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Checkpoint kinase 1 (Chk1) is a promising target for the design of novel anticancer agents. In the present work, molecular docking simulations and three-dimensional quantitative structure–activity relationship (3D-QSAR) studies were performed on pyridyl aminothiazole derivatives as Chk1 inhibitors. AutoDock was used to determine the probable binding conformations of all the compounds inside the active site of Chk1. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models were developed based on the docking conformations and alignments. The CoMFA model produced statistically significant results with a cross-validated correlation coefficient (q2) of 0.608 and a coefficient of determination (r2) of 0.972. The reliable CoMSIA model withq2of 0.662 andr2of 0.970 was obtained from the combination of steric, electrostatic and hydrogen bond acceptor fields. The predictive power of the models were assessed using an external test set of 14 compounds and showed reasonable external predictabilities (r2pred) of 0.668 and 0.641 for CoMFA and CoMSIA models, respectively. The models were further evaluated by leave-ten-out cross-validation, bootstrapping and progressive scrambling analyses. The study provides valuable information about the key structural elements that are required in the rational design of potential drug candidates of this class of Chk1 inhibitors. [ABSTRACT FROM PUBLISHER]

The multidrug resistance protein 1 (MRP1) is involved in multidrug resistance of cancer cells by mediating drug efflux out of cells, often in co-transport with glutathione (GSH). GSH efflux mediated by MRP1 can be stimulated by verapamil. In cells overexpressing MRP1, we have previously shown that verapamil induced a huge intracellular GSH depletion which triggered apoptosis of the cells. That phenomenon takes place in the more global anticancer strategy called "collateral sensitivity" and could be exploited to eradicate some chemoresistant cancer cells. Seeking alternative compounds to verapamil, we screened a library of natural flavonoids and synthetic derivatives. A large number of these compounds stimulate MRP1-mediated GSH efflux and the most active ones have been evaluated for their cytotoxic effect on MRP1-overexpressing cells versus parental cells. Interestingly, some are highly and selectively cytotoxic for MRP1-cells, leading them to apoptosis. However, some others do not exhibit any cytotoxicity while promoting a strong GSH efflux, indicating that GSH efflux is necessary but not sufficient for MRP1-cells apoptosis. In support to this hypothesis, structure activity relationships show that the absence of a hydroxyl group at position 3 of the flavonoid C ring is an absolute requirement for induction of MRP1-cells death, but is not for GSH efflux stimulation. Chrysin (compound 8) and its derivatives, compounds 11 and 22, exhibit a high selectivity toward MRP1-cells with a IC50 value of 4.1μM for compound 11 and 4.9μM for chrysin and compound 22, making them among the best described selective killer compounds of multidrug ABC transporter-overexpressing cells. [ABSTRACT FROM AUTHOR]

Methionine amino peptidases (MetAPs) are metalloproteases that remove co-translational N-terminal methionine from nascent polypeptide chains. Due to their essential role in protein synthesis, MetAPs are considered as potential targets for antibacterial drugs. In the present work, three-dimensional quantitative structure-activity relationship (3D-QSAR) studies were carried out on a series of pyridine-2-carboxylic acid thiazol-2-ylamide-based MetAP inhibitors using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. The models were developed using 30 training set molecules. The optimum CoMFA and CoMSIA models obtained for the training set were statistically significant with cross-validated correlation coefficients ( q) of 0.799 and 0.704 and conventional correlation coefficients ( r) of 0.989 and 0.954, respectively. These inhibitors were docked into MetAP active site. The CoMFA and CoMSIA field contour maps correlate well with the structural characteristics of the binding pocket of MetAP active site. Using the knowledge of structure-activity relationship and receptor-ligand interactions from 3D-QSAR model and the docked complexes, four new pyridine-2-carboxylic acid thiazol-2-ylamide analogs were designed. These analogs exhibit significantly better predicted activity than the reported molecules. The present work has implications for the development of novel antibiotics as potent MetAP inhibitors. [ABSTRACT FROM AUTHOR]

