• Genomics & Informatics
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• 제16권4호
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• pp.23.1-23.5
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• 2018

Virus taxonomy was initially determined by clinical experiments based on phenotype. However, with the development of sequence analysis methods, genotype-based classification was also applied. With the development of genome sequence analysis technology, there is an increasing demand for virus taxonomy to be extended from in vivo and in vitro to in silico. In this study, we verified the consistency of the current International Committee on Taxonomy of Viruses taxonomy using an in silico approach, aiming to identify the specific sequence for each virus. We applied this approach to norovirus in Caliciviridae, which causes 90% of gastroenteritis cases worldwide. First, based on the dogma "protein structure determines its function," we hypothesized that the specific sequence can be identified by the specific structure. Firstly, we extracted the coding region (CDS). Secondly, the CDS protein sequences of each genus were annotated by the conserved domain database (CDD) search. Finally, the conserved domains of each genus in Caliciviridae are classified by RPS-BLAST with CDD. The analysis result is that Caliciviridae has sequences including RNA helicase in common. In case of Norovirus, Calicivirus coat protein C terminal and viral polyprotein N-terminal appears as a specific domain in Caliciviridae. It does not include in the other genera in Caliciviridae. If this method is utilized to detect specific conserved domains, it can be used as classification keywords based on protein functional structure. After determining the specific protein domains, the specific protein domain sequences would be converted to gene sequences. This sequences would be re-used one of viral bio-marks.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2022년도 추계학술대회
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• pp.231-231
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• 2022

The GASA protein (Gibberellic acid-stimulated Arabidopsis) are family of small cysteine-rich peptides found in plants. These GASA gene family mainly involved in biotic/abiotic stress responses and plant development. Despite being present in a wide plant species, their action and functions still remain unclear. In this study, using the in-silico analysis method we identified 41 GASA genes in peanuts (Arachis hypogaea L.). Based on the phylogenetic analysis 41 GASA genes are classified in the four major clusters and subclades. Mainly, clusters IV and III comprise the majority of GASA genes 15 and 11 genes respectively, followed by cluster I and cluster II with 9 and 6 genes respectively. Additionally, based on in-silico analysis we predicted the post-transcriptional and post-translational changes of GASA proteins under abiotic stresses such as drought and salt stress would aid our understanding of the regulatory mechanisms. Hence, a further study is planned to evaluate the expression of these GASA genes under stress in different plant tissues to elucidate the possible functional role of GASA genes in peanut plants. These findings might offer insightful data for peanut advancement.

• 대한한방내과학회지
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• 제27권4호
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• pp.888-894
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• 2006

Objectives : For the purpose of developing new anti-HIV agents from natural sources, the extracts of Ricinus communis were tested for their inhibitory effects on essential enzymes reverse transcriptase (RT), protease and alpha-glucosidase. Inhibition activity of major compounds of Ricinus communis were predicted from quantitative structure activity relationships (QSAR) in silico. Methods and Results : In the anti-HIV-1 RT using enzyme-linked oligonucleotide sorbent assay (ELOSA) method, water and methanol extracts (100ug/ml) of Ricinus communis showed strong activity of 94.2% and 82.7%, respectively. In the HIV-1 protease and alpha-glucosidase inhibition assay, neither water nor methanol extracts of Ricinus communis inhibited the activity of the enzyme to cleave any substrates as oligopeptides and oligosaccharides. Conclusions : We found that for these samples it is possible that the inhibition of the RT in vitro is due to the secondary metabolites of Ricinus communis such as ricinine and quercetin. It would beof great interest to identify the compounds which are responsible for this inhibition, since all therapeutically useful agents up to date are RT inhibitors.

• Journal of Microbiology and Biotechnology
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• 제21권10호
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• pp.1097-1100
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• 2011

A toxin produced by Pseudomonas tolaasii, tolaasin, causes brown blotch disease in mushrooms. Tolaasin forms pores on the cellular membrane and destroys cell structure. Inhibiting the ability of tolaasin to form ion channels may be an effective method to protect against attack by tolaasin. However, it is first necessary to elucidate the three-dimensional structure of the ion channels formed by tolaasin. In this study, the structure of the tolaasin ion channel was determined in silico based on data obtained from nuclear magnetic resonance experiments.

• Reproductive and Developmental Biology
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• 제34권3호
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• pp.153-159
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• 2010

The 34 potently pig pheromonal odorants (1-32, 5755 & 7113) through structure-based virtual screening and ligand-based virtual screening method were selected and their ADMET and pharmacokinetics characters were evaluated and discussed quantitatively. The pheromonal odorants were projected on the following pre-calculated models, Caco-2 cell permeability, blood-brain barrier permeation, hERG inhibition and volume-distribution. From the results of in silico study, it is found that an optimal compound (31) either penetrating or have a little ($P_{caco2}$=-8.143) for Caco-2 cell permeability, moderate penetrating ability ($P_{BBB}$=0.082) for blood-brain barrier permeation, the low QT prolongation ($P_{hERG}$=1.137) for the hERG $K^+$ channel inhibition, and low distribution into tissues ($P_{VD}$=-5.468) for volume-distribution. Therefore, it is predicted that the compound (31) a topical application may be preferable from these based foundings.

