Docking Study and Three‐Dimensional Quantitative Structure‐Activity Relationship (3D‐QSAR) Analyses and Novel Molecular Design of a Series of 4‐Aminoquinazolines as Inhibitors of Aurora B Kinase

The Aurora proteins are critical regulators of major mitotic events and attractive targets for anticancer therapy. 3D‐QSAR studies based on molecular docking were performed on a dataset of 40 4‐aminoquinazolines compounds. The CoMSIA model produced significantly better results than CoMFA model, with q²=0.652 and r²=0.991. The contours analysis provides useful information about the structural requirements for 4‐aminoquinazolines for inhibiting Aurora B. Scaffold hopping method was used to generate new structures based on the maximum common substructure of the training and test set compounds. The ADMET property, binding affinity and inhibitory activity of the new designed compounds were predicted, respectively. Finally 16 compounds were identified as the novel inhibitors for Aurora B kinase.     

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     

2D and 3D‐QSAR studies on antiproliferative thiazolidine analogs

Two‐dimensional (2D) and three‐dimensional (3D) quantitative structure–activity relationships (QSARs) of 22 thiazolidine analogs with antiproliferative activity expressed as pIC₅₀, which is defined as the negative value of the logarithm of necessary molar concentration of these compounds to cause 50% growth inhibition against melanoma cell lines WM‐164, have been studied by using a combined method of the DFT, MM2 and statistics for 2D, as well as the comparative molecular field analysis (CoMFA) method for 3D. The established 2D‐QSAR model in training set comprised of random 18 compounds shows not only significant statistical quality, but also predictive ability, with the square of adjusted correlation coefficient (R = 0.832) and the square of the cross‐validation coefficient (q² = 0.803). The same model was further applied to predict pIC₅₀ values of the four compounds in the test set, and the resulting R reaching 0.784, further confirms that this 2D‐QSAR model has high predictive ability. The 3D‐QSAR model also shows good correlative and predictive capabilities in terms of R² (0.956) and q² (0.615) obtained from CoMFA model. Further, the robustness of the CoMFA model was verified by bootstrapping analysis (100 runs) with R (0.979) and SD_bs (0.056). It is very interesting to find that the results from 2D‐ and 3D‐QSAR analyses accord with each other, and they all show that the steric interaction plays a crucial role in determining the cytotoxicities of the compounds, and that selecting a moderate‐size or appropriate‐hydrophobicity substituent R as well as increasing the negative charges of C₄ on phenyl ring at the same time are advantageous to improving the cytotoxicity. Such results can offer some useful theoretical references for directing the molecular design and understanding the action mechanism of this kind of compound with antiproliferative activity. © 2008 Wiley Periodicals, Inc. Int J Quantum Chem, 2008     

Insight into the structural requirements of benzimidazole derivatives as interleukin‐2 inducible t‐cell kinase inhibitors by computational explorations

In the present work, a set of ligand‐ and receptor‐based 3D‐QSAR models were developed to explore the structure–activity relationship of 109 benzimidazole‐based interleukin‐2‐inducible T‐cell kinase (ITK) inhibitors. In order to reveal the requisite 3D structural features impacting the biological activities, a variety of in silico modeling approaches including the comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), docking, and molecular dynamics were applied. The results showed that the ligand‐based CoMFA model (Q² = 0.552, R²_ncv = 0.908, R²_pred = 0.787, SEE = 0.252, SEP = 0.558) and CoMSIA model (Q² = 0.579, R²_ncv = 0.914, R²_pred = 0.893, SEE = 0.240, SEP = 0.538) were superior to other models with greater predictive power. In addition, a combined analysis between the 3D contour maps and docking results showed that: (1) Compounds with bulky or hydrophobic substituents near ring D and electropositive or hydrogen acceptor groups around rings C and D could increase the activity. (2) The key amino acids impacting the receptor–ligand interactions in the binding pocket are Met438, Asp500, Lys391, and Glu439. The results obtained from this work may provide helpful guidelines in design of novel benzimidazole analogs as inhibitors of ITK. © 2013 Wiley Periodicals, Inc.     