Polychlorinated Dibenzodioxins (PCDDs), Dibenzofurans (PCDFs) and Biphenyls (PCBs) are industrial compounds or byproducts that can cause toxic effects after binding to aryl hydrocarbon receptor (AhR). But the mechanism about PCDDs, PCDFs and PCBs binding to AhR is unclear. To study the interaction and significant amino acid residues in binding of PCDDs, PCDFs and PCBs to AhR, a docking-based Comparative Molecular Similarity Indices Analysis (CoMSIA) was performed on a set of structurally diverse PCDDs, PCDFs and PCBs with known binding affinities. The docking-based CoMSIA model (non-cross-validated regression coefficient of 0.942 and cross-validated regression coefficient of 0.768) was developed and compared with previous report, the presented docking-based CoMSIA model showed good robustness and predictive performance. The obtained docking conformations and predictive CoMSIA model could provide clues to understand key residues and interactions between receptor and compounds of interest. [ABSTRACT FROM AUTHOR]

β-Secretase (beta-amyloid converting enzyme 1 [BACE1]) is involved in the first and rate-limiting step of β- amyloid (Aβ) peptides production, which leads to the pathogenesis of Alzheimer's disease(AD). Therefore, inhibition of BACE1 activity has become an efficient approach for the treatment of AD. Ligand-based and docking-based 3D-quantitative structure-activity relationship (3D-QSAR) studies of acyl guanidine analogues were performed with comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) to obtain insights for designing novel potent BACE1 inhibitors. We obtained highly reliable and predictive CoMSIA models with a cross-validated q² value of 0.725 and a predictive coefficient r²pred value of 0.956. CoMSIA contour maps showed the structural requirements for potent activity. 3D-QSAR analysis suggested that an acyl guanidine and an amide group in the R6 substituent would be important moieties for potent activity. Moreover, the introduction of small hydrophobic groups in the phenyl ring and hydrogen bond donor groups in 3,5-dichlorophenyl ring could increase biological activity. [ABSTRACT FROM AUTHOR]

Three-dimensional quantitative structure–activity relationship (3D-QSAR) analysis were performed on the toxicity of a large set of substituted benzenes toward ciliate Tetrahymena pyriformis. The 3D-QSAR studies were carried out using comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA) and VolSurf techniques. The optimal CoMFA and CoMSIA models obtained from the training set were all statistically significant with correlation coefficients (R 2) greater than 0.79 and absolute error less than 0.33 in log units. The predictive ability of the models was externally evaluated through the prediction of a test set (20 percent of the whole data set) that were not included in the training set. A simple and fairly good predictive linear model based on VolSurf descriptors was also developed that showed an adequate prediction power of the toxicity (pIGC50) of substituted benzenes. Validation, reliability and robustness of models were also evaluated by leave-one-out, leave-four-out, bootstrapping and progressive scrambling approaches. The results confirmed that in addition to hydrophobic effects, electrostatic and H-bonding interactions also play important roles in the toxicity of substituted benzenes. The information obtained from CoMFA and CoMSIA 3-D contour maps could be useful to explain the toxicity mechanism of substituted benzenes. [Copyright &y& Elsevier]

Three-dimensional quantitative structure-activity relationship has been performed on 28 aminopyrazolopyridine ureas derivatives to correlate their chemical structures with their observed VEGFR kinase inhibitory activity. The studies include comparative molecular field analysis (CoMFA), CoMFA region focusing and comparative molecular similarity indices analysis (CoMSIA). An alignment rule for the compounds was defined using Distill in SYBYL. Data set was divided into training and test sets using diversity to validate the models. The constructed CoMFA, CoMFA region-focusing and CoMSIA models produced statistically significant results with the cross-validated correlation coefficients ( q) of 0.858, 0.884, and 0.794, noncross-validated correlation coefficients ( r) of 0.990, 0.991, and 0.930 and predicted correlation coefficients $$(r_{\text{pred}}^{2} )$$ of 0.796, 0.785, and 0.910, respectively. These results ensure the CoMFA and CoMSIA models as a tool to guide the design of series of new potent VEGFR kinase inhibitors. [ABSTRACT FROM AUTHOR]

