Molecular Modeling and Design of Arylthioindole Derivatives as Tubulin Inhibitors

Three-dimensional quantitative structure activity relationship （3D-QSAR） and docking studies of a series of arylthioindole derivatives as tubulin inhibitors against human breast cancer cell line MCF-7 have been carried out. An optimal 3D-QSAR model from the comparative molecular field analysis （CoMFA） for training set with significant statistical quality （R2=0.898） and predictive ability （q2=0.654） was established. The same model was further applied to predict pIC50 values of the compounds in test set, and the resulting predictive correlation coefficient R2（pred） reaches 0.816, further showing that this CoMFA model has high predictive ability. Moreover, the appropriate binding orientations and conformations of these compounds interacting with tubulin are located by docking study, and it is very interesting to find the consistency between the CoMFA field distribution and the 3D topology structure of active site of tubulin. Based on CoMFA along with docking results, some important factors improving the activities of these compounds were discussed in detail and were summarized as follows： the substituents R3-R5 （on the phenyl ring） with higher electronegativity, the substituent R6 with higher eleetropositivity and bigger bulk, the substituent R7 with smaller bulk, and so on. In addition, five new compounds with higher activities have been designed. Such results can offer useful theoretical references for experimental works.     

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     

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     

3D QSAR Studies on Benzyl Phenyl Ether Diamidine Derivatives with Antiprotozoal Activities

Human African trypanosomiasis (HAT) is a neglected tropical disease, and some drugs treating HAT have been used for even more than 60 years. Currently, a series of benzyl phenyl ether diamidine derivatives are discovered, which exhibit high antiprotozoal activities and low cytotoxicity, leading to good development prospects. The comparative molecular field analysis (CoMFA) and the comparative molecular similarity indices analysis (CoMSIA) are used to study the relationship between the structure and antiprotozoal activities. The established 3D QSAR model shows not only significant statistical quality, but also satisfies predictive ability: the best CoMFA model had r² = 0.958 and q² = 0.766, the best CoMSIA model had r² = 0.957 and q² = 0.812, the predictive ability of CoMFA and CoMSIA model were further confirmed by a test set which had 11 compounds, giving the correlation coefficient Q_ext² of 0.792, 0.873, respectively. The contour maps and contribution maps show important features that can improve the antiprotozoal activity: position 3 from substituent R4 should be a low electronegativity group, position 4 from substituent R₄ should have higher electronegativity, substituent R₂ should be selected to a low electronegativity and small bulk group. Together these results may offer some useful theoretical information in designing potential inhibitors.     

A Quantitative Structure–Activity Relationship Study of Calpeptin (Calpain Inhibitor) as an Anticancer Agent

Calpeptin analogs show anticancer properties with inhibition of calpain. In this work, we applied a quantitative structure–activity relationship (QSAR) model on 34 calpeptin derivatives to select the most appropriate compound. QSAR was employed to generate the models and predict the more significant compounds through a series of calpeptin derivatives. The HyperChem, Gaussian 09, and Dragon software programs were used for geometry optimization of the molecules. The 2D and 3D molecular structures were drawn by ChemDraw (Ultra 16.0) and Chem3D (Pro16.0) software. The Unscrambler program was used for the analysis of data. Multiple linear regression (MLR‐MLR), partial least‐squares (MLR‐PLS1), principal component regression (MLR‐PCR), a genetic algorithm‐artificial neural networks (GA‐ANN), and a novel similarity analysis‐artificial neural network (SA‐ANN) method were used to create QSAR models. Among the three MLR models, MLR‐MLR provided better statistical parameters. The R² and RMSE of the prediction were estimated as 0.8248 and 0.26, respectively. Nevertheless, the constructed model using GA‐ANN revealed the best statistical parameters among the studied methods (R² test = 0.9643, RMSE test = 0.0155, R² train = 0.9644, RMSE train = 0.0139). The GA‐ANN model is found to be the most favorable method among the statistical methods and can be employed for designing new calpeptin analogs as potent calpain inhibitors in cancer treatment.     

