• Bulletin of the Korean Chemical Society
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• 제29권3호
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• pp.647-655
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• 2008

Microsomal prostaglandin E2 synthase (mPGES-1) is a potent target for pain and inflammation. Various QSAR (quantitative structure activity relationship) analyses used to understand the factors affecting inhibitory potency for a series of MK886 analogues. We derived four QSAR models utilizing various quantum mechanical (QM) descriptors. These QM models indicate that steric, electrostatic and hydrophobic interaction can be important factors. Common pharmacophore hypotheses (CPHs) also have studied. The QSAR model derived by best-fitted CPHs considering hydrophobic, negative group and ring effect gave a reasonable result (q2 = 0.77, r2 = 0.97 and Rtestset = 0.90). The pharmacophore-derived molecular alignment subsequently used for 3D-QSAR. The CoMFA (Comparative Molecular Field Analysis) and CoMSIA (Comparative Molecular Similarity Indices Analysis) techniques employed on same series of mPGES-1 inhibitors which gives a statistically reasonable result (CoMFA; q2 = 0.90, r2 = 0.99. CoMSIA; q2 = 0.93, r2 = 1.00). All modeling results (QM-based QSAR, pharmacophore modeling and 3D-QSAR) imply steric, electrostatic and hydrophobic contribution to the inhibitory activity. CoMFA and CoMSIA models suggest the introduction of bulky group around ring B may enhance the inhibitory activity.

• Korean Chemical Engineering Research
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• 제61권4호
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• pp.523-541
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• 2023

3D 프린터의 활용이 높아짐에 따라 발생하는 화학물질에 대한 노출 빈도가 증가하고 있다. 그러나 3D 프린팅 발생 화학물질의 독성 및 유해성에 대한 연구는 미비하며, 분자 구조 데이터의 결측치로 인해 in silico 기법을 사용한 독성예측 연구는 저조한 실정이다. 본 연구에서는 화학물질의 분자구조 정보를 나타내는 주요 분자표현자의 결측치를 보간하여 3D 프린팅의 독성 및 유해성을 예측한 Data-centric QSAR 모델을 개발하였다. 먼저 MissForest 알고리즘을 사용해 3D 프린팅으로 발생되는 유해물질의 분자표현자 결측치를 보완하였으며, 서로 다른 4가지 기계학습 모델(결정트리, 랜덤포레스트, XGBoost, SVM)을 기반으로 Data-centric QSAR 모델을 개발하여 생물 농축 계수(Log BCF)와 옥탄올-공기분배계수(Log Koa), 분배계수(Log P)를 예측하였다. 또한, 설명 가능한 인공지능(XAI) 방법론 중 TreeSHAP (SHapley Additive exPlanations) 기법을 활용하여 Data-centric QSAR 모델의 신뢰성을 입증하였다. MissForest 알고리즘 기반 결측지 보간 기법은, 기존 분자구조 데이터에 비하여 약 2.5배 많은 분자구조 데이터를 확보할 수 있었다. 이를 바탕으로 개발된 Data-centric QSAR 모델의 성능은 Log BCF, Log Koa와 Log P를 각각 73%, 76%, 92% 의 예측 성능으로 예측할 수 있었다. 마지막으로 Tree-SHAP 분석결과 개발된 Data-centric QSAR 모델은 각 독성치와 물리적으로 상관성이 높은 분자표현자를 통하여 선택함을 설명할 수 있었고 독성 정보에 대한 높은 예측 성능을 확보할 수 있었다. 본 연구에서 개발한 방법론은 다른 프린팅 소재나 화학공정, 그리고 반도체/디스플레이 공정에서 발생 가능한 오염물질의 독성 및 인체 위해성 평가에 활용될 수 있을 것으로 사료된다.

• 대한약학회:학술대회논문집
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• 대한약학회 2003년도 Proceedings of the Convention of the Pharmaceutical Society of Korea Vol.1
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• pp.249.2-250
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• 2003

3D-QSAR analyses by CoMFA and CoMSIA were conducted on a series of thiazole and triazole analogues with respect to their antifungal activities against Microsporum gypseum. A total of twenty analogues were used for the derivation of the 3D-QSAR models (training set). Thesuperposition of the compounds was performed by applying the FlexS with shape-based screening method. (omitted)

• Bulletin of the Korean Chemical Society
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• 제25권10호
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• pp.1513-1520
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• 2004

We investigate a series of synthesized ${\beta}$-methoxyacrylate analogues for their 3D QSAR & HQSAR against Magnaporthe grisea (Rice Blast Disease). We perform the three-dimensional Quantitative Structure-Activity Relationship (3D-QSAR) studies, using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) procedure. In addition, we carry out a two-dimensional Quantitative Structure-Activity Relationship (2D-QSAR) study, using the Hologram QSAR (HQSAR). We perform these studies, using 53 compounds as a training set and 10 compounds as a test set. The predictive QSAR models have conventional $r^2$ values of 0.955 at CoMFA, 0.917 at CoMSIA, and 0.910 at HQSAR respectively; similarly, we obtain cross-validated coefficient $q^2$ values of 0.822 at CoMFA, 0.763 at CoMSIA, and 0.816 at HQSAR, respectively. From these studies, the CoMFA model performs better than the CoMSIA model.