Isocitrate lyase (ICL) is one of the most important targets in the treatment of Mycobacterium tuberculosis. In this study a diverse set of 2-benzanilide derivatives were aligned by two different methods for CoMFA, CoMSIA, and HQSAR analysis. The best CoMFA model was obtained with the internal validation value ( q) of 0.730 and conventional coefficient ( r) of 0.944. Various CoMSIA models were generated and cross-validated. The best cross-validation coefficient ( q) value was found to be statistically satisfactory (0.688). Both the models were validated by test set of 10 compounds with satisfactory prediction value of ( r) 0.725 and 0.631 for CoMFA and CoMSIA, respectively. Cross-validation coefficient value ( q) of 0.694 and r of 0.856 were obtained for HQSAR study. The docking study reveals that large hydrophobic pockets occupy R substitutions of these compounds. An electronically negative surface is observed near R substitution. The results of the 3D-QSAR analysis corroborate with the molecular docking results, and our findings will serve as a basis for further development of better allosteric inhibitors of ICL inhibitors against M. tuberculosis. [ABSTRACT FROM AUTHOR]

Validated comparative 2D- and 3D-QSAR modeling and docking studies were performed for forty-five quinolone carboxylic acids having cytotoxic, antiviral, and anti-HIV-1 IN activity. Statistically significant 2D-QSAR model was developed through MLR and PLS analyses on unsplitted as well as splitted dataset and validated. The models were validated on external set compounds. Chemical potential, Mulliken charge at C, and ETSA index at C are important for cytotoxicity. Global hardness, electrophilic frontier electron density at C, ETSA index at O, and C play pivotal role for antiviral activity. Mulliken charge at C, ETSA index at C, RTSA index at C, and C and LUMO density on C are important for anti-HIV-1 IN activity. HQSAR study suggested that maximum contributing fragments include C and C and substitutions at C and C for anti-HIV-1 IN activity and antiviral activity, respectively. The positively contributing fragments include C, C, C, C, and C are beneficial for cytotoxicity. CoMFA study suggested that favorable steric region located near C is important for anti-HIV-1 IN activity, steric factor at C substitution is important for antiviral and cytotoxicity activities. CoMSIA study correlates the steric region found in CoMFA study; hydrophobic favorable regions are located around C and near C. For antiviral activity, unfavorable hydrogen bond acceptor region is observed near C substitution, favorable hydrogen bond acceptor region is observed at N substitution. For cytotoxic activity, favorable electrostatic region is located around quinolone and benzene ring. Docking study suggested that Glu152, Gln148, and Asn155 residues of the HIV-1 integrase enzyme bind with the molecule. [ABSTRACT FROM AUTHOR]

Three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis of inhibitory activities for a series of pyrrolotriazine derivatives against histone H3 phosphorylation (pHH3) was performed using comparative of molecular field analysis (CoMFA) and comparative of molecular similarities indices analysis (CoMSIA) techniques. 62 derivatives were used to establish and validate two models by considering a high deviation in biological activities and structural variations. Optimum CoMFA and CoMSIA models obtained from the training set were statistically significant with cross-validated correlation coefficients q of 0.551 and 0.621, and conventional correlation coefficients ( r) of 0.999 and 0.995, respectively. The predicted correlation coefficients of test set ( R) for CoMFA and CoMSIA were 0.835 and 0.918, respectively. Two models obtained provide guidelines to trace the features that really matter chiefly with respect to the design of novel pyrrolotriazine derivatives. [ABSTRACT FROM AUTHOR]

