3D-QSAR Studies of 2-Arylbenzoxazoles as Novel Cholesteryl Ester Transfer Protein Inhibitors

Ghasemi, Jahan B.,Pirhadi, Somayeh,Ayati, Mahnaz Korean Chemical Society 2011 Bulletin of the Korean Chemical Society Vol.32 No.2

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.

A New Variable Selection Method Based on Mutual Information Maximization by Replacing Collinear Variables for Nonlinear Quantitative Structure-Property Relationship Models

Ghasemi, Jahan B.,Zolfonoun, Ehsan Korean Chemical Society 2012 Bulletin of the Korean Chemical Society Vol.33 No.5

Selection of the most informative molecular descriptors from the original data set is a key step for development of quantitative structure activity/property relationship models. Recently, mutual information (MI) has gained increasing attention in feature selection problems. This paper presents an effective mutual information-based feature selection approach, named mutual information maximization by replacing collinear variables (MIMRCV), for nonlinear quantitative structure-property relationship models. The proposed variable selection method was applied to three different QSPR datasets, soil degradation half-life of 47 organophosphorus pesticides, GC-MS retention times of 85 volatile organic compounds, and water-to-micellar cetyltrimethylammonium bromide partition coefficients of 62 organic compounds.The obtained results revealed that using MIMRCV as feature selection method improves the predictive quality of the developed models compared to conventional MI based variable selection algorithms.

Docking, CoMFA and CoMSIA Studies of a Series of N-Benzoylated Phenoxazines and Phenothiazines Derivatives as Antiproliferative Agents

Ghasemi, Jahan B.,Aghaee, Elham,Jabbari, Ali Korean Chemical Society 2013 Bulletin of the Korean Chemical Society Vol.34 No.3

Using generated conformations from docking analysis by Gold algorithm, some 3D-QSAR models; CoMFA and CoMSIA have been created on 39 N-benzoylated phenoxazines and phenothiazines, including their S-oxidized analogues. These molecules inhibit the polymerization of tubulin into microtubules and thus they have been studied for the development of antitumor drugs. Training set for the CoMFA and CoMSIA models using 30 docked conformations gives $q^2$ Leave one out (LOO) values of 0.756 and 0.617, and $r^2$ ncv values of 0.988 and 0.956, respectively. The ability of prediction and robustness of the models were evaluated by test set, cross validation (leave-one-out and leave-ten-out), bootstrapping, and progressive scrambling approaches. The all-orientation search (AOS) was used to achieve the best orientation to minimize the effect of initial orientation of the structures. The docking results confirmed CoMFA and CoMSIA contour maps. The docking and 3D-QSAR studies were thoroughly interpreted and discussed and confirmed the experimental $pIC_{50}$ values.

Docking, CoMFA and CoMSIA Studies of a Series of N-Benzoylated Phenoxazines and Phenothiazines Derivatives as Antiproliferative Agents

Jahan B. Ghasemi,Elham Aghaee,Ali Jabbari 대한화학회 2013 Bulletin of the Korean Chemical Society Vol.34 No.3

Using generated conformations from docking analysis by Gold algorithm, some 3D-QSAR models; CoMFA and CoMSIA have been created on 39 N-benzoylated phenoxazines and phenothiazines, including their Soxidized analogues. These molecules inhibit the polymerization of tubulin into microtubules and thus they have been studied for the development of antitumor drugs. Training set for the CoMFA and CoMSIA models using 30 docked conformations gives q2 Leave one out (LOO) values of 0.756 and 0.617, and r2 ncv values of 0.988 and 0.956, respectively. The ability of prediction and robustness of the models were evaluated by test set, cross validation (leave-one-out and leave-ten-out), bootstrapping, and progressive scrambling approaches. The allorientation search (AOS) was used to achieve the best orientation to minimize the effect of initial orientation of the structures. The docking results confirmed CoMFA and CoMSIA contour maps. The docking and 3DQSAR studies were thoroughly interpreted and discussed and confirmed the experimental pIC50 values.

3D-QSAR Studies of 2-Arylbenzoxazoles as Novel Cholesteryl Ester Transfer Protein Inhibitors

Jahan B. Ghasemi,Mahnaz Ayati,Somayeh Pirhadi 대한화학회 2011 Bulletin of the Korean Chemical Society Vol.32 No.2

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.