• 통합자연과학논문집
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• 제4권3호
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• pp.210-215
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• 2011

Holographic quantitative structure-activity relationships (HQSAR) is a useful tool to correlates structures with their biological activities. HQSAR is a two dimensional (2D) QSAR methodology, which generates QSAR equations through 2D fingerprint and correlates it with biological activity. Here, we report a 2D-QSAR model for a series of fifty-one 3,4-dihydroxychalcones derivatives utilizing HQSAR methodology. We developed HQSAR model with 6 optimum numbers of components (ONC), which resulted in cross-validated correlation coefficient ($q^2$) of 0.855 with 0.283 standard error of estimate (SEE). The non-cross-validated correlation coefficient (r2) with 0.966 indicates the model is predictive enough for analysis. Developed HQSAR model was binned in to a hologram length of 257. Atomic contribution map revealed the importance of dihydroxy substitution on phenyl ring.

• 농약과학회지
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• 제14권3호
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• pp.191-198
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• 2010

새로운 고활성의 살충성 화합물을 예측하고 설계하기 위하여 N'-phenyl-N-methylformamidine 유도체들의 두점박이 응애(Tetranychus urticae)에 대한 살충활성과 물리-화합적인 설명인자들 사이의 2차원적인 정량적 구조-활성관계(2D-QSAR)와 분자 홀로그래피적인 정량적 구조-활성관계(HQSAR)를 구체적으로 검토하였다. 2D-QSAR 모델(1 및 3)로부터 입체적인 요소로서 $R_3$-치환기의 폭($B_2$)과 $R_4$-치환기의 적정한 전체 쌍극자능율값(TDM=2.025 D)이 살충활성에 주로 영향을 미쳤으며 살충활성은 $R_3$- 및 $R_4$-치환기들에 의존적이었다. 특히, 2D-QSAR 모델(3)과 HQSAR 모델 F2에 의하여 설계된 새로운 유력한 활성화합물(P1; $EC_{50}$=0.516 ppm)의 살충활성은 Amitraz에 비하여 약 34.3배 높을 것으로 예측되었다.

• Applied Biological Chemistry
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• 제50권3호
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• pp.147-153
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• 2007

새로운 유방암의 억제 물질을 탐색하고 설계하기 위하여 flavopiridol 유도체의 치환기($R_1{\sim}R_2$) 변화에 따른 유방암 유발세포 MCF-7의 저해활성에 관한 2D-QSAR 및 분자 홀로그래피적인 QSAR을 분석하였다. 2D-QSAR 모델(1)로부터 분자는 분산력으로 그리고 치환기는 입체장애를 유발하는 요인으로 작용하였으며 질량(MS)보다 굴절율(MR)상수가 저해활성에 크게 기여하였다. 그리고 2D-QSAR 모델(2)로부터는 MR상수의 적정값. $(MR)_{opt.}$= 126$Cm^3/mol$을 가지는 치환기의 저해활성이 가장 높을 것으로 예상되었다. 또한, 최적의 HQSAR 모델은 분자 조각의 크기($7{\sim}10$) 조건에서 예측성($q^2$= 0.583)과 상관성($r^2$= 0.982)이 매우 양호하였으며 기여도로부터 flavopiridol 분자내 A고리의 $C_8$원자에 결합된 수소원자나 hydroxyl-기보다 $C_9$원자 부분의 imino 골격이 저해활성에 기여하였다. 결과적으로 치환기들에 의한 분산력이 유방암 유발 세포 MCF-7의 저해활성에 크게 관여하는 주요인이었다.

• Reproductive and Developmental Biology
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• 제33권3호
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• pp.119-123
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• 2009

The two dimensional quantitative structure-activity relationships (2D-QSARs) models concerning the binding affinity constants ($p[Od.]_{50}$) between 2-cyclohexyltetrahydropyrane and 2-cyclohexyltetrahydrofurane analogues as substrates, and bovine odorant binding protein (bOBP) as receptor were derived by multiple regression analyses method and discussed. The statistical quality of the optimized 2D-QSAR model (5) was good (r=0.907). From the model, the binding affinity constants ($p[Od.]_{50}$) were dependent upon the optimal value ($(TL)_{opt.}$=2.737) of total lipole (TL) of substrate molecules. Based on these findings, the high active compounds predicted by optimized 2D-QSAR model (5) were 2-(dimethylcyclohexyl)tetrahydropyrane molecule and their isomer molecules. The binding affinity constants regarding bOBP of the tetrahydrofuryl-2-yl family compounds were dependent upon the hydrophobicity (logP) of whole substrate molecules. In any case of porcine odorant-binding proteins (pOBP), the constants were dependent upon the hydrophobicity (${\pi}x={\log}P_X-{\log}P_H$) of substituents (R) in substrate molecules. Also, from the optimal values of hydrophobic constant, the hydrophobicity for bOBP influenced ca. twice time bigger (bOBP>pOBP) than that for pOBP.

• 약학회지
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• 제55권2호
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• pp.91-97
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• 2011

To search a new anti-depressant agents against para-chloroamphetamine-induced excitation, three dimensional quantitative-structure relationships (3D-QSAR) models between structure of 3a,4-dihydro-3H-[1]-benzopyronao[4,3]isoxazoles (1-30) and thieir inhibitory activity against para-chloroamphetamine-induced excitation were performed and discussed quantitatively using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods. From these basis on the findings, the optimized CoMSIA-2F model ($q^2$=0.793 and $r^2$=0.952) showed the best statistical results. And also, it is found that the para-chloroamphetamine inhibitory activity from the optimized CoMSIA-2F model was dependent on steric field (35.2%) and electrostatic field (64.8%) of tricyclic isoxazoles. Particularly, it is predicted that the inhibitory activity against para-chloroamphetamine-induced excitation will be able to increase by the designed compounds from the CoMSIA-2F model.

• Bulletin of the Korean Chemical Society
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• 제30권9호
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• pp.2117-2120
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• 2009