In this study, 3D QSAR (CoMFA and CoMSIA) analysis was performed on 4 H-chromen-1,2,3,4-tetrahydropyrimidine-5-carboxylate derivatives as potential anti-mycobacterial agents. 'Distill' function in SYBYL X 1.2 was used for alignment of the molecules. The best CoMFA and CoMSIA models were obtained for the training set compounds with leave-one-out correlation coefficients ( q) of 0.753 and 0.646, cross validated correlation coefficients ( r) of 0.714 and 0.619, and conventional coefficients ( r) of 0.975 and 0.983, respectively. Both the models were validated by a test set of 8 compounds giving satisfactory prediction ( r) of 0.788 and 0.663 for CoMFA and CoMSIA models, respectively. The results of the study would provide useful information for the design of new compounds and it would also help in prediction of activity of designed compounds prior to their synthesis. [ABSTRACT FROM AUTHOR]

The development of EGFR kinase inhibitors attracts much attention of research for treating of cancer in recent years. In this work, based on a dataset composed of 46 EGFR kinase inhibitors, the combination of three-dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking was applied to reveal structural characteristics impacting the inhibitory activity of EGFR, and to provide a better understanding of the binding modes between inhibitors and EGFR kinase. 3D-QSAR models of pyrazoline derivatives were established to reveal how steric, electrostatic, hydrophobic, and H-bond acceptor interactions contribute to inhibitors' bioactivities, which were unanimous in the docking results. Furthermore, based on the most active compound, several new molecules with high inhibitory activity were obtained. [ABSTRACT FROM AUTHOR]

Mitogen-activated protein kinase-activated protein kinase 2 (MAPKAP-K2) has been identified as a drug target for the treatment of inflammatory diseases. Therefore, there is an urgent need to develop new classes of MAPKAP-K2 inhibitors. To understand the structure activity correlation of MAPKAP-K2 inhibitors, we have carried out a molecular docking study and three-dimensional quantitative structure-activity relationship (3D-QSAR) modeling. Both comparative molecular field analysis ( $$r_{\text{cv}}^{2}$$ = 0.602, $$r_{\text{ncv}}^{2}$$ = 0.955) and comparative molecular similarity indices analysis ( $$r_{\text{cv}}^{2}$$ = 0.546, $$r_{\text{ncv}}^{2}$$ = 0.891) models were generated using the training set on the basis of the common substructure-based alignment and gave reasonable results. The structural insights obtained from both the 3D-QSAR contour maps and molecular docking help to better interpret the structure activity relationship. The results obtained from this study will be useful in the design of potent MAPKAP-K2 inhibitors. [ABSTRACT FROM AUTHOR]

Focal adhesion kinase (FAK) plays a primary role in regulating the activity of many signaling molecules. Increased FAK expression has been implicated in a series of cellular processes, including cell migration and survival. Inhibiting the activity of FAK for cancer therapy is currently under investigation. Hence, FAK and its inhibitors have been the subject of intensive research. To understand the structural factors affecting inhibitory potency, molecular docking and 3D-QSAR modeling were studied in this project. CoMFA and CoMSIA methods were used for deriving 3D-QSAR models, which were trained with 78 compounds and then were evaluated for predictive ability with additional 19 compounds. Two substructure-based 3D-QSAR models, including CoMFA model ( r = 0.930; q = 0.629) and CoMSIA model ( r = 0.952; q = 0.586), had a good quality to predict the biological activities of new compounds. Meanwhile, using the flexible docking strategy, two docking-based 3D-QSAR models (CoMFA with r = 0.914; q = 0.594; CoMSIA with r = 0.914; q = 0.524) were also constructed. The structure-activity relationship has been illustrated clearly by the contour maps gained from the 3D-QSAR models in combination with the docked binding structures. All the results indicated that it might be useful in the rational design of novel FAK inhibitors. [ABSTRACT FROM AUTHOR]

A series of 36 diclofenac analogues were analyzed for structure-activity relationship using CoMFA and CoMSIA. The CoMFA-based equation gave q = 0.625 and r = 0.973 compared to q = 0.773 and r = 0.959 for CoMSIA. The CoMSIA and CoMFA contours were analyzed and the structural features contributing to the enhancement of activity were identified. Based on the results obtained from these analysis two compounds were designed which show enhancement in activity compared to the parent compound. The new leads are predicted to be non-toxic through computational methods. [ABSTRACT FROM AUTHOR]

