CoMFA,CoMSIA, Topomer CoMFA,HQSAR, molecular docking and molecular dynamics simulations study of triazine morpholino derivatives as mTOR inhibitors for the treatment of breast cancer

mTOR has become a promising target for many types of cancer like breast, lung and renal cell carcinoma. CoMFA, CoMSIA, Topomer CoMFA and HQSAR were performed on the series of 39 triazine morpholino derivatives. CoMFA analysis showed q² value of 0.735, r²_cv value of 0.722 and r²_pred value of 0.769. CoMSIA analysis (SEHD) showed q² value of 0.761, r²_cv value of 0.775 and r²_pred value of 0.651. Topomer CoMFA analysis showed q² value of 0.693, r² (conventional correlation coefficient) value of 0.940 and r²_pred value of 0.720. HQSAR analysis showed q²,r²and r²_pred values of 0.694, 0.920 and 0.750, respectively. HQSAR analysis with the combination of atomic number (A), bond type (B) and atomic connections showed q² and r² values of 0.655 and 0.891, respectively. Contour maps from all studies provided significant insights. Molecular docking studies with molecular dynamics simulations were carried out on the highly potent compound 36. Furthermore, four acridine derivatives were designed and docking results of these designed compounds showed the same interactions as that of the standard PI-103 which proved the efficiency of 3D-QSAR and MD/MS study. In future, this study might be useful prior to synthesis for the designing of novel mTOR inhibitors.     

Computational Analysis of CRTh2 receptor antagonist: A Ligand-based CoMFA and CoMSIA approach

CRTh2 receptor is an important mediator of inflammatory effects and has attracted much attention as a therapeutic target for the treatment of conditions such as asthma, COPD, allergic rhinitis and atopic dermatitis. In pursuit of better CRTh2 receptor antagonist agents, 3D-QSAR studies were performed on a series of 2-(2-(benzylthio)-1H-benzo[d]imidazol-1-yl) acetic acids. There is no crystal structure information available on this protein; hence in this work, ligand-based comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed by atom by atom matching alignment using systematic search and simulated annealing methods. The 3D-QSAR models were generated with 10 different combinations of test and training set molecules, since the robustness and predictive ability of the model is very important. We have generated 20 models for CoMFA and 100 models for CoMSIA based on two different alignments. Each model was validated with statistical cut off values such as q² > 0.4, r² > 0.5 and r²_pred > 0.5. Based on better q² and r²_pred values, the best predictions were obtained for the CoMFA (model 5 q² = 0.488, r²_pred = 0.732), and CoMSIA (model 45 q² = 0.525, r²_pred = 0.883) from systematic search conformation alignment. The high correlation between the cross-validated/predicted and experimental activities of a test set revealed that the CoMFA and CoMSIA models were robust. Statistical parameters from the generated QSAR models indicated the data is well fitted and have high predictive ability. The generated models suggest that steric, electrostatic, hydrophobic, H-bond donor and acceptor parameters are important for activity. Our study serves as a guide for further experimental investigations on the synthesis of new CRTh2 antagonist.     

Structural investigations of anthranilimide derivatives by CoMFA and CoMSIA 3D-QSAR studies reveal novel insight into their structures toward glycogen phosphorylase inhibition

In the present work, three-dimensional quantitative structure–activity relationship (3-D QSAR) studies on a set of 70 anthranilimide compounds has been performed using docking-based as well as substructure-based molecular alignments. This resulted in the selection of more statistically relevant substructure-based alignment for further studies. Further, molecular models with good predictive power were derived using CoMFA (r ^2?=?0.997; Q ^2?=?0.578) and CoMSIA (r ^2?=?0.976; Q ^2?=?0.506), for predicting the biological activity of new compounds. The so-developed contour plots identified several key features of the compounds explaining wide activity ranges. Based on the information derived from the CoMFA contour maps, novel leads were proposed which showed better predicted activity with respect to the already reported systems. Thus, the present study not only offers a highly significant predictive QSAR model for anthranilimide derivatives as glycogen phosphorylase (GP) inhibitors which can eventually assist and complement the rational drug-design attempts, but also proposes a highly predictive pharmacophore model as a guide for further development of selective and more potent GP inhibitors as anti-diabetic agents.     

CoMFA Analysis of Biodegradability

Abstract

CoMFA (comparative molecular field analysis) has been used to correlate the biodegradability of several classes of compounds. The technique uses an atomic probe to detect the steric and electrostatic fields around a molecule. Good cross-validated correlations were obtained for some series (alcohols, carboxylic acids and linear alkyl benzene sulphonates). Correlations were weaker for esters and benzene sulphonates, and were non-existent for phenols. These results may reflect the unreliability of biodegradation data, but may also be a result of molecular misalignment in the CoMFA procedure. CoMFA appears to be a potentially very useful method for the prediction of biodegradability.     