A New Variable Selection Method Based on Mutual Information Maximization by Replacing Collinear Variables for Nonlinear Quantitative Structure-Property Relationship Models

Jahan B. Ghasemi,Ehsan Zolfonoun 대한화학회 2012 Bulletin of the Korean Chemical Society Vol.33 No.5

Selection of the most informative molecular descriptors from the original data set is a key step for development of quantitative structure activity/property relationship models. Recently, mutual information (MI) has gained increasing attention in feature selection problems. This paper presents an effective mutual information-based feature selection approach, named mutual information maximization by replacing collinear variables (MIMRCV), for nonlinear quantitative structure-property relationship models. The proposed variable selection method was applied to three different QSPR datasets, soil degradation half-life of 47 organophosphorus pesticides, GC-MS retention times of 85 volatile organic compounds, and water-to-micellar cetyltrimethylammonium bromide partition coefficients of 62 organic compounds.The obtained results revealed that using MIMRCV as feature selection method improves the predictive quality of the developed models compared to conventional MI based variable selection algorithms.

Spectrophotometric Study of Acidity and Complex Formation of Anti-Inflammatory Drug Piroxicam with Some Transition Metal Ions in Different Methanol/Water Mixtures by Chemometric Methods

Ghasemi, Jahan B.,Jalalvand, Alireza Korean Chemical Society 2009 대한화학회지 Vol.53 No.6

소염제 piroxicam (PX, 4-hydroxy-2-methyl-N-2-pridyl-2H-1, 2-benzothiazine-3-carboxadiamide-1,1-dioxide)의 착물형성을 전이금속이온, Co(II), Ni(II), Cu(II), Zn(II)과 함께 메탄올(MeOH)/물 이성분 혼합물에서 25$^{\circ}C$, 일정한 pH=5.0와 I=0.1 M에서 분광광도법으로 연구하였다. 컴퓨터 프로그램 SQUAD를 스팩트라 데이터로부터 원하는 정보를 얻는데 사용하였다. Fitting 과정의 output은 안정도 상수, 평가한 안정도 상수의 표준편차, 농도분포 다아그램, 모든 종의 스팩트럼 프로파일이다. Co(II), Ni(II), Cu(II), Zn(II)의 PX 착체의 안정도 순서는 Cu(II) > Co(II) > Ni(II) ${\approx}$ Zn(II) 순서이다. 이것은 이들 금속이 온들이 기하학적 경향이 다른 이유일 것이다. PX의 산성도 상수는 다른 pH 값에서 흡수 스펙트럼으로 부터 위의 조건에서 역시 결정하였다. 컴퓨터 프로그램 DATAN을 PX의 산성도 상수의 결정하는 데 사용하였다. 산성도 상수의 validity는 잘 알려진 컴퓨터 프로그램 SPECFIT/32을 사용하였다. 안정 및 산성도 상수의 용매성질, 음이온과 같은 다른 인자의 효과에 관하여 자세하게 논의하였다. The complex formation of anti-inflamatory drug piroxicam (PX, 4-hydroxy-2-methyl-N-2--pridyl-2H-1,2-benzothiazine-3-carboxadiamide-1,1-dioxide) with transition metal ions Co(II), Ni(II), Cu(II) and Zn(II) in methanol(MeOH)/water binary mixtures were studied by spectrophotometric method at 25$^{\circ}C$, constant pH = 5.0 and I = 0.1 M. The computer program SQUAD was used to extract the desired information from the spectral data. The outputs of the fitting processes were stability constants, standard deviations of the estimated stability constants, concentration distribution diagrams and spectral profiles of all species. The sequence of the stability constants of PX complexes with Co(II), Ni(II), Cu(II) and Zn(II) follow the Cu(II) > Co(II) > Ni(II) ${\approx}$ Zn(II) order. This may be due to different geometry tendencies of these metal ions. The acidity constants of the PX were also determined under above condition from its absorption spectra at different pH values. The computer program DATAN was used for determination of acidity constants of PX. The validity of the obtained acidity constants was checked by a well known computer program SPECFIT/32. The effects of the different parameters like solvent nature, cations characteristics on the stability and acidity constants were thoroughly discussed.