A series of 42 (pregna-D′-pentarane) steroid ligands was used to generate models predicting ligand affinity to the progesterone receptor. The best result ( Q = 0.91) was obtained using a combination of molecular docking, molecular dynamics simulation and artificial neural networks. Good predictive power of the model was validated using a group of 8 pentaranes synthesized separately and tested in vitro ( R = 0.77). This model can be used for determination of ligand-receptor binding affinity and accurate ranking of binding capacity of compounds tested. [ABSTRACT FROM AUTHOR]

Highlights: [•] We assayed the DPPH-scavenging activity of cucurmin compounds. [•] The quantitative relationships between the structures and their antioxidative activity were studied. [•] Several CoMSIA models are generated for choosing the best one. [•] This study provides useful guide for further development of new antioxidative cucurmin analogues. [ABSTRACT FROM AUTHOR]

Abstract: A series of symmetrical and unsymmetrical 1,4-dihydropyridines were synthesized by a rapid, single pot microwave irradiation (MWI) based protocol along with conventional approach and characterized by NMR, IR and mass spectroscopic techniques. The compounds were evaluated for their tumor cell cytotoxicity in HL-60 tumor cells. A 3D-QSAR study using CoMFA and CoMSIA was carried out to decipher the factors governing MDR reversing ability in cancer. The resulting contour maps derived by the best 3D-QSAR models provide a good insight into the molecular features relevant to the biological activity in this series of analogs. 3D contour maps as a result of 3D-QSAR were utilized to identify some novel features that can be incorporated into the 1,4-dihydropyridine framework to enhance the activity. [Copyright &y& Elsevier]

Molecular modelling studies were performed to identify the essential structural requirements of quinoline-based derivatives for improving their antimalarial activity. The developed CoMFA, CoMSIA and HQSAR models for a training set comprising 37 derivatives showed good statistical significance in terms of internal cross validation (q2) 0.70, 0.69 and 0.80 and non-cross validation (r2) 0.80, 0.79 and 0.80. Also, the predictedr2values (r2pred) of 0.63, 0.61 and 0.72 for a test set consisting of 12 compounds suggested significant predicting ability of the models. Structural features were correlated in terms of steric, electrostatic, hydrophobic, hydrogen bond donor and hydrogen bond acceptor interactions. Furthermore, the bioactive conformation was explored and explained by docking compounds #28, 32 and 40 into the active binding site of lactate dehydrogenase ofPlasmodium falciparum. The QSAR models, contour map and docking binding affinity obtained could be successfully utilized as a guiding tool for the design and discovery of novel quinoline-based derivatives with potent antimalarial activity. [ABSTRACT FROM AUTHOR]

Highlights: [•] PknB is an essential serine/threonine kinase of Mycobacterium tuberculosis. [•] Polar surface area was affecting the cell wall permeability of inhibitors. [•] 3D-QSAR studies were performed on amino-pyrimidine derivatives. [•] Validated models were used in designing potent PknB inhibitors. [•] The docking study reveals the important interactions necessary for PknB inhibitory activity. [Copyright &y& Elsevier]

Highlights: [•] The oxygen radical absorbing capacity (ORAC) of 21 anthocyanins was analysed. [•] The 3D QSAR models were established from 21 anthocyanins. [•] Major anthocyanins in eggplant and red radish were screened using QSAR models. [•] Promising anthocyanins were isolated from eggplants and red radish and validated. [•] Structure criteria of anthocyanins with high ORAC were concluded. [ABSTRACT FROM AUTHOR]

Abstract: The orphan G protein-coupled receptor GPR55 has been proposed as a new potential drug target for the treatment of diabetes, Parkinson's disease, neuropathic pain, and cancer. Coumarin and 8-amido-chromen-4-one-2-carboxylic acid derivatives were identified as novel antagonists for GPR55. In this study, we established reliable models and explored the valuable information by quantitative structure–activity relationship (QSAR). Firstly, we obtained a quite reliable multiple linear regression (MLR) model with correlation coefficient (R 2) of 0.8204 for the training set, and R 2 of 0.7770 for the test set. Next, we built a better model with R 2 of 0.8763 for the training set, and R 2 of 0.8179 for the test set based on the simplified molecular input line entry system (SMILES). Lastly, we established dependable comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models. Then we validated these models' predictive ability using various validation methods for the test set. Besides, we designed and confirmed six new potential inhibitors with higher predicted activities and tested twenty-eight compounds without clear activities by the established models. The results obtained from molecular modeling not only provide models to predict the activities of inhibitors but also lead to a better understanding of the essential features that should be considered when designing novel inhibitors with desired activities. [Copyright &y& Elsevier]