• 제어로봇시스템학회논문지
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• 제11권10호
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• pp.851-856
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• 2005

The DNA and protein data of diverse species have been daily discovered and deposited in the public archives according to each established format. Database systems in the public archives provide not only an easy-to-use, flexible interface to the public, but also in silico analysis tools of unidentified sequence data. Of such in silico analysis tools, multiple sequence alignment [1] methods relying on pairwise alignment and Smith-Waterman algorithm [2] enable us to identify unknown DNA, protein sequences or phylogenetic relation among several species. However, in the existing multiple alignment method as the number of sequences increases, the runtime increases exponentially. In order to remedy this problem, we adopted a parallel processing suffix tree algorithm that is able to search for common subsequences at one time without pairwise alignment. Also, the cross-matching subsequences triggering inexact-matching among the searched common subsequences might be produced. So, the cross-matching masking process was suggested in this paper. To identify the function of the clusters generated by suffix tree clustering, BLAST was combined with a clustering tool. Our clustering and annotating tool is summarized as the following steps: (1) construction of suffix tree; (2) masking of cross-matching pairs; (3) clustering of gene sequences and (4) annotating gene clusters by BLAST search. The system was successfully evaluated with 22 gene sequences in the pyrubate pathway of bacteria, clustering 7 clusters and finding out representative common subsequences of each cluster

• ALGAE
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• 제38권4호
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• pp.295-306
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• 2023

Human coronavirus diseases, particularly severe acute respiratory syndrome coronavirus 2, still remain a persistent public health issue, and many recent studies are focusing on the quest for new leads against coronaviruses. To contribute to this growing pool of knowledge and explore the available marine natural products against coronaviruses, this study investigated the antiviral effects of fucoxanthin isolated from Sargassum siliquastrum-a brown alga found on Jeju Island, South Korea. The antiviral effects of fucoxanthin were confirmed in severe acute respiratory syndrome coronavirus 2-infected Vero cells, and its structural characteristics were verified in silico using molecular docking and molecular dynamic simulations and in vitro colorimetric method. Fucoxanthin inhibited the infection in a concentration-dependent manner, without showing cytotoxicity. Molecular docking simulations revealed that fucoxanthin binds to the angiotensinconverting enzyme 2-spike protein (binding energy -318.306 kcal mol^-1) and main protease (binding energy -205.118 kcal mol^-1). Moreover, molecular dynamic simulations showed that fucoxanthin remains docked to angiotensin-converting enzyme 2-spike protein for 20 ns, whereas it breaks away from main protease after 3 ns. Also, the in silico prediction of the fucoxanthin was verified through the in vitro colorimetric method by inhibiting the binding between angiotensinconverting enzyme 2 and spike protein in a concentration-dependent manner. These results indicate that fucoxanthin exhibits antiviral effects against severe acute respiratory syndrome coronavirus 2 by blocking the entry of the virus. Therefore, fucoxanthin from S. siliquastrum can be a potential candidate for treating coronavirus infection.

• Advances in nano research
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• 제15권2호
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• pp.165-174
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• 2023

The study investigated the effect of geometric structures of nano-patterned surfaces, such as peak sharpness, height, width, aspect ratio, and spacing, on mechano-bactericidal properties. Here, in silico models were developed to explain surface interactions with Escherichia coli. Numerical solutions were performed based on the finite element method and verified by the artificial neural network method. An E. coli cell adhered to the nano surface formed elastic and creep deformation models, and the cells' maximum deformation, maximum stress, and maximum strain were calculated. The results determined that the increase in peak sharpness, aspect ratio, and spacing values increased the maximum deformation, maximum stress, and maximum strain on E. coli cell. In addition, the results showed that FEM and ANN methods were in good agreement with each other. This study proved that the geometrical structures of nano-patterned surfaces have an important role in the mechano-bactericidal effect.

• 인지과학
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• 제28권4호
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• pp.299-314
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• 2017

In-silico 기반의 약물-표적 단백질 연관관계 예측은 신약 탐색 단계에서 매우 중요하다. 그러나 기존의 예측모델은 입력 값이 고정적이며 표적 단백질의 특질 값이 가공된 데이터로 한정됨으로써 예측 모델의 확장성과 유연성이 부족하다. 본 논문에서는 약물-표적 단백질 연관관계를 예측하는 확장 가능한 형태의 머신러닝 모델을 소개한다. 확장 가능한 머신러닝 모델의 핵심 아이디어는 쌍기반의 뉴럴 네트워크로써, 약물과 단백질의 미가공 데이터를 사용하여 특질을 추출하고 특질 값을 각각의 뉴럴 네트워크 레이어에 입력한다. 이 방법은 추가적인 지식없이 자동적으로 약물과 단백질의 특질을 추출한다. 또한 쌍기반 레이어는 특질 값을 풍부한 저차원의 벡터로 향상 시킴으로써 입력 값의 차이로 인한 편향 학습을 방지한다. PubChem BioAssay(PCBA) 데이터 셋에 기반한 5-폴드 교차 검증법을 통하여 제안한 모델의 성능을 평가했으며, 이전의 모델보다 우월한 성능을 보였다.

• 통합자연과학논문집
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• 제5권4호
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• pp.216-219
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• 2012

Structure-based drug design possibly benefit from in silico methods that precisely predict the binding affinity of small molecules to target macromolecules. There are many limitations arise from the difficulty of predicting the binding affinity of a small molecule to a biological target with the current scoring functions. There is thus a strong interest in novel methodologies based on MD simulations that claim predictions of greater accuracy than current scoring functions, helpful for a regular use designed for drug discovery in the pharmaceutical industry. Herein, we report a short review on free energy calculations using MMPBSA method a useful method in structure based drug discovery.