Grid potential analysis,virtual screening studies and ADME/T profiling on N‐arylsulfonylindoles as anti‐HIV‐1 agents

A grid potential analysis employing a novel approach of 3D quantitative structure–activity relationships (QSAR) as AutoGPA module in MOE2009.10 was performed on a dataset of 42 compounds of N‐arylsulfonylindoles as anti‐HIV‐1 agents. The uniqueness of AutoGPA module is that it automatically builds the 3D‐QSAR model on the pharmacophore‐based molecular alignment. The AutoGPA‐based 3D‐QSAR model obtained in the present study gave the cross‐validated Q² value of 0.588, r²_pred value of 0.701, r²_m statistics of 0.732 and Fisher value of 94.264. The results of 3D‐QSAR analysis indicated that hydrophobic groups at R₁ and R₂ positions and electron releasing groups at R₃ position are favourable for good activity. To find similar analogues, virtual screening on ZINC database was carried out using generated AutoGPA‐based 3D‐QSAR model and showed good prediction. In addition to those mentioned earlier, in‐silico ADME absorption, distribution, metabolism and excretion profiling and toxicity risk assessment test was performed, and results showed that majority of compounds from current dataset and newly virtually screened hits generated were within their standard limit. Copyright © 2013 John Wiley & Sons, Ltd.     

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.     

3D-QSAR Study on a Series of Indolo[1,2-b]quinazoline Derivatives with Anticancer Activity and their Molecular Design

Indolo[1,2-b]quinazoline derivatives have recently been reported as a type of compound with potential anticancer activity. On the basis of our the published two-dimensional quantitative structure-activity relationship (2D-QSAR) of these compounds, a further study on the three-dimensional quantitative structure-activity relationship (3D-QSAR) was carried out using the method of comparative molecular field analysis (CoMFA). A reasonable, receivable, and an effective 3D-QSAR model has been established, in which the correlation coefficient (r²) and cross-validation coefficient (q²) values are 0.986 and 0.695, respectively, the statistical squared deviation ratio (F) is 114.6, and the standard deviation (SD) is 0.084. The results suggest that the electrostatic effect of substituent R₁ and steric effect of substituent R₂ play a very important role in the improvement of the anticancer activity of these compounds. In this article, some significant conclusions, which are in good agreement with the conclusions obtained using 2D-QSAR, were drawn as follows. (1) The electrostatic effect in the substituent R₁ part plays a major role, and it is very important to make the first atom of R₁ carrying more positive charges in order to improve the anticancer activity of the compounds. (2) The steric effect plays a major role in the substituent R₂ part, and the volume of R₂ should be moderate. Based on the above conclusions, three new molecules of Indolo[1,2-b]quinazoline derivatives with higher anticancer activity have been theoretically designed and are waiting for support from experiment. The QSAR results can offer a theoretical reference for the pharmaceutical synthesis.     

Mirror‐Image Organometallic Osmium Arene Iminopyridine Halido Complexes Exhibit Similar Potent Anticancer Activity

Four chiral Os^II arene anticancer complexes have been isolated by fractional crystallization. The two iodido complexes, (S_Os,S_C)‐[Os(η⁶‐p‐cym)(ImpyMe)I]PF₆ (complex 2 , (S)‐ImpyMe: N‐(2‐pyridylmethylene)‐(S)‐1‐phenylethylamine) and (R_Os,R_C)‐[Os(η⁶‐p‐cym)(ImpyMe)I]PF₆ (complex 4 , (R)‐ImpyMe: N‐(2‐pyridylmethylene)‐(R)‐1‐phenylethylamine), showed higher anticancer activity (lower IC₅₀ values) towards A2780 human ovarian cancer cells than cisplatin and were more active than the two chlorido derivatives, (S_Os,S_C)‐[Os(η⁶‐p‐cym)(ImpyMe)Cl]PF₆, 1 , and (R_Os,R_C)‐[Os(η⁶‐p‐cym)(ImpyMe)Cl]PF₆, 3 . The two iodido complexes were evaluated in the National Cancer Institute 60‐cell‐line screen, by using the COMPARE algorithm. This showed that the two potent iodido complexes, 2 (NSC: D‐758116/1) and 4 (NSC: D‐758118/1), share surprisingly similar cancer cell selectivity patterns with the anti‐microtubule drug, vinblastine sulfate. However, no direct effect on tubulin polymerization was found for 2 and 4 , an observation that appears to indicate a novel mechanism of action. In addition, complexes 2 and 4 demonstrated potential as transfer‐hydrogenation catalysts for imine reduction.     

Hydrophilicity Control of Visible‐Light Hydrogen Evolution and Dynamics of the Charge‐Separated State in Dye/TiO2/Pt Hybrid Systems

