• 대한약학회:학술대회논문집
• /
• 대한약학회 2003년도 Proceedings of the Convention of the Pharmaceutical Society of Korea Vol.1
• /
• pp.250.1-250.1
• /
• 2003

In this work, we have conducted 3D-QSAR studies on a series of acanthonic acid derivatives that act as COX-2 inhibitors, using two different methods: comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). CoMFA and CoMSIA analysis of twenty five pimarane analogues produced good models with high predictive abilities. (omitted)

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

• Archives of Pharmacal Research
• /
• 제27권10호
• /
• pp.1001-1008
• /
• 2004

Three-dimensional quantitative structure-activity relationship (3D-QSAR) studies on 59 cinnamaldehyde analogues as Farnesyl Protein Transferase (FPTase) inhibitors were investigated using comparative molecular field analysis (CoMFA) with the PLS region-focusing method. Forty-nine training set inhibitors were used for CoMFA with two different grid spacings, $2{\AA}\;and\;1{\AA}$ Ten compounds, which were not used in model generation, were used to validate the CoMFA models. After the PLS analysis, the best predictive CoMFA model showed that the cross-validated value $(r^2_{cv})$ and the non-cross validated conventional value$(r^2_{ncv})$ are 0.557 and 0.950, respectively. From the CoMFA contour maps, the steric and electrostatic properties of cinnamaldehyde analogues can be identified and verified.

• 농약과학회지
• /
• 제14권1호
• /
• pp.72-77
• /
• 2010

3차원적 정량적인 구조-활성관계(3D-QSARs: CoMFA 및 CoMSIA)에 기초하여 phytoene desaturase (PDS)에 대한 O-(2-phenoxy)ethyl-N-aralkylcarbamate 유도체(1-15)의 제초성 평가를 위한 R-phenoxy 치환기들의 구조적인 요건들을 정량적으로 검토하였다. CoMFA 1 모델의 예측성 및 상관성($r^2_{cv.}=0.753$ 및 $r^2_{ncv.}=0.964$)이 나머지 모델들보다 높았다. 최적화된 CoMFA 1 모델로부터 PDS 저해활성은 O-(2-phenoxy)ethyl-N-aralkylcarbamate 유도체들의 입체장(44.0%), 정전기장(36.3%) 및 소수성장(19.6%)에 의존적이었다. CoMFA 등고도 분석결과, phenoxy 고리상 meta-와 para-위치에는 입체적으로 큰 치환기, meta-위치는 음하전, para-위치의 바깥 부분에는 양하전, ortho- 및 para- phenoxy 고리 중앙의 바깥 부분에는 친수성 치환기가 그리고 meta-위치에 소수성 R-치환기가 각각 도입될 경우에 PDS에 대한 저해활성이 증가할 것으로 예측되었다.

• 통합자연과학논문집
• /
• 제4권4호
• /
• pp.266-272
• /
• 2011

Focal adhesion kinase (FAK) is a potential target for the treatment of primary cancers as well as prevention of tumor metastasis. To understand the structural and chemical features of FAK inhibitors, we report comparative molecular field analysis (CoMFA) for the series of 7H-pyrrolo(2,3-d)pyrimidines. The CoMFA models showed good correlation between the actual and predicted values for training set molecules. Our results indicated the ligand-based alignment has produced better statistical results for CoMFA ($q^2$ = 0.505, $r^2$ = 0.950). Both models were validated using test set compounds, and gave good predictive values of 0.537. The statistical parameters from the generated 3D-QSAR models were indicated that the data are well fitted and have high predictive ability. The contour map from 3D-QSAR models explains nicely the structure-activity relationships of FAK inhibitors and our results would give proper guidelines to further enhance the activity of novel inhibitors.

• Bulletin of the Korean Chemical Society
• /
• 제27권11호
• /
• pp.1741-1746
• /
• 2006

3D-QSARs on the neuroblocking activities by 1-(6-chloro-3-pyridylmethyl)-2-nitroiminoimidazolidine analogues as agonist at the nicotinic acetylcholine receptor (nAChR) were studied quantitatively using CoMFA and CoMSIA methodologies. The statistical results of CoMFA (A5: $r^2\;_{cv.}\;=\;0.707\;&\;r^2\;_{ncv.}$= 0.986) and CoMSIA model (A3: $r^2\;_{cv.}$ = 0.715 & $r^2\;_{ncv.}$ = 0.961) showed the best predictability and fitness for neuroblocking activity based on the cross-validated value and non-cross validated value. The steric and H-bond acceptor nature of a compound were essential for high activity. The study on 3D-QSARs between substrate molecules and their neuroblocking activities appears to be an useful approach for designing better neuroblocking drug development.

