• Journal of Sensor Science and Technology
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• v.26 no.3
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• pp.199-203
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• 2017

In this paper, we developed an underwater localization system for underwater robot docking using the electromagnetic wave attenuation model. Electromagnetic waves are generally known to be impossible to use in water environment. However, according to the conclusions of the previous studies on the attenuation characteristics in underwater, the attenuation pattern is uniform and its model was accurately proposed and verified in 3-dimensional space via the omnidirectional antenna. In this paper, a docking structure and localization sensor system are developed for a widely used cone type docking mechanism. First, we fabricated electromagnetic wave range sensor transmit modules. And a mobile sensor node is equipped with unmanned underwater vehicle(UUV)s. The mobile node senses the four different signal strength (RSS: Received Signal Strength) from fixed nodes, and the obtained RSS data are transformed to each distance information using the 3-Dimensional EM wave attenuation model. Then, the relative localization between the docking area and underwater robot can be achieved according to optimization algorithm. Finally, experimental results show the feasibility of the proposed localization system for the docking induction by comparing the errors in the actual position of the mobile node and the theoretical position through the model.

• Bulletin of the Korean Chemical Society
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• v.33 no.5
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• pp.1597-1602
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• 2012

In this study, we determined the 3D-structure of Arabidopsis thaliana KAPAS by homology modeling. We then investigated the binding mode of compounds obtained from in-house library using computational docking methods. From the flexible docking study, we achieved high dock scores for the active compounds denoted in this study as compound $\mathbf{3}$ and compound $\mathbf{4}$. Thus, we highlight the flexibility of specific residues, Lys 312 and Phe 172, when used in active sites.

• Journal of the Korea Safety Management & Science
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• v.15 no.2
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• pp.167-184
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• 2013

A cross docking operation involves multiple inbound trucks that deliver items from suppliers to a distribution center and multiple outbound trucks that ship items from the distribution center to customers. Based on customer demands, an inbound truck may have its items transferred to multiple outbound trucks. Similarly, an outbound truck can receive its consignments from multiple inbound trucks. The objective of this study is to find the best truck spotting sequence for both inbound and outbound trucks in order to minimize total operation time of the cross docking system under the condition that multiple visits to the dock by a truck to unload or load its consignments is allowed. The allocations of the items from inbound trucks to outbound trucks are determined simultaneously with the spotting sequences of both the inbound and outbound trucks.

• Proceeding of EDISON Challenge
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• 2016.03a
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• pp.126-130
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• 2016

Epidermal growth factor receptor(EGFR)는 HER family에 속하는 tyrosine kinase receptor로서 다양한 하류경로로 신호를 전달하여 세포 증식, 혈관 형성, 세포 사멸을 억제하는 역할을 한다. EGFR이 폐암의 형성에 중요한 역할을 하고 많은 상피세포 종양에서 비정상적으로 활성화됨에 따라 암 치료에 중요한 역할을 하고 있어 EGFR tyrosine kinase inhibitor(TKI)에 관한 많은 연구가 이루어졌다. 위와 같은 약 개발에 있어서 현재 가상 시뮬레이션을 통한 약 후보물질 개발이 진행되고 있다. 특히, Molecular docking 시뮬레이션은 기존의 실험적인 기술(X-ray crystallography, NMR)로는 연구하기가 어려웠던 protein과 ligand간의 상호작용을 예측하여 이에 대한 정보를 제공할 수 있다. 하지만, 우선적으로 Molecular docking 시뮬레이션은 정확한 validation을 기반으로 진행되어야 신뢰할 수 있는 정보를 얻을 수 있다. 따라서 이번 연구에서는 EDISON에서 제공하는 Dock 프로그램과 일반적으로 잘 알려진 Glide, Autodock 프로그램으로 protein data bank(PDB)에서 제공하는 EGFR wild type cocrystal을 redocking하는 방식을 통하여 최상위 rank pose의 RMSD 값을 통한 validation 성능을 비교함으로써 어떤 프로그램이 EGFR과 ligand 간의 결합예측을 하는데 있어서 보다 더 정확한 결과를 낼 수 있는지 알아보고자 하였고 시뮬레이션 결과 Autodock에서 가장 우수한 결과 값을 보여주었다.

• Genomics & Informatics
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• v.12 no.4
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• pp.283-288
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• 2014

Among all serious diseases globally, diabetes (type 1 and type 2) still poses a major challenge to the world population. Several target proteins have been identified, and the etiology causing diabetes has been reasonably well studied. But, there is still a gap in deciding on the choice of a drug, especially when the target is mutated. Mutations in the KCNJ11 gene, encoding the kir6.2 channel, are reported to be associated with congenital hyperinsulinism, having a major impact in causing type 1 diabetes, and due to the lack of its 3D structure, an attempt has been made to predict the structure of kir6.2, applying fold recognition methods. The current work is intended to investigate the affinity of four phytochemicals namely, curcumin (Curcuma longa), genistein (Genista tinctoria), piperine (Piper nigrum), and pterostilbene (Vitis vinifera) in a normal as well as in a mutant kir6.2 model by adopting a molecular docking methodology. The phytochemicals were docked in both wild and mutated kir6.2 models in two rounds: blind docking followed by ATP-binding pocket-specific docking. From the binding pockets, the common interacting amino acid residues participating strongly within the binding pocket were identified and compared. From the study, we conclude that these phytochemicals have strong affinity in both the normal and mutant kir6.2 model. This work would be helpful for further study of the phytochemicals above for the treatment of type 1 diabetes by targeting the kir6.2 channel.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.3
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• pp.248-257
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• 2011