Synthesis,Bioactivities and Structure Activity Relationship of N‐4‐Methyl‐1,2,3‐thiadiazole‐5‐carbonyl‐N′‐phenyl Ureas

Twenty nine novel N‐4‐methyl‐1,2,3‐thiadiazole‐5‐carbonyl‐N′‐phenyl ureas were designed and synthesized, and their structures were confirmed by proton nuclear magnetic resonance (¹H NMR), infra red spectroscopy (IR) and high‐resolution mass spectroscopy (HRMS). Compounds V‐9 , V‐11 , V‐12 , V‐15 , V‐19 , V‐21 , V‐22 and V‐24 exhibit excellent activity against Culex pipiens pallens. Compounds V‐12 and V‐22 present good insecticidal activity against Plutella xylostella L. Their median lethal concentrations (LC₅₀) are 164.15 and 89.69 mg·L^?1, respectively. Compound V‐11 also has potential wide spectrum of fungicide activity. Its median effective concentrations (EC₅₀) detected from 3.82 µg·mL^?1 against Physalospora piricola to 31.60 µg·mL^?1 against Cercospora arachidicola. Compounds V‐15 and V‐24 show outstanding induction activities as same as positive controls TDL and ningnanmycin, furthermore V‐24 has the highest induction activity of 41.85%±4.43%. To elucidate the structure activity relationship in these compounds, a 3D‐QSAR model has been built. The established model showed a reliable predicting ability with q² values of 0.643 and r² values of 0.982.     

3D－QSAR Study on Diindolylmethane and Its Analogues with Comparative Molecular Field Analysis(CoMFA)

Comparative molecular field analysis (CoMFA),a three dimensional quantitative structure-activity relationship (3D-QSAR) method was applied to a series of diindolylmethane(DIM) analogs to study the relationship between their structure and their induction of CYP 1A1-associated ethoxyresorufin-O-deethylase(EROD) activity.A DISCO model of pharmacophore was derved to guide the superposition of the compounds.The coefficient of cross-validation (q^2) and non cross-validation(r^2) for the model established by the study are 0.827 and 0.988 respectively,the value of variance ratio (F) is 103.53 and standard error estimate (SEE)is 0.044.These values indicate that the CoMFA model derived is significant and might have a good prediction for the catalytic activity of DIM compounds.As a consequence,the predicted activity values of new designed compounds were all higher than that of the reported value.     

Binding conformations,QSAR, and molecular design of Alkene‐3‐quinolinecarbonitriles as Src inhibitors

A theoretical study on binding orientations and quantitative structure–activity relationship (QSAR) of a novel series of alkene‐3‐quinolinecarbonitriles acting as Src inhibitors has been carried out by using the docking study and three‐dimensional QSAR (3D‐QSAR) analyses. The appropriate binding orientations and conformations of these compounds interacting with Src kinase were revealed by the docking studies, and the established 3D‐QSAR models show significant statistical quality and satisfactory predictive ability, with high R² values and q² values: comparative molecular field analysis (CoMFA) model (q² = 0.748, R² = 0.972), comparative molecular similarity indices analysis (CoMSIA) model (q² = 0.731, R² = 0.987). The systemic external validation indicated that both CoMFA and CoMSIA models possessed high predictive powers with $ R{^2}_{\!\!\!\rm pred} $ values of 0.818 and 0.892, $ {r^2}_{\!\!\!\rm m} $ values of 0.879 and 0.886, $ {r^2}_{\!\!\!\rm m(LOO)} $ values of 0.874 and 0.874, $ r^2_{\rm m(overall)} $ values of 0.879 and 0.885, respectively. Several key structural features of the compounds responsible for inhibitory activity were discussed in detail. Based on these structural factors, eight new compounds with quite higher predicted Src‐inhibitory activities have been designed and presented. We hope these theoretical results can offer some valuable references for the pharmaceutical molecular design as well as the action mechanism analysis. © 2012 Wiley Periodicals, Inc.     

