• Title/Summary/Keyword: Interface Modeling

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Binding Mode Analysis of Bacillus subtilis Obg with Ribosomal Protein L13 through Computational Docking Study

  • Lee, Yu-No;Bang, Woo-Young;Kim, Song-Mi;Lazar, Prettina;Bahk, Jeong-Dong;Lee, Keun-Woo
    • Interdisciplinary Bio Central
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    • v.1 no.1
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    • pp.3.1-3.6
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    • 2009
  • Introduction: GTPases known as translation factor play a vital role as ribosomal subunit assembly chaperone. The bacterial Obg proteins ($Spo{\underline{0B}}$-associated ${\underline{G}}TP$-binding protein) belong to the subfamily of P-loop GTPase proteins and now it is considered as one of the new target for antibacterial drug. The majority of bacterial Obgs have been commonly found to be associated with ribosome, implying that these proteins may play a fundamental role in ribosome assembly or maturation. In addition, one of the experimental evidences suggested that Bacillus subtilis Obg (BsObg) protein binds to the L13 ribosomal protein (BsL13) which is known to be one of the early assembly proteins of the 50S ribosomal subunit in Escherichia coli. In order to investigate binding mode between the BsObg and the BsL13, protein-protein docking simulation was carried out after generating 3D structure of the BsL13 structure using homology modeling method. Materials and Methods: Homology model structure of BsL13 was generated using the EcL13 crystal structure as a template. Protein-protein docking of BsObg protein with ribosomal protein BsL13 was performed by DOT, a macro-molecular docking software, in order to predict a reasonable binding mode. The solvated energy minimization calculation of the docked conformation was carried out to refine the structure. Results and Discussion: The possible binding conformation of BsL13 along with activated Obg fold in BsObg was predicted by computational docking study. The final structure is obtained from the solvated energy minimization. From the analysis, three important H-bond interactions between the Obg fold and the L13 were detected: Obg:Tyr27-L13:Glu32, Obg:Asn76-L13:Glu139, and Obg:Ala136-L13:Glu142. The interaction between the BsObg and BsL13 structures were also analyzed by electrostatic potential calculations to examine the interface surfaces. From the results, the key residues for hydrogen bonding and hydrophobic interaction between the two proteins were predicted. Conclusion and Prospects: In this study, we have focused on the binding mode of the BsObg protein with the ribosomal BsL13 protein. The interaction between the activated Obg and target protein was investigated with protein-protein docking calculations. The binding pattern can be further used as a base for structure-based drug design to find a novel antibacterial drug.

Location Service Modeling of Distributed GIS for Replication Geospatial Information Object Management (중복 지리정보 객체 관리를 위한 분산 지리정보 시스템의 위치 서비스 모델링)

  • Jeong, Chang-Won;Lee, Won-Jung;Lee, Jae-Wan;Joo, Su-Chong
    • The KIPS Transactions:PartD
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    • v.13D no.7 s.110
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    • pp.985-996
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    • 2006
  • As the internet technologies develop, the geographic information system environment is changing to the web-based service. Since geospatial information of the existing Web-GIS services were developed independently, there is no interoperability to support diverse map formats. In spite of the same geospatial information object it can be used for various proposes that is duplicated in GIS separately. It needs intelligent strategies for optimal replica selection, which is identification of replication geospatial information objects. And for management of replication objects, OMG, GLOBE and GRID computing suggested related frameworks. But these researches are not thorough going enough in case of geospatial information object. This paper presents a model of location service, which is supported for optimal selection among replication and management of replication objects. It is consist of tree main services. The first is binding service which can save names and properties of object defined by users according to service offers and enable clients to search them on the service of offers. The second is location service which can manage location information with contact records. And obtains performance information by the Load Sharing Facility on system independently with contact address. The third is intelligent selection service which can obtain basic/performance information from the binding service/location service and provide both faster access and better performance characteristics by rules as intelligent model based on rough sets. For the validity of location service model, this research presents the processes of location service execution with Graphic User Interface.

