• Genomics & Informatics
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• 제7권2호
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• pp.122-130
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• 2009

A systems biology approach for the identification of perturbed molecular functions is required to understand the complex progressive disease such as breast cancer. In this study, we analyze the microarray data with Gene Ontology terms of molecular functions to select perturbed molecular functional modules in breast cancer tissues based on the definition of Gene ontology Functional Code. The Gene Ontology is three structured vocabularies describing genes and its products in terms of their associated biological processes, cellular components and molecular functions. The Gene Ontology is hierarchically classified as a directed acyclic graph. However, it is difficult to visualize Gene Ontology as a directed tree since a Gene Ontology term may have more than one parent by providing multiple paths from the root. Therefore, we applied the definition of Gene Ontology codes by defining one or more GO code(s) to each GO term to visualize the hierarchical classification of GO terms as a network. The selected molecular functions could be considered as perturbed molecular functional modules that putatively contributes to the progression of disease. We evaluated the method by analyzing microarray dataset of breast cancer tissues; i.e., normal and invasive breast cancer tissues. Based on the integration approach, we selected several interesting perturbed molecular functions that are implicated in the progression of breast cancers. Moreover, these selected molecular functions include several known breast cancer-related genes. It is concluded from this study that the present strategy is capable of selecting perturbed molecular functions that putatively play roles in the progression of diseases and provides an improved interpretability of GO terms based on the definition of Gene Ontology codes.

• 통합자연과학논문집
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• 제3권1호
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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.

• 한국생물물리학회:학술대회논문집
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• 한국생물물리학회 2001년도 학술 발표회 진행표 및 논문초록
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• pp.19-19
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• 2001

The genome sequencing has revealed a large number of proteins of unknown or little characterized functions that have been well conserved during evolution. It remains a great challenge to decipher the molecular and physiological functions of these proteins. One example of the evolutionarily conserved protein family with little understood function is the surE family.(omitted)

• 대한기계학회논문집A
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• 제23권7호
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• pp.1223-1230
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• 1999

This paper addresses a novel optimization technique based on molecular dynamics simulation which has been utilized for physical model simulation at various disciplines. In this study, objective functions are considered to be potential functions, which depict molecular interactions. Comparisons of typical optimization method such as the steepest descent and the present method for several test functions are made. The present method shows applicability and stability in finding a global optimum.

• 대한화학회지
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• 제57권2호
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• pp.172-175
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• 2013

We compare the relative usefulness of common basis functions and numerical integration methods in representing complex resonance state encountered in the molecular scattering problem of aluminum dimer electronic predissociation. Specifically, the basis set size and computing CPU times are monitored in order to find the minimum requirement for ensuring the modest accuracy of calculated resonance energies (0.1 $cm^{-1}$) for more than 100 resonance states. The combination of the so-called one-dimensional box eigenfunctions and energy-dependent boundary functions are found to be most efficient if integration is done using the basis set quadrature rules.

• 반도체디스플레이기술학회지
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• 제10권4호
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• pp.47-51
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• 2011

We investigated the substrate surface polishing by the spherical rigid abrasive under the compression using classical molecular dynamics modeling. We performed three-dimensional molecular dynamic simulations using the Morse potential functions for the various slide-to-roll ratios, from 0 to 1, and then, the compressive forces acting on the spherical rigid abrasive were calculated as functions of the time and the slide-to-roll ratio. The friction coefficients obtained from the classical molecular dynamics simulations were compared to those obtained from the experiments; and found that the molecular dynamic simulation results with the slide-to-roll ratio of 0 value were in good agreement with the experimental results.

• 한국결정학회:학술대회논문집
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• 한국결정학회 2007년도 추계학술연구발표회 및 정기총회
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• pp.11-11
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• 2007

• 한국자기공명학회논문지
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• 제2권2호
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• pp.152-157
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• 1998

The diversity of RNA functions ranges from storage and propagation of genetic information to enzymatic activity during RNA processing and protein synthesis. This diversity of functions requires an equally diverse arrays of structures, and, very often, the formation of functional RNA-protein complexes. Recognition of specific RNA signals by RNA-binding proteins is central to all aspects of post-transcriptional regulation of gene expression. We will describe how NMR is being used to understand at the atomic level how these important biological processes occur.

• Bulletin of the Korean Chemical Society
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• 제35권12호
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• pp.3527-3531
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• 2014

In this paper, we report thermodynamic and transport properties (diffusion coefficient, viscosity, and thermal conductivity) of diatomic gases ($H_2$, $N_2$, $O_2$, and $Cl_2$) at 273.15 K and 1.00 atm by performing molecular dynamics simulations using Lennard-Jones intermolecular potential and modified Green-Kubo formulas. The results of self-diffusion coefficients of diatomic gases obtained from velocity auto-correlation functions by Green-Kubo relation are in good agreement with those obtained from mean square displacements by Einstein relation. While the results for viscosities of diatomic gases obtained from stress auto-correlation functions underestimate the experimental results, those for thermal conductivities obtained from heat flux auto-correlation functions overestimate the experimental data except $H_2$.

• Bulletin of the Korean Chemical Society
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• 제34권10호
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• pp.2931-2936
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• 2013

This paper presents results for the calculation of transport properties of noble gases (He, Ne, Ar, Kr, and Xe) at 273.15 K and 1.00 atm using equilibrium molecular dynamics (EMD) simulations through a Lennard-Jones (LJ) intermolecular potential. We have utilized the revised Green-Kubo formulas for the stress (SAC) and the heat-flux auto-correlation (HFAC) functions to estimate the viscosities (${\eta}$) and thermal conductivities (${\lambda}$) of noble gases. The original Green-Kubo formula was employed for diffusion coefficients (D). The results for transport properties (D, ${\eta}$, and ${\lambda}$) of noble gases at 273.15 and 1.00 atm obtained from our EMD simulations are in a good agreement with the rigorous results of the kinetic theory and the experimental data. The radial distribution functions, mean square displacements, and velocity auto-correlation functions of noble gases are remarkably different from those of liquid argon at 94.4 K and 1.374 $g/cm^3$.