DFT‐based QSAR study and molecular design of AHMA derivatives as potent anticancer agents

A quantitative structure–activity relationship (QSAR) of 3‐(9‐acridinylamino)‐5‐hydroxymethylaniline (AHMA) derivatives and their alkylcarbamates as potent anticancer agents has been studied using density functional theory (DFT), molecular mechanics (MM+), and statistical methods. In the best established QSAR equation, the energy (E_NL) of the next lowest unoccupied molecular orbital (NLUMO) and the net charges (Q_FR) of the first atom of the substituent R, as well as the steric parameter (MR₂) of subsituent R₂ are the main independent factors contributing to the anticancer activity of the compounds. A new scheme determining outliers by “leave‐one‐out” (LOO) cross‐validation coefficient (q) was suggested and successfully used. The fitting correlation coefficient (R²) and the “LOO” cross‐validation coefficient (q²) values for the training set of 25 compounds are 0.881 and 0.829, respectively. The predicted activities of 5 compounds in the test set using this QSAR model are in good agreement with their experimental values, indicating that this model has excellent predictive ability. Based on the established QSAR equation, 10 new compounds with rather high anticancer activity much greater than that of 34 compounds have been designed and await experimental verification. © 2006 Wiley Periodicals, Inc. Int J Quantum Chem, 2007     

Conceptual DFT properties‐based 3D QSAR: Analysis of inhibitors of the nicotine metabolizing CYP2A6 enzyme

Structure‐activity relationships of 46 P450 2A6 inhibitors were analyzed using the 3D‐QSAR methodology. The analysis was carried out to confront the use of traditional steric and electrostatic fields with that of a number of fields reflecting conceptual DFT properties: electron density, HOMO, LUMO, and Fukui f⁻ function as 3D fields. The most predictive models were obtained by combining the information of the electron density with the Fukui f⁻ function (r² = 0.82, q² = 0.72), yielding a statistically significant and predictive model. The generated model was able to predict the inhibition potencies of an external test set of five chemicals. The result of the analysis indicates that conceptual DFT‐based molecular fields can be useful as 3D QSAR molecular interaction fields. © 2008 Wiley Periodicals, Inc. J Comput Chem 2009     

Three-dimensional Quantitative Structure-Activity Relationship Analyses of a Series of Butenolide ETA Antagonists

Two kinds of Three-dimensional Quantitative Structure-activity Relationship(3D-QSAR) methods,comparative molecular filed analysis(CoMFA) and comparative molecular similarity indices analysis (CoMSIA) ,were applied to analyze the structure-activity relationship of a series of 63 butenolide ETA selective antagonists with respect to their inhibition against human ETA receptor,The CoMFA and CoMSIA models were developed for the conceivable alignment of the molecules based on a template structure from the crystallized data.The statistical results from the initial orientation of the aligned molecules show that the 3D-QSAR model from CoMFA(q^2=0.543) is obviously superior to that from the conventional CoMSIA(q^2=0.407).In order to refine the model,all-space search (ASS) was applied to minimize the field sampling process.By rotating and translating the molecular aggregate within the grid systematically,all the possible samplings of the molecular fields were tested and subsequently the one with the highest q^2 was picked out .The comparison of the sensitivity of CoMFA and CoMSIA to different space orientation shows that the CoMFA q^2 values are more sensitive to the translations and rotations of the aligned molecules with respect to the lattice than those of CoMSIA.The best CoMFA model from ASS was further refined by the region focused technique.The high quality of the best model is indicated by the high corss-validated correlation and the prediction on the external test set.The CoMFA coefficient contour plots identify several key features that explain the wide range of activities,which may help us to design new effective ETA selective antagonists.     

