• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2005년도 BIOINFO 2005
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• pp.249-255
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• 2005

Angiotensin-converting enzyme (ACE) is primarily responsible for human hypertension. Current ACE drugs show serious cough and angiodema health problems due to the un-specific activity of the drug to ACE protein. The availability of ACE crystal structure (1UZF) provided the plausible biological orientation of inhibitors to ACE active site (C-domain). Three-dimensional quantitative structure-activity relationship (3D-QSAR) models have been constructed using the comparative molecula. field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) for a series of 28 ACE inhibitors. Alignment for CoMFA obtained by docking ligands to 1UZF protein using FlexX program showed better statistical model as compared to superposition of corresponding atoms. The statistical parameters indicate reasonable models for both CoMFA (q$^2$ = 0.530, r$^2$ = 0.998) and CoMSIA (q$^2$= 0.518, r$^2$ = 0.990). The 3D-QSAR analyses provide valuable information for the design of ACE inhibitors with potent activity towards C-domain of ACE. The group substitutions involving the phenyl ring and carbon chain at the propionyl and sulfonyl moieties of captopril are essential for specific activity to ACE.

• Bulletin of the Korean Chemical Society
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• 제34권3호
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• pp.837-850
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• 2013

Bovine viral diarrhea virus (BVDV), a major pathogen of cattle, is a well-characterized pestivirus which has been used as a good model virus for HCV. The RNA-dependent RNA polymerase (RdRp) plays a key role in the RNA replication process, thus it has been targeted for antivirus drugs. We employed two-dimensional quantitative structure-activity relationship (2D-QSAR) and molecular field analysis (MFA) to identify the molecular substructure requirements, and the particular characteristics resulted in increased inhibitory activity for the known series of compounds to act as effective BVDV inhibitors. The 2D-QSAR study provided the rationale concept for changes in the structure to have more potent analogs focused on the class of arylazoenamines, benzimidazoles, and acridine derivatives with an optimal subset of descriptors, which have significantly contributed to overall anti-BVDV activity. MFA represented the molecular patterns responsible for the actions of antiviral compound at their receptors. We conclude that the polarity and the polarizability of a molecule play a main role in the inhibitory activity of BVDV inhibitors in the QSAR modeling.

• 통합자연과학논문집
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• 제10권3호
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• pp.141-147
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• 2017

Vascular endothelial growth factor (VEGF) is an important signaling protein involved in angiogenesis, which is the formation of new blood vessels from pre-existing vessels. Consequently, blocking of the vascular endothelial growth factor receptor (VEGFR-2) by small molecule inhibitors leads to the inhibition of cancer induced angiogenesis. In this study, we performed a two dimensional quantitative structure activity relationship (2D-QSAR) study of 38 N-Phenyl-N'-{4-(4-quinolyloxy) phenyl} urea derivatives as VEGFR-2 inhibitors based on hologram quantitative structure-activity (HQSAR). The model developed showed reasonable $q^2=0.521$ and $r^2=0.932$ values indicating good predictive ability and reliability. The atomic contribution map analysis of most active compound (compound 7) indicates that hydrogen and oxygen atoms in the side chain of ring A and oxygen atom in side chain of ring C contributes positively to the activity of the compounds. The HQSAR model developed and the atomic contribution map can serve as a guideline in designing new compounds for VEGFR-2 inhibition.

• Bulletin of the Korean Chemical Society
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• 제35권11호
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• pp.3181-3187
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• 2014

A series of 3,4-dihydroquinazoline derivatives with anti-cancer activities against human colon cancer HT-29 cell were subjected to three-dimensional quantitative structure-activity relationship (3D-QSAR) studies using the comparative molecular similarity indices analysis (CoMSIA) approaches. The most potent compound, BK10001 was used to align the molecules. As a result, the best prediction was obtained with CoMSIA combined electrostatic, hydrophobic, and hydrogen-bond acceptor fields ($q^2=0.648$, $r^2=0.882$). This model was validated by an external test set of six compounds giving satisfactory predictive $r^2$ values of 0.879. This model would guide the design of potent 3,4-dihydroquinazoline derivatives as anti-cancer agent for the treatment of human colon cancer.

