically pleasing drawing of large-scale protein interaction networks and that it is an order of magnitude faster than other force-directed layouts.

Algorithms↗

PubMed2003

Discovering the interaction propensities of amino acids and nucleotides from protein-RNA complexes.

With the availability of many genome sequences, the mining of biological data is attracting much attention, most of it limited to the sequences of macromolecules. Sequence data are easy to analyze as they can be treated as strings of characters, whereas the structure of a macromolecule is much more complex. We developed a set of algorithms to analyze the structures of protein-RNA complexes at the atomic level and used them to analyze protein-RNA interactions using structural data on 51 protein-RNA complexes. The analysis revealed, among other things, that: (1) polar and charged amino acids have a strong tendency to interact with nucleotides, (2) arginine and asparagine tend to hydrogen bond with uracil, and (3) histidine favors uracil in water-mediated bonding with RNA. We analyzed a large set of structural data of protein-RNA complexes involving water-mediated hydrogen bonds as well as direct hydrogen bonds. The interaction patterns discovered from the analysis provide useful information for predicting the structure of RNA that binds proteins, and of proteins that bind RNA.

Algorithms↗

PubMed2003

A fast layout algorithm for protein interaction networks.

MOTIVATION: Graph drawing algorithms are often used for visualizing relational information, but a naive implementation of a graph drawing algorithm encounters real difficulties when drawing large-scale graphs such as protein interaction networks. RESULTS: We have developed a new, extremely fast layout algorithm for visualizing large-scale protein interaction networks in the three-dimensional space. The algorithm (1) first finds a layout of connected components of an entire network, (2) finds a global layout of nodes with respect to pivot nodes within a connected component and (3) refines the local layout of each connected component by first relocating midnodes with respect to their cutvertices and direct neighbors of the cutvertices and then by relocating all nodes with respect to their neighbors within distance 2. Advantages of this algorithm over classical graph drawing methods include: (1) it is an order of magnitude faster, (2) it can directly visualize data from protein interaction databases and (3) it provides several abstraction and comparison operations for effectively analyzing large-scale protein interaction networks. AVAILABILITY: http://wilab.inha.ac.kr/interviewer/

Algorithms↗

PubMed2003

Computational analysis of hydrogen bonds in protein-RNA complexes for interaction patterns.

Structural analysis of protein-RNA complexes is labor-intensive, yet provides insight into the interaction patterns between a protein and RNA. As the number of protein-RNA complex structures reported has increased substantially in the last few years, a systematic method is required for automatically identifying interaction patterns. This paper presents a computational analysis of the hydrogen bonds in the most representative set of protein-RNA complexes. The analysis revealed several interesting interaction patterns. (1) While residues in the beta-sheets favored unpaired nucleotides, residues in the helices showed no preference and residues in turns favored paired nucleotides. (2) The backbone hydrogen bonds were more dominant than the base hydrogen bonds in the paired nucleotides, but the reverse was observed in the unpaired nucleotides. (3) The protein-RNA complexes contained more paired nucleotides than unpaired nucleotides, but the unpaired nucleotides were observed more frequently interacting with the proteins. And (4) Arg-U, Thr-A, Lys-A, and Asn-U were the most frequently observed pairs. The interaction patterns discovered from the analysis will provide us with useful information in predicting the structure of the RNA binding protein and the structure of the protein binding RNA.

Amino Acids↗

PubMed2003

Prevention of passively transferred experimental autoimmune myasthenia gravis by an in vitro selected RNA aptamer.

Myasthenia gravis (MG) and its animal model, experimental autoimmune MG (EAMG), are mainly caused by autoantibodies directed against acetylcholine receptors (AChR) located in the postsynaptic muscle membrane. Previously, we isolated an RNA aptamer with 2'-fluoropyrimidines using in vitro selection techniques that acted as an effective decoy against both a rat monoclonal antibody called mAb198, which recognizes the main immunogenic region on the AChR, and a significant fraction of patient autoantibodies with MG. To investigate the therapeutic potential of the RNA, we tested the ability of the RNA aptamer to protect the receptors in vivo from mAb198. Clinical symptoms of EAMG in rats engendered by passive transfer of mAb198 were efficiently inhibited by a truncated RNA aptamer that was modified with polyethylene glycol, but not by control scrambled RNA. Moreover, the loss of AChR in the animals induced by the antibody was also significantly blocked with the modified RNA aptamer. These results suggested that RNA aptamers could be applied for antigen-specific treatment for autoimmune diseases including MG.