CoMFA and CoMSIA studies on C-aryl glucoside SGLT2 inhibitors as potential anti-diabetic agents

SGLT2 has become a target of therapeutic interest in diabetes research. CoMFA and CoMSIA studies were performed on C-aryl glucoside SGLT2 inhibitors (180 analogues) as potential anti-diabetic agents. Three different alignment strategies were used for the compounds. The best CoMFA and CoMSIA models were obtained by means of Distill rigid body alignment of training and test sets, and found statistically significant with cross-validated coefficients (q ²) of 0.602 and 0.618, respectively, and conventional coefficients (r ²) of 0.905 and 0.902, respectively. Both models were validated by a test set of 36 compounds giving satisfactory predicted correlation coefficients (r ² _pred) of 0.622 and 0.584 for CoMFA and CoMSIA models, respectively. A comparison was made with earlier 3D QSAR study on SGLT2 inhibitors, which shows that our 3D QSAR models are better than earlier models to predict good inhibitory activity. CoMFA and CoMSIA models generated in this work can provide useful information to design new compounds and helped in prediction of activity prior to synthesis.     

细胞周期蛋白依赖性激酶CDK4抑制剂的3D-QSAR研究

采用比较分子场分析法（comparative molecular field analysis，CoMFA）和比较分子相似性指数分析法（comparative similarity indices analysis，CoMSIA），系统研究了57个CDK4酶抑制剂的三维定量结构-活性关系．所建立CoMFA和CoMSIA模型的交叉验证系数q^2值分别为0．656和0．811，非交叉验证相关系数r^2分别为0．954和0．969，都具有较好的预测能力．CoMFA和CoMSIA模型的三维等值图直观地解释了化合物的构效关系，为进一步研究提供了重要依据．     

Theoretical studies on QSAR and mechanism of 2‐indolinone derivatives as tubulin inhibitors

The theoretical studies on three‐dimensional quantitative structure activity relationship (3D‐QSAR) and action mechanism of a series of 2‐indolinone derivatives as tubulin inhibitors against human breast cancer cell line MDA‐MB‐231 have been carried out. The established 3D‐QSAR model from the comparative molecular field analysis (CoMFA) shows not only significant statistical quality but also predictive ability, with high correlation coefficient (R² = 0.986) and cross‐validation coefficient (q² = 0.683). In particular, the appropriate binding orientations and conformations of these 2‐indolinone derivatives interacting with tubulin are located by docking study, and it is very interesting to find that the plot of the energy scores of these compounds in DOCK versus the corresponding experimental pIC₅₀ values exhibits a considerable linear correlation. Therefore, the inhibition mechanism that 2‐indolinone derivatives were regarded as tubulin inhibitors can be theoretically confirmed. Based on such an inhibition mechanism along with 3D‐QSAR results, some important factors improving the activities of these compounds were discussed in detail. These factors can be summarized as follows: the H atom adopted as substituent R₁, the substituent R₂ with higher electropositivity and smaller bulk, the substituents R₄–R₆ (on the phenyl ring) with higher electropositivity and larger bulk, and so on. These results can offer useful theoretical references for understanding the action mechanism, designing more potent inhibitors, and predicting their activities prior to synthesis. © 2008 Wiley Periodicals, Inc. Int J Quantum Chem, 2009     

雌激素β受体喹啉类配体的分子对接及3D-QSAR研究

对33个喹啉衍生物的雌激素β受体活性进行了分子对接以及比较分子力场分析(CoMFA)和比较分子相似性指数分析(CoMSIA). 对接结果显示氢键和疏水作用是配体与受体结合的主要因素,同时结果亦显示对接结合能与观测值pIC50具有极显著的线性相关性. 根据对接后各优势构象将33个样本进行叠合并进行CoMFA与CoMSIA研究,均得到了较优的结果,其中以选用立体场、静电场和疏水场建立的CoMSIA模型结果最优,其主成分数,r2,q2（LOO）和r2pred分别为2, 0.894, 0.708和0.802. 构效关系模型分析显示基团的空间位阻、电性及疏水作用是影响活性的主要因素     

Comparative Molecular Field Analysis （CoMFA） of Curcumin-related Compounds for Anticancer Activity

Three-dimensional （3D） quantitative structure-activity relationship （QSAR） studies of 44 curcumin-related compounds have been carried out based on our previously reported result for their anticancer activity against pancreas cancer Panc-I cells and colon cancer HT-29 cells. The established 3D-QSAR models from the comparative molecular field analysis （CoMFA） in training set showed not only significant statistical quality, but also satisfying predictive ability, with high correlation coefficient values （R12= 0.911, R22= 0.985） and cross-validation coefficient values （q2= 0.580, q22= 0.722）. Based on the CoMFA contour maps, some key structural factors responsible for anticancer activity of these series of compounds were revealed. The results provide some useful theoretical references for understanding the mechanism of action, designing new curcumin-related compounds with anticancer activity and predicting their activities prior to synthesis.