In this study we designed novel substituted benzimidazole derivatives and predicted their absorption, distribution, metabolism, excretion and toxicity (ADMET) properties, based on a predictive 3D QSAR study on 132 substituted benzimidazoles as AngII–AT1receptor antagonists. The two best predicted compounds were synthesized and evaluated for AngII–AT1receptor antagonism. Three different alignment tools for comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were used. The best 3D QSAR models were obtained using the rigid body (Distill) alignment method. CoMFA and CoMSIA models were found to be statistically significant with leave-one-out correlation coefficients (q2) of 0.630 and 0.623, respectively, cross-validated coefficients (r2cv) of 0.651 and 0.630, respectively, and conventional coefficients of determination (r2) of 0.848 and 0.843, respectively. 3D QSAR models were validated using a test set of 24 compounds, giving satisfactory predicted results (r2pred) of 0.727 and 0.689 for the CoMFA and CoMSIA models, respectively. We have identified some key features in substituted benzimidazole derivatives, such as lipophilicity and H-bonding at the 2- and 5-positions of the benzimidazole nucleus, respectively, for AT1receptor antagonistic activity. We designed 20 novel substituted benzimidazole derivatives and predicted their activity.In silicoADMET properties were also predicted for these designed molecules. Finally, the compounds with best predicted activity were synthesized and evaluated forin vitroangiotensin II–AT1receptor antagonism. [ABSTRACT FROM AUTHOR]

Three-dimensional quantitative structure-activity relationships were performed for a series of isatin derivatives as anti-cancer agents using the CoMFA and CoMSIA methods. Statistically significant CoMFA ( $$r_{\text{cv}}^{2} = 0.869,\;r_{\text{ncv}}^{2} = 0.962$$ ) and CoMSIA ( $$r_{\text{cv}}^{2} = 0.865,\;r_{\text{ncv}}^{2} = 0.959$$ ) models were generated using the training set on the basis of the common substructure-based alignment. Further, the predictive ability of the CoMFA and CoMSIA models was determined using a test set of nine compounds. Based on the information derived from CoMFA and CoMSIA contour maps, we have identified some key features for increasing the activity of compounds and have been used to design new anti-cancer agents. The newly designed molecules in this series of compounds may be more potent anti-cancer agents. [ABSTRACT FROM AUTHOR]

BRAF have been identified as new promising targets for the design of novel anticancer agents. It is reported that the inhibitors based on 2,3-dihydroimidazo[4,5]pyridin-2-one scaffold and a meta-substituted middle ring exhibit potent inhibitory activities toward BRAF. To investigate how their chemical structures relate to the inhibitory activities and to identify the key structural elements that are required in the rational design of potential drug candidates of this class, molecular docking simulations and three-dimensional quantitative structure-activity relationship (3D-QSAR) methods were performed. The bioactive conformation was explored by docking one potent compound 1 into the active site of BRAF in its DFG-out inactive conformation. The constructed CoMFA and CoMSIA models produced statistically significant results with the cross-validated correlation coefficients q of 0.563 and 0.624, non-cross-validated correlation coefficients r of 0.982 and 0.962, and predicted correction coefficients r of 0.822 and 0.875, respectively. In addition, the CoMFA and CoMSIA models were used to guide the design of a series of new inhibitors of this class with predicted excellent activities. Thus, these models may be used as an efficient tool to predict the inhibitory activities and to guide the future rational design of 2,3-dihydroimidazo[4,5]pyridin-2-one derivatives with a meta substitution pattern as BRAF inhibitors with potent activities. [ABSTRACT FROM AUTHOR]