Development of A Material Flow Model for Predicting Nano-TiO2 Particles Removal Efficiency in a WWTP (하수처리장 내 나노 TiO2 입자 제거효율 예측을 위한 물질흐름모델 개발)

  • Ban, Min Jeong;Lee, Dong Hoon;Shin, Sangwook;Lee, Byung-Tae;Hwang, Yu Sik;Kim, Keugtae;Kang, Joo-Hyon
    • Journal of Wetlands Research
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    • v.24 no.4
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    • pp.345-353
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    • 2022
  • A wastewater treatment plant (WWTP) is a major gateway for the engineered nano-particles (ENPs) entering the water bodies. However existing studies have reported that many WWTPs exceed the No Observed Effective Concentration (NOEC) for ENPs in the effluent and thus they need to be designed or operated to more effectively control ENPs. Understanding and predicting ENPs behaviors in the unit and \the whole process of a WWTP should be the key first step to develop strategies for controlling ENPs using a WWTP. This study aims to provide a modeling tool for predicting behaviors and removal efficiencies of ENPs in a WWTP associated with process characteristics and major operating conditions. In the developed model, four unit processes for water treatment (primary clarifier, bioreactor, secondary clarifier, and tertiary treatment unit) were considered. Additionally the model simulates the sludge treatment system as a single process that integrates multiple unit processes including thickeners, digesters, and dewatering units. The simulated ENP was nano-sized TiO2, (nano-TiO2) assuming that its behavior in a WWTP is dominated by the attachment with suspendid solids (SS), while dissolution and transformation are insignificant. The attachment mechanism of nano-TiO2 to SS was incorporated into the model equations using the apparent solid-liquid partition coefficient (Kd) under the equilibrium assumption between solid and liquid phase, and a steady state condition of nano-TiO2 was assumed. Furthermore, an MS Excel-based user interface was developed to provide user-friendly environment for the nano-TiO2 removal efficiency calculations. Using the developed model, a preliminary simulation was conducted to examine how the solid retention time (SRT), a major operating variable affects the removal efficiency of nano-TiO2 particles in a WWTP.

A Numerical Analysis to Estimate Disposal Spacing and Rock Mass Condition for High Efficiency Repository Based on Temperature Criteria of Bentonite Buffer (벤토나이트 완충재 설계 기준 온도에 따른 고효율 처분시스템 처분 간격 및 암반 조건 산정을 위한 수치해석적 연구)

  • Kim, Kwang-Il;Lee, Changsoo;Kim, Jin-Seop;Cho, Dongkeun
    • Tunnel and Underground Space
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    • v.31 no.4
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    • pp.289-308
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    • 2021
  • This study conducts coupled thermo-hydro-mechanical numerical modeling to investigate the maximum temperature and conditions for securing mechanical stability of the high-level radioactive waste repository when temperature criteria of bentonite buffer are 100℃ and 125℃, respectively. In case of temperature criterion of buffer as 100℃, the maximum temperatures at the interface between canister and buffer are calculated to be 99.4℃ and 99.8℃, respectively for a case with disposal tunnel spacing of 40 m and deposition hole spacing of 5.5 m and for the other case with disposal tunnel spacing of 30 m and deposition hole spacing of 6.5 m. In case of temperature criterion of buffer as 125℃, spacings of disposal tunnel and deposition hole could be decreased to 30 m and 4.5 m, respectively, which reduces the disposal area up to 55% compared to the disposal area of KRS+. According to analysis of mechanical stability for various disposal spacings, RMR of rock mass for KRS+ should be larger than 72.4 which belongs to good rock in RMR classification to prevent failure of rock mass. As disposal spacing is decreased, required RMR of rock mass is increased. In order to prevent failure of rock mass for a case with disposal tunnel spacing of 30 m and deposition hole spacing of 4.5 m, RMR larger than 87.3 is needed. However, mechanical stability of the repository is secured for all cases with RMR over 75 considering the enhancement of rock strength due to confining stress induced by swelling of the bentonite buffer and backfill.

Development of Yóukè Mining System with Yóukè's Travel Demand and Insight Based on Web Search Traffic Information (웹검색 트래픽 정보를 활용한 유커 인바운드 여행 수요 예측 모형 및 유커마이닝 시스템 개발)

  • Choi, Youji;Park, Do-Hyung
    • Journal of Intelligence and Information Systems
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    • v.23 no.3
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    • pp.155-175
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    • 2017
  • As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.