Cross docking is a logistics management concept in which items delivered to a terminal by inbound trucks are immediately sorted out, routed and loaded into outbound trucks for delivery to customers. Two main advantages by introducing a cross docking terminal are to consolidate multiple smaller shipment into full truck load and remove storage and order picking processes to save up logistics costs related to warehousing and transportation costs. This research considers the scheduling problem of trucks in the cross docking terminals with multi-door in an inbound and outbound dock, respectively. The trucks sequentially deal with the storage process at the one of inbound doors and the shipping process at the one of the outbound doors. A mathematical model for an optimal solution is derived, and genetic algorithms with two different chromosome representations are proposed. To verify performance of the GA algorithms, we compare the solutions of GAs with the optimal solutions and the best solution using randomly generated several examples.

• International Journal of Aeronautical and Space Sciences
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• v.12 no.1
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• pp.43-56
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• 2011

An integrated system composed of guidance, navigation and control (GNC) system for autonomous proximity operations and the docking of two spacecraft was developed. The position maneuvers were determined through the integration of the state-dependent Riccati equation formulated from nonlinear relative motion dynamics and relative navigation using rendezvous laser vision (Lidar) and a vision sensor system. In the vision sensor system, a switch between sensors was made along the approach phase in order to provide continuously effective navigation. As an extension of the rendezvous laser vision system, an automated terminal guidance scheme based on the Clohessy-Wiltshire state transition matrix was used to formulate a "V-bar hopping approach" reference trajectory. A proximity operations strategy was then adapted from the approach strategy used with the automated transfer vehicle. The attitude maneuvers, determined from a linear quadratic Gaussian-type control including quaternion based attitude estimation using star trackers or a vision sensor system, provided precise attitude control and robustness under uncertainties in the moments of inertia and external disturbances. These functions were then integrated into an autonomous GNC system that can perform proximity operations and meet all conditions for successful docking. A six-degree of freedom simulation was used to demonstrate the effectiveness of the integrated system.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2004.11a
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• pp.210-218
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• 2004

Poly(ADP-ribose)polymerase-1 (PARP-1) is a nuclear enzyme involved in various physical functions related to genomic repair, and PARP inhibitors have therapeutic application in a variety of neurological diseases. Docking and the QSAR (quantitative structure-activity relationships) studies for 52 PARP-1 inhibitors were conducted using FlexX algorithm, comparative molecular field analysis (CoMFA), and hologram quantitative structure-activity relationship analysis (HQSAR). The resultant FlexX model showed a reasonable correlation (r$^{2}$ = 0.701) between predicted activity and observed activity. Partial least squares analysis produced statistically significant models with q$^{2}$ values of 0.795 (SDEP=0.690, r$^{2}$=0.940, s=0.367) and 0.796 (SDEP=0.678, r$^{2}$ = 0.919, s=0.427) for CoMFA and HQSAR, respectively. The models for the entire inhibitor set were validated by prediction test and scrambling in both QSAR methods. In this work, combination of docking, CoMFA with 3D descriptors and HQSAR based on molecular fragments provided an improved understanding in the interaction between the inhibitors and the PARP. This can be utilized for virtual screening to design novel PARP-1 inhibitors.

• Journal of Integrative Natural Science
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• v.3 no.1
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• pp.49-53
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• 2010

Molecular docking is a critical event which mostly forms Van der waals complex in molecular recognition. Since the majority of developed drugs are small molecules, docking them into proteins has been a prime concern in drug discovery community. Since the binding pose space is too vast to cover completely, many search algorithms such as genetic algorithm, Monte Carlo, simulated annealing, distance geometry have been developed. Proper evaluation of the quality of binding is an essential problem. Scoring functions derived from force fields handle the ligand binding prediction with the use of potential energies and sometimes in combination with solvation and entropy contributions. Knowledge-based scoring functions are based on atom pair potentials derived from structural databases. Forces and potentials are collected from known protein-ligand complexes to get a score for their binding affinities (e.g. PME). Empirical scoring functions are derived from training sets of protein-ligand complexes with determined affinity data. Because non of any single scoring function performs generally better than others, some other approaches have been tried. Although numerous scoring functions have been developed to locate the correct binding poses, it still remains a major hurdle to derive an accurate scoring function for general targets. Recently, consensus scoring functions and target specific scoring functions have been studied to overcome the current limitations.

• Bulletin of the Korean Chemical Society
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• v.28 no.10
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• pp.1811-1814
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• 2007