Animals↗

PubMed2003

PSEUDOVIEWER2: Visualization of RNA pseudoknots of any type.

Visualizing RNA pseudoknot structures is computationally more difficult than depicting RNA secondary structures, because a drawing of a pseudoknot structure is a graph (and possibly a nonplanar graph) with inner cycles within the pseudoknot, and possibly outer cycles formed between the pseudoknot and other structural elements. We previously developed PSEUDOVIEWER for visualizing H-type pseudoknots. PSEUDOVIEWER2 improves on the first version in many ways: (i) PSEUDOVIEWER2 is more general because it can visualize a pseudoknot of any type, including H-type pseudoknots, as a planar graph; (ii) PSEUDOVIEWER2 computes a drawing of RNA structures much more efficiently and is an order of magnitude faster in actual running time; and (iii) PSEUDOVIEWER2 is a web-based application program. Experimental results demonstrate that PSEUDOVIEWER2 generates an aesthetically pleasing drawing of pseudoknots of any type and that the new representation offered by PSEUDOVIEWER2 ensures uniform and clear drawings, with no edge crossing, for all types of pseudoknots. The PSEUDOVIEWER2 algorithm is the first developed for the automatic drawing of RNA secondary structures, including pseudoknots of any type. PSEUDOVIEWER2 is accessible at http://wilab.inha.ac.kr/pseudoviewer2/.

Algorithms↗

PubMed2003

Visualization and analysis of protein interactions.

SUMMARY: We have developed a new program called InterViewer for drawing large-scale protein interaction networks in three-dimensional space. Unique features of InterViewer include (1) it is much faster than other recent implementations of drawing algorithms; (2) it can be used not only for visualizing protein interactions but also for analyzing them interactively; and (3) it provides an integrated framework for querying protein interaction databases and directly visualizes the query results. AVAILABILITY: http://wilab.inha.ac.kr/protein/

Algorithms↗

PubMed2003

Complexity management in visualizing protein interaction networks.

MOTIVATION: Protein-protein interaction networks often consist of thousands of nodes or more. This severely limits the utility of many graph drawing tools because they become too slow for an interactive analysis of the networks and because they produce cluttered drawings with many edge crossings. RESULTS: A new layout algorithm with complexity management operations in visualizing a large-scale protein interaction network was developed and implemented in a program called InterViewer3. InterViewer3 simplifies a complex network by collapsing a group of nodes with the same interacting partners into a composite node and by replacing a clique with a star-shaped subgraph. The experimental results demonstrated that InterViewer3 is one order of magnitude faster than the other drawing programs and that its complexity management is successful.

Algorithms↗

PubMed2002

PseudoViewer: automatic visualization of RNA pseudoknots.

MOTIVATION: Several algorithms have been developed for drawing RNA secondary structures, however none of these can be used to draw RNA pseudoknot structures. In the sense of graph theory, a drawing of RNA secondary structures is a tree, whereas a drawing of RNA pseudoknots is a graph with inner cycles within a pseudoknot as well as possible outer cycles formed between a pseudoknot and other structural elements. Thus, RNA pseudoknots are more difficult to visualize than RNA secondary structures. Since no automatic method for drawing RNA pseudoknots exists, visualizing RNA pseudoknots relies on significant amount of manual work and does not yield satisfactory results. The task of visualizing RNA pseudoknots by hand becomes more challenging as the size and complexity of the RNA pseudoknots increase. RESULTS: We have developed a new representation and an algorithm for drawing H-type pseudoknots with RNA secondary structures. Compared to existing representations of H-type pseudoknots, the new representation ensures uniform and clear drawings with no edge crossing for any H-type pseudoknots. To the best of our knowledge, this is the first algorithm for automatically drawing RNA pseudoknots with RNA secondary structures. The algorithm has been implemented in a Java program, which can be executed on any computing system. Experimental results demonstrate that the algorithm generates an aesthetically pleasing drawing of all H-type pseudoknots. The results have also shown that the drawing has high readability, enabling the user to quickly and easily recognize the whole RNA structure as well as the pseudoknots themselves.

Algorithms↗