Some case studies on application of “rm2” metrics for judging quality of quantitative structure–activity relationship predictions: Emphasis on scaling of response data

Quantitative structure–activity relationship (QSAR) techniques have found wide application in the fields of drug design, property modeling, and toxicity prediction of untested chemicals. A rigorous validation of the developed models plays the key role for their successful application in prediction for new compounds. The r_m² metrics introduced by Roy et al. have been extensively used by different research groups for validation of regression‐based QSAR models. This concept has been further advanced here with introduction of scaling of response data prior to computation of r_m². Further, a web application (accessible from http://aptsoftware.co.in/rmsquare/ and http://203.200.173.43:8080/rmsquare/ ) for calculation of the r_m² metrics has been introduced here. The present study reports that the web application can be easily used for computation of r_m² metrics provided observed and QSAR‐predicted data for a set of compounds are available. Further, scaling of response data is recommended prior to r_m² calculation. © 2013 Wiley Periodicals, Inc.     

A facile synthesis of novel 5‐substituted pyridine 2 carboxamide derivatives and their biological evaluation and 3D QSAR studies

A variety of novel 5‐substituted pyridine 2 carboxamides were designed and synthesized using both normal and solvent‐free microwave (MW) irradiation techniques. The results revealed that MW protocol proceeded smoothly under mild reaction conditions in short reaction times, thus avoiding the use of toxic organic solvents. Structural elucidation of the synthesized compounds was carried out on the basis of various spectroscopic methods, such as ¹H NMR, ¹³C NMR, LCMS, and IR. The synthesized compounds were evaluated for their in vitro antimicrobial activity (MIC) using the agar disk diffusion method. Among the various synthetic compounds, compound 3b showed higher potential activity against Escherichia coli than the other compounds. The order of activity against E. coli of the studied compounds is 3b > 3e > 3g > 3h > 3d > 3c > 3a > 3f . Additionally, 2D and 3D structural features of the synthesized derivatives were recognized by the 3D‐QSAR model. This validated model exhibited good internal (r², 0.924) and external prediction (r²pred, 0.851) correlation. The results of QSAR studies concluded that Alog P, the number of hydrogen bond acceptors, and the number of rotatable bonds were necessary features for the activity of the pyridine carboxamide derivatives.     

Tailoring the Structure of Two‐Dimensional Self‐Assembled Nanoarchitectures Based on NiII–Salen Building Blocks

The synthesis of a series of Ni^II–salen‐based complexes with the general formula of [Ni(H₂L)] (H₄L=R²‐N,N′‐bis[R¹‐5‐(4′‐benzoic acid)salicylidene]; H₄L1: R²=2,3‐diamino‐2,3‐dimethylbutane and R¹=H; H₄L2: R²=1,2‐diaminoethane and R¹=tert‐butyl and H₄L3: R²=1,2‐diaminobenzene and R¹=tert‐butyl) is presented. Their electronic structure and self‐assembly was studied. The organic ligands of the salen complexes are functionalized with peripheral carboxylic groups for driving molecular self‐assembly through hydrogen bonding. In addition, other substituents, that is, tert‐butyl and diamine bridges (2,3‐diamino‐2,3‐dimethylbutane, 1,2‐diaminobenzene or 1,2‐diaminoethane), were used to tune the two‐dimensional (2D) packing of these building blocks. Density functional theory (DFT) calculations reveal that the spatial distribution of the LUMOs is affected by these substituents, in contrast with the HOMOs, which remain unchanged. Scanning tunneling microscopy (STM) shows that the three complexes self‐assemble into three different 2D nanoarchitectures at the solid–liquid interface on graphite. Two structures are porous and one is close‐packed. These structures are stabilized by hydrogen bonds in one dimension, while the 2D interaction is governed by van der Waals forces and is tuned by the nature of the substituents, as confirmed by theoretical calculations. As expected, the total dipolar moment is minimized