Visible‐light‐driven H₂ evolution based on Dye/TiO₂/Pt hybrid photocatalysts was investigated for a series of (E)‐3‐(5′‐{4‐[bis(4‐R¹‐phenyl)amino]phenyl}‐4,4′‐(R²)₂‐2,2′‐bithiophen‐5‐yl)‐2‐cyanoacrylic acid dyes. Efficiencies of hydrogen evolution from aqueous suspensions in the presence of ethylenediaminetetraacetic acid as electron donor under illumination at λ>420 nm were found to considerably depend on the hydrophilic character of R¹, varying in the order MOD (R¹=CH₃OCH₂, R²=H)≈ MO4D (R¹=R²=CH₃OCH₂)> HD (R¹=R²=H)> PD (R¹=C₃H₇, R²=H). In the case of MOD /TiO₂/Pt, the apparent quantum yield for photocatalyzed H₂ generation at 436 nm was 0.27±0.03. Transient absorption measurements for MOD ‐ or PD ‐grafted transparent films of TiO₂ nanoparticles dipped into water at pH 3 commonly revealed ultrafast formation (<100 fs) of the dye radical cation (Dye^.+) followed by multicomponent decays, which involve minor fast decays (<5 ps) almost independent of R¹ and major slower decays with significant differences between the two samples: 1) the early decay of the major components for MOD is about 2.5 times slower than that for PD and 2) a redshift of the spectrum occurred for MOD with a time constant of 17 ps, but not for PD . The substituent effects on H₂ generation as well as on transient behavior have been discussed in terms substituent‐dependent charge recombination (CR) of Dye^.+ with electrons in bulk, inner‐trap, and/or interstitial‐trap states, arising from different solvent reorganization.     

3D-QSAR and Docking Studies of Pyrido[2,3-d]pyrimidine Derivatives as Wee1 Inhibitors

In order to investigate the inhibiting mechanism and obtain some helpful information for de-signing functional inhibitors against Wee1, three-dimensional quantitative structure-activity relationship (3D-QSAR) and docking studies have been performed on 45 pyrido[2,3-d] pyrim-idine derivatives acting as Wee1 inhibitors. Two optimal 3D-QSAR models with significant statistical quality and satisfactory predictive ability were established, including the CoMFA model (q²=0.707, R²=0.964) and CoMSIA model (q²=0.645, R²=0.972). The external val-idation indicated that both CoMFA and CoMSIA models were quite robust and had high predictive power with the predictive correlation coefficient values of 0.707 and 0.794, essen-tial parameter r²_m values of 0.792 and 0.826, the leave-one-out r²_m(LOO) values of 0.781 and 0.809, r²_m(overall) values of 0.787 and 0.810, respectively. Moreover, the appropriate binding orientations and conformations of these compounds interacting with Wee1 were revealed by the docking studies. Based on the CoMFA and CoMSIA contour maps and docking analyses, several key structural requirements of these compounds responsible for inhibitory activity were identified as follows: simultaneously introducing high electropositive groups to the sub-stituents R1 and R5 may increase the activity, the substituent R2 should be smaller bulky and higher electronegative, moderate-size and strong electron-withdrawing groups for the substituent R3 is advantageous to the activity, but the substituent X should be medium-size and hydrophilic. These theoretical results help to understand the action mechanism and design novel potential Wee1 inhibitors.     

CoMFA 3D-QSAR Analysis of Epothilones Based on Docking Conformation and Alignment

Epothilones belong to a class of novel microtubule stabilizing and anti-mitotic agents, which have a paclitaxel-like mechanism of action. A three-dimensional quantitative structure-activity relationship （3D-QSAR） model was built for epothilones by the method of comparative molecular field analysis （CoMFA） combined with the flexible docking technology. The docking CoMFA model gave a good cross-validated value of q2=0.784 with an optimized component of 6 and the conventional correlation coefficient of r^2=0.985. The statistical results show that the model has good ability to predict the activity of the studied compounds. At last, the docking CoMFA model was analyzed through contour maps complemented with MOLCAD-generated active site potential surface in the α,β-tubulin receptor, which can provide important information for the structure-based drug design.     

Structure-based CoMFA and CoMSIA study of indolinone inhibitors of PDK1

Phosphoinositide-dependent protein kinase-1 (PDK1) is a Ser/Thr kinase which phosphorylates and activates members of the AGC kinase group known to control processes such as tumor cell growth, protection from apoptosis, and tumor angiogenesis. In this paper, CoMFA and CoMSIA studies were carried out on a training set of 56 conformationally rigid indolinone inhibitors of PDK1. Predictive 3D QSAR models, established using atom fit alignment rule based on crystallographic-bound conformation, had cross-validated (r _cv²) values of 0.738 and 0.816 and non-cross-validated (r _ncv²) values of 0.912 and 0.949 for CoMFA and CoMSIA models, respectively. The predictive ability of the CoMFA and CoMSIA models was determined using a test set of 14 compounds, which gave predictive correlation coefficients (r _pred²) of 0.865 and 0.837, respectively. Structure-based interpretation of the CoMFA and CoMSIA field properties provided further insights for the rational design of new PDK1 inhibitors. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.