• 농약과학회지
• /
• 제12권1호
• /
• pp.18-23
• /
• 2008

기질 분자로서 6-bromobenzo-[4,5]imidazo[$1,2{\alpha}$]pyridin-8,9-diones 유도체의 photosystem II의 저해활성에 관한 3차원적인 정량적 구조와 활성과의 관계(3D-QSARs)들을 비교 분자장분석(CoMFA)과 비교분자 유사성 지수분석(CoMSIA) 방법으로 각각 검토하였다. CoMFA 모델은 CoMSIA 모델보다 높은 예측성과 상관성을 갖는 모델이었다. 또한 최적화된 CoMFA 2 모델의 기여도는 입체장(90.4%)에 가장 의존적이었다. CoMFA 등고도 분석으로부터, 치환기(R)로서 모체로 연결되는 탄소원자(ipso carbon)에 곁가지를 가진 치환체가 도입될수록 저해활성이 증가할 것으로 보인다. 또한, imidazol 고리와 pyridine 고리 사이의 위치에 양하전을 가질수록 활성이 높을 것으로 예상되며 친수성을 띄는 선 형태의 치환기가 도입되는 경우에 활성이 개선될 것으로 판단되었다.

• Bulletin of the Korean Chemical Society
• /
• 제32권2호
• /
• pp.645-650
• /
• 2011

The 3D-QSAR study of 2-arylbenzoxazoles as novel cholesteryl ester transfer protein inhibitors was performed by comparative molecular field analysis (CoMFA), CoMFA region focusing (CoMFA-RF) for optimizing the region for the final PLS analysis, and comparative molecular similarity indices analysis (CoMSIA) methods to determine the factors required for the activity of these compounds. The best orientation was searched by all-orientation search strategy using AOS, to minimize the effect of the initial orientation of the structures. The predictive ability of CoMFARF and CoMSIA were determined using a test set of twelve compounds giving predictive correlation coefficients of 0.886, and 0.754 respectively indicating good predictive power. Further, the robustness and sensitivity to chance correlation of the models were verified by bootstrapping and progressive scrambling analyses respectively. Based upon the information derived from CoMFA(RF) and CoMSIA, identified some key features that may be used to design new inhibitors for cholesteryl ester transfer protein.

• Applied Biological Chemistry
• /
• 제50권3호
• /
• pp.192-197
• /
• 2007

고추역병균(Phytophthora capsici)에 대한 N-phenylbenzenesulfonamide 및 N-phenyl-2-thienylsulfonamide 유도체(1-37)들의 살균활성에 관한 3차원적인 정량적 구조와 활성과의 관계(3DQSARs)들을 비교 분자장 분석(CoMFA)과 비교분자 유사성 지수분석(CoMSIA) 방법으로 각각 검토하였다. CoMFA(2) 모델($r^2_{cv.}(q^2)$ = 0.692 및 $r^2_{ncv.}$= 0.965)이 CoMSIA(2) 모델($r^2_{cv.}(q^2)$ =0.796 및 $r^2_{ncv.}$= 0.958)보다 상관성과 예측성이 양호하였다. 최적의 CoMFA(2) 모델에 따른 살균활성은 분자의 입체장과 정전기장에 의존적이었다. 또한, CoMFA(2) 모델의 등고도 분석 결과로부터 살균활성의 63%가 입체적으로 큰 S-phenyl 고리의 meta-치환기($R_1$) 그리고 나머지 살균활성의 32.9%가 양하전을 띄는 N-phenyl 고리의 $R_4$-치환기와 S-phenyl 고리의 para-치환기($R_1$)에 기인하는것으로 예측되었으며 이 같은 사실에 기초하여 일련의 고활성 화합물, $R_1$ = 3-decyl 치환체 ($pred.pI_50$ = 5.88) 등이 예측되었다.

• 통합자연과학논문집
• /
• 제8권3호
• /
• pp.214-220
• /
• 2015

Cancer has emerged as one of the leading cause of deaths worldwide. A three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis was performed on a series of quinazoline-based anticancer agents. Purpose of the study is to understand the structural basis for their inhibitory activity. Comparative molecular field analysis (CoMFA) technique was employed to develop 3D-QSAR model. Ligand-based alignment scheme was used to generate a reliable CoMFA model. The model produced statistically significant results with a cross-validated correlation coefficient ($q^2$) of 0.589 and a non-cross-validated correlation coefficient ($r^2$) of 0.928. Model was further validated by bootstrapping and progressive scrambling analysis. This study could assist in the design of novel and more potent anticancer agents.