The metal-chelating activity of a series of 48 chromone compounds, evaluated by ferrous (Fe) chelating test, were subjected to 3D-QSAR studies using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The best CoMFA model obtained from HF/6-31G* geometry optimization and field fit alignment gave cross-validated r ( q) = 0.582, non-cross-validated r = 0.975. The best CoMSIA model gave q = 0.617, non-cross-validated r = 0.917. The resulted CoMFA and CoMSIA contour maps proposed the Fe-chelating sites of chromone compounds compared with those of quercetin. [ABSTRACT FROM AUTHOR]

Anaplastic lymphoma kinase (ALK) is involved in many signaling mechanisms that lead to cell-cycle progression; overexpression of ALK has been found in many types of cancers. ALK is a recognized target for the development of small-molecule inhibitors for the treatment of cancer. In this study, a diverse set of 71 ALK inhibitors were aligned by three different methods (pharmacophore, docking-based, and rigid body (Distill) alignment) for the development of comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models. The best 3D QSAR models were obtained, which used rigid body (Distill) alignment of test and training set molecules. CoMFA and CoMSIA models were found statistically significant with leave-one-out correlation coefficients ( q) of 0.816 and 0.838, respectively; cross-validated coefficients ( $$r_{\text{cv}}^{2}$$ ) of 0.812 and 0.837, respectively; and conventional coefficients ( r) of 0.969 and 0.966, respectively. QSAR models were validated by a test set of 14 compounds giving satisfactory prediction of correlation coefficients ( $$r_{\text{pred}}^{2}$$ ) of 0.910 and 0.904 for CoMFA and CoMSIA models, respectively. Based on the generated contour maps, we have designed 10 novel ALK inhibitors and predicted their activities. Finally, molecular docking study was performed for designed molecules. The designed compounds showed good potential to be used as ALK inhibitors. [ABSTRACT FROM AUTHOR]

The 3D-QSAR analysis was performed on the set of 175 potent inhibitors of the PDE10A enzyme. Four separate models were built based on different conformations and superimposition methods. They were generated following next criteria: (I) database alignment based on the conformations most similar to the co-crystalized ligand conformation, (II) database alignment based on the minimum energy conformations, (III) docking alignment based on the docked conformations, and (IV) database alignment based on the docking conformations. The best CoMFA and CoMSIA models, derived from superimposition III, show leave-one-out cross-validated correlation coefficient ( q) values of 0.673 and 0.707 as well as the non-cross-validated correlation coefficient ( r) values of 0.936 and 0.924, respectively. In addition, the satisfactory results, based on the bootstrapping analysis and 10- and 50-fold cross-validation, further indicate the highly statistical significance of the models. The external predictive abilities of these models were evaluated using a prediction set of 35 compounds, producing the predicted correlation coefficients. Results were graphically interpreted in terms of field contribution maps. A DISCOtech pharmacophore model was also constructed to light important structural features that could be responsible for the low- or high-inhibition activity. [ABSTRACT FROM AUTHOR]

Abstract: Three-dimensional quantitative structure–activity relationship (3D-QSAR) modeling, comparative molecular field analysis (CoMFA), and comparative molecular similarity indices analysis (CoMSIA) of polyhydroxylated N-benzylbenzamide derivatives containing an adamantyl moiety were performed to understand the mechanism of action and structure–activity relationship of these compounds. Contour map analysis indicated that steric contributions of the adamantyl moiety and electrostatic contributions of the hydroxyl group at the 3-position are important in the activity. Activities of the training set and test sets predicted by CoMFA fit well with actual activities, demonstrating that CoMFA, along with the best calculated q 2 value, has the best predictive ability. [Copyright &y& Elsevier]

