• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2003년도 제2차 연례학술대회 발표논문집
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• pp.133-138
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• 2003

The prediction of protein secondary structure has been an important bioinformatics tool that is an essential component of the template-based protein tertiary structure prediction process. It has been known that the predicted secondary structure information improves both the fold recognition performance and the alignment accuracy. In this paper, we describe several novel ideas that may improve the prediction accuracy. The main idea is motivated by an observation that the protein's structural information, especially when it is combined with the evolutionary information, significantly improves the accuracy of the predicted tertiary structure. From the non-redundant set of protein structures, we derive the 'potential' parameters for the protein secondary structure prediction that contains the structural information of proteins, by following the procedure similar to the way to derive the directional information table of GOR method. Those potential parameters are combined with the frequency matrices obtained by running PSI-BLAST to construct the feature vectors that are used to train the support vector machines (SVM) to build the secondary structure classifiers. Moreover, the problem of huge model file size, which is one of the known shortcomings of SVM, is partially overcome by reducing the size of training data by filtering out the redundancy not only at the protein level but also at the feature vector level. A preliminary result measured by the average three-state prediction accuracy is encouraging.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2004년도 The 3rd Annual Conference for The Korean Society for Bioinformatics Association of Asian Societies for Bioinformatics 2004 Symposium
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• pp.250-261
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• 2004

A novel method for ab initio prediction of protein tertiary structures, PROFESY (PROFile Enumerating SYstem), is introduced. This method utilizes secondary structure prediction information and fragment assembly. The secondary structure prediction of proteins is performed with the PREDICT method which uses PSI-BLAST to generate profiles and a distance measure in the pattern space. In order to predict the tertiary structure of a protein sequence, we assemble fragments in the fragment library constructed as a byproduct of PREDICT. The tertiary structure is obtained by minimizing the potential energy using the conformational space annealing method which enables one to sample diverse low lying minima of the energy function. We apply PROFESY for prediction of some proteins with known structures, which shows good performances. We also participated in CASP5 and applied PROFESY to new fold targets for blind predictions. The results were quite promising, despite the fact that PROFESY was in its early stage of development. In particular, the PROFESY result is the best for the hardest target T0161.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2005년도 추계학술발표대회 및 정기총회
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• pp.15-18
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• 2005

A ribonucleic acid (RNA) is one of the two types of nucleic acids found in living organisms. An RNA molecule represents a long chain of monomers called nucleotides. The sequence of nucleotides of an RNA molecule constitutes its primary structure, and the pattern of pairing between nucleotides determines the secondary structure of an RNA. Non-coding RNA genes produce transcripts that exert their function without ever producing proteins. Predicting the secondary structure of non-coding RNAs is very important for understanding their functions. We focus on Nussinov's algorithm as useful techniques for predicting RNA secondary structures. We introduce a new traceback matrix and scoring table to improve above algorithm. And the improved prediction algorithm provides better levels of performance than the originals.

• Molecules and Cells
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• 제23권2호
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• pp.228-238
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• 2007

Since molecular structure of hnRNP is not available in foreseeable future, it is best to construct a working model for hnRNP structure. A geometric problem, assembly of $700{\pm}20$ nucleotides with 48 proteins, is visualized by a frame work in which all the proteins participate in primary binding, followed by secondary, tertiary and quaternary binding with neighboring proteins without additional import. Thus, 40S hnRNP contains crown-like secondary structure (48 stemloops) and appearance of 6 petal (octamers) rose-like architectures. The proteins are wrapped by RNA. Co-transcriptional folding for RNP fibril of FMR1 gene can produce 2,571 stem-loops with frequency of 1 stem-loop/15.3 nucleotides and 53 40S hnRNP beaded structure. By spliceosome driven reactions, there occurs removal of 16 separate lariated RNPs, joining 17 separate beaded exonic structures and anchoring EJC on each exon junction. Skipping exon 12 has 5'GU, 3'AG and very compact folding pattern with frequency of 1 stem-loop per 12 nucleotides in short exon length (63 nucleotides). 5' end of exon 12 contains SS (Splicing Silencer) element of UAGGU. In exons 10, 15 and 17 where both regular and alternative splice sites exist, SS (hnRNP A1 binding site) is observed at the regular splicing site. End products are mature FMR-1 mRNP, 4 species of Pri-microRNAs derived from introns 7,9,15 and 3'UTR of exon17, respectively. There may also be some other regulatory RNAs containing ALU/Line elements as well.

• Molecules and Cells
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• 제41권10호
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• pp.889-899
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• 2018

Intrinsically disordered proteins (IDPs) are highly unorthodox proteins that do not form three-dimensional structures under physiological conditions. The discovery of IDPs has destroyed the classical structure-function paradigm in protein science, 3-D structure = function, because IDPs even without well-folded 3-D structures are still capable of performing important biological functions and furthermore are associated with fatal diseases such as cancers, neurodegenerative diseases and viral pandemics. Pre-structured motifs (PreSMos) refer to transient local secondary structural elements present in the target-unbound state of IDPs. During the last two decades PreSMos have been steadily acknowledged as the critical determinants for target binding in dozens of IDPs. To date, the PreSMo concept provides the most convincing structural rationale explaining the IDP-target binding behavior at an atomic resolution. Here we present a brief developmental history of PreSMos and describe their common characteristics. We also provide a list of newly discovered PreSMos along with their functional relevance.