• 농약과학회지
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• 제9권2호
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• pp.140-145
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• 2005

정량적 구조 활성관계 모델링은 물리적인 성질과 생물학적 활성이 관계 있다는 것을 전제로 한다. 그러나, 퍼센트 활성과 같은 데이터들은 모델링에 많이 활용되지 않았다. 이것의 중요한 이유중의 하나는 이러한 값들이 정량적이 아니고 정성적인 데에 있다. 본 연구에서는 분자모델링에 퍼센트활성 데이터를 활용하기 위하여 데이터 값들을 2개의 계층으로 분류하고 CoMFA(비교분자장)를 판별함수로 활용하였다. 즉, 베타-케토아세트아닐라이드 유도체들의 토마토 역병균에 대한 항균력 시험의 퍼센트 활성 데이터를, 한 계층은 활성이 있는 것, 다른 계층은 활성이 없는 것으로 나누었다. 특히, CoMFA를 활용함으로써 화학적인 이해에 중요한 3차원적인 정보를 얻을 수 있었다. 이 모델은 주어진 데이타를 98%의 정확도로 설명하였으며, LOO 검증을 해본 결과 예측력은 약 69% 정도였다 이 결과는 활성 데이터를 근사적으로 2개의 계급으로 나누고 CoMFA를 활용하는 방식이 구조활성관계를 이해하고 화합물 유도체를 합성하는데 활용될 수 있음을 보여준다.

• Bulletin of the Korean Chemical Society
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• 제30권11호
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• pp.2739-2748
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• 2009

Hologram and three dimensional quantitative structure activity relationship (3D QSAR) studies for a series of anilinobipyridine JNK3 inhibitors were performed using various alignment-based comparative molecular field analysis (COMFA) and comparative molecular similarity indices analysis (CoMSIA). The in vitro JNK3 inhibitory activity exhibited a strong correlation with steric and electrostatic factors of the molecules. Using four different types of alignments, the best model was selected based on the statistical significance of CoMFA ($q_2\;=\;0.728,\;r_2\;=\;0.865$), CoMSIA ($q_2\;=\;0.706,\;r_2\;=\;0.960$) and Hologram QSAR (HQSAR: $q_2\;=\;0.838,\;r_2\;=\;0.935$). The graphical analysis of produced CoMFA and CoMSIA contour maps in the active site indicated that steric and electrostatic interactions with key residues are crucial for potency and selectivity of JNK3 inhibitors. The HQSAR analysis showed a similar qualitative conclusion. We believe these findings could be utilized for further development of more potent and selective JNK3 inhibitors.

• 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.

• 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.

• Bulletin of the Korean Chemical Society
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• 제32권5호
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• pp.1604-1612
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• 2011

We developed three-dimensional quantitative structure activity relationship (3D-QASR) models for 17 adamantyl derivatives as P-glycoprotein (P-gp) inhibitors. Eighteen different partial charge calculation methods were tested to check the feasibility of the 3D-QSAR models. Best predictive comparative molecular field analysis (CoMFA) model was obtained with the Austin Model 1-Bond Charge Correction (AM1-BCC) atomic charge. The 3D-QSAR models were derived with CoMFA and comparative molecular similarity indices analysis (CoMSIA). The final CoMFA model ($q^2$ = 0.764, $r^2$ = 0.988) was calculated with an AM1-BCC charge and electrostatic parameter, whereas the CoMSIA model ($q^2$ = 0.655, $r^2$ = 0.964) was derived with an AM1-BCC charge and combined steric, electrostatic, hydrophobic and HB-acceptor parameters. Leave-five-out (LFO) cross-validation was also performed, which yielded good correlation coefficient for both CoMFA (0.801) and CoMSIA (0.656) models. Robustness of the developed models was checked further with 1000 run bootstrapping analyses, which gave an acceptable correlation coefficient for CoMFA (BS-$r^2$ = 0.997, BS-SD = 0.003) and CoMSIA (BS-$r^2$ = 0.996, BS-SD = 0.018).

• Bulletin of the Korean Chemical Society
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• 제34권8호
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• pp.2387-2393
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• 2013

Benzotriazole is an important synthetic auxiliary for potential clinical applications. A series of benzotriazoles as potential antiproliferative agents by inhibiting histone deacetylase (HDAC) were recently reported. Three-dimensional quantitative structure-activity relationship (3D-QSAR), including comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA), were performed to elucidate the 3D structural features required for the antiproliferative activity. The results of both ligand-based CoMFA model ($q^2=0.647$, $r^2=0.968$, ${r^2}_{pred}=0.687$) and CoMSIA model ($q^2=0.685$, $r^2=0.928$, ${r^2}_{pred}=0.555$) demonstrated the highly statistical significance and good predictive ability. The results generated from CoMFA and CoMSIA provided important information about the structural characteristics influence inhibitory potency. In addition, docking analysis was applied to clarify the binding modes between the ligands and the receptor HDAC. The information obtained from this study could provide some instructions for the further development of potent antiproliferative agents and HDAC inhibitors.