• 한국자기공명학회논문지
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• 제16권1호
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• pp.22-33
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• 2012

Tid1, belonging to the Hsp40/DnaJ family of proteins, functions as a cochaperone of cytosolic and mitochondrial Hsp70 proteins. In particular, the N-terminal J-domain of Tid1 (Tid1-JD) constitutes the major binding sites for proteinprotein interactions with client proteins, including p53, as well as its partner chaperone, Hsp70. In the present study, soluble, recombinant protein of Tid1-JD could be obtained by using the pCold vector system, and backbone NMR assignments were completed using the isotope $[^{13}C/^{15}N]$-enriched protein. Far-UV CD result implied that Tid1-JD is an ${\alpha}$-helical protein and the secondary structure determined using chemical shift data sets indentified four ${\alpha}$-helices with a loop region containing the HPD (conserved tripeptide of His, Pro and Asp) motif. Additionally, NMR spectra under different conditions implied that the HPD motif, which is a critical region for protein-protein interactions of Tid1-JD, would possess dynamic properties.

• 한국정보통신학회논문지
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• 제22권1호
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• pp.26-32
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• 2018

단백질의 이차구조는 단백질의 진화, 구조, 기능을 연구하는데 중요한 정보이다. 단백질 서열 정보만을 이용하여 단백질의 이차 구조를 예측하는 분야에 심층 학습 방법들이 최근 들어 활발히 적용되고 있다. 이러한 방법에서 널리 사용되는 입력은 단백질 서열을 변환하여 만들어진 단백질 프로파일이다. 본 논문에서는 효과적인 단백질 프로파일을 얻기 위하여 단백질 서열 탐색 방법으로 PSI-BLAST와 더불어서 HHblits를 사용하였다. 단백질 프로파일의 구성에 사용되는 상동 단백질 서열을 결정하기 위한 유사도 문턱치와 상동 단백질 서열 정보를 반복적으로 사용하는 회수를 조절하였다. 합성곱 신경망과 순환 신경망을 사용하여 단백질 이차구조를 예측하였는데, 진화적 정보를 한번만 추가하여 만들어진 단백질 프로파일이 효과적이었다.

• 한국자기공명학회논문지
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• 제12권2호
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• pp.65-73
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• 2008

HP1298 (Swiss-Prot ID ; P65108) is an 72-residue protein from Helicobacter pylori strain 26695. The function of HP1298 was identified as Translation initiation factor IF-l based on sequence homology, and HP1298 is included in IF-l family. Here, we report the sequence-specific backbone resonance assignments of HP1298. About 97% of all the $^{1}HN$, $^{15}N$, $^{13}C{\alpha}$, $^{13}C{\beta}$, and $^{13}CO$ resonances could be assigned unambiguously. We could predict the secondary structure of HP1298, by analyzing the deviation of the $^{13}C{\alpha}$ and $^{13}C{\beta}$ shemical shifts from their respective random coil values. Secondary structure prediction shows that HP1298 consists of six $\beta$-strands. This study is a prerequisite for determining the solution structure of HP1298 and investigating the structure-function relationship of HP1298. Assigned chemical shift can be used for the study on interaction between HP1298 and other Helicobacter pylori proteins.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2004년도 The 3rd Annual Conference for The Korean Society for Bioinformatics Association of Asian Societies for Bioinformatics 2004 Symposium
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• pp.244-249
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• 2004

There have been many attempts to predict the secondary structure content of a protein from its primary sequence, which serves as the first step in a series of bioinformatics processes to gain knowledge of the structure and function of a protein. Most of them assumed that prediction relying on the information of the amino acid composition of a protein can be successful. Several approaches expanded the amount of information by including the pair amino acid composition of two adjacent residues. Recent methods achieved a remarkable improvement in prediction accuracy by using this expanded composition information. The overall average errors of two successful methods were 6.1% and 3.4%. This work was motivated by the observation that evolutionarily related proteins share the similar structure. After manipulating the values of the frequency matrix obtained by running PSI-BLAST, inputs of an artificial neural network were constructed by taking the ratio of the amino acid composition of the evolutionarily related proteins with a query protein to the background probability. Although we did not utilize the expanded composition information of amino acid pairs, we obtained the comparable accuracy, with the overall average error being 3.6%.

• 한국정보통신학회논문지
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• 제20권9호
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• pp.1816-1821
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• 2016

단백질은 대부분의 생물학적 과정에서 중대한 역할을 수행하고 있으므로, 단백질 진화, 구조와 기능을 알아내기 위하여 많은 연구가 수행되고 있는데, 단백질의 이차 구조는 이러한 연구의 중요한 기본적 정보이다. 본 연구는 대규모 단백질 구조 자료로부터 단백질 이차 구조 정보를 효과적으로 추출하여 미지의 단백질 서열이 가지는 이차 구조를 예측하려 한다. 질의 서열과 상동관계에 있는 단백질 구조자료내의 서열들을 광범위하게 찾아내기 위하여, 탐색에 사용하는 프로파일의 구성에 질의 서열과 유사한 서열들을 사용하고 갭을 허용하여 반복적인 탐색이 가능한 PSI-BLAST를 사용하였다. 상동 단백질들의 이차구조는 질의 서열과의 상동 관계의 강도에 따라 가중되어 이차 구조 예측에 기여되었다. 이차 구조를 각각 세 개와 여덟 개로 분류하는 예측 실험에서 상동 서열들과 신경망을 동시에 사용하여 93.28%와 88.79%의 정확도를 얻어서 기존 방법보다 성능이 향상되었다.