Abstract: In order to develop a lead antimycobacterium tuberculosis compound, a series of 52, novel pyrrole hydrazine derivatives have been synthesized and screened which target the essential enoyl-ACP reductase. The binding mode of the compounds at the active site of enoyl-ACP reductase was explored using surflex-docking method. The binding model suggests one or two hydrogen bonding interactions between pyrrole hydrazones and InhA enzyme. Highly active compound 5r (MIC 0.2 μg/mL) showed hydrogen bonding interactions with Tyr158 and NAD+ in the same manner as those of ligands PT70 and triclosan. The CoMFA and CoMSIA models generated with database alignment were the best in terms of overall statistics. The predictive ability of the CoMFA and CoMSIA models was determined using a test set of 13 compounds, which gave predictive correlation coefficients (r pred 2) of 0.896 and 0.930, respectively. [Copyright &y& Elsevier]

Molecular modelling studies [comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), topomer CoMFA and hologram quantitative structure-activity relationship (HQSAR)] have been performed on the series of 28 molecules belonging to the series of aromatic acid ester derivatives for their carbonic anhydrase inhibitory activity. The model exhibited good correlation coefficient ( r2) and cross-validated correlation coefficient ( q2) for CoMFA, CoMSIA and HQSAR methods. On the basis of the findings from all these studies, a structure-activity relationship was established. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Three-dimensional quantitative structure activity relationships (3D-QSAR) methods of comparative molecular field analysis (CoMFA), CoMFA region focusing (CoMFA-RF), and comparative molecular similarity indices analysis (CoMSIA) were successfully employed to predict and model of the separation factors of N-donor heterocyclic extractants in the separation of americium(III) from europium(III) ions from acidic aqueous solutions. An all-orientation search (AOS) strategy was used to acquire the best orientation and minimize the effect of the initial orientation of aligned compounds. The obtained 3D-QSAR models showed R2> 0.97 and an absolute error of > 0.1 in log unit of the separation factors. Validation, reliability, and robustness of 3D-QSAR models were evaluated by the prediction of external test sets, leave-one-out, leave-four-out, bootstrapping, and progressive scrambling approaches. The results confirmed that steric hindrance and electrostatic interactions besides hydrophobic effects of N-donor extractants play an important role in Am(III)/Eu(III) separation processes. The obtained information could be very useful in designing the most efficient ligands and finding new extractants for lanthanide and actinide separation. [ABSTRACT FROM PUBLISHER]

Highlights: [•] We developed CoMFA, CoMSIA models for a series of 53 3-Pyridine heterocyclic derivatives. [•] Molecular docking method was used to analyses possible interactions between receptors and the compounds. [•] The results of models based ligand alignment and receptor alignment support each other. [•] Ten derivatives as potential candidates of PI3K/mTOR inhibitors with good predicted activities were designed. [Copyright &y& Elsevier]

Abstract: 3,6-Diaryl-dihydro-1,2,4,5-tetrazine derivatives were synthesized and their structures were confirmed by single-crystal X-ray diffraction. Monosubstituted dihydrotetrazines are the 1,4-dihydro structure, but disubstituted dihydrotetrazines are the 1,2-dihydro structure. The results of further research indicated there may be a rearrangement during the synthesis process of disubstituted dihydrotetrazines. Their antitumor activities were evaluated against A-549 and P388 cells in vitro. The results showed several compounds to be endowed with cytotoxicity in the low micromolar range. Two compounds were highly effective against A-549 cell and IC50 values were 0.575 and 2.08μM, respectively. Three-dimensional quantitative structure–activity relationship (3D-QSAR) studies of comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were carried out on 37 1,2,4,5-tetrazine derivatives with antitumor activity against A-549 cell. Models with good predictive abilities were generated with the cross validated q 2 values for CoMFA and CoMSIA being 0.744 and 0.757, respectively. Conventional r 2 values were 0.978 and 0.988, respectively, the predicted R 2 values were 0.916 and 0.898, respectively. The results provide the tool for guiding the design and synthesis of novel and more potent tetrazine derivatives. [Copyright &y& Elsevier]

Chloroquine resistance is nowadays a great problem in malaria. Aurone derivatives were effective against chloroquine resistant parasite. Validated density functional theory (DFT)-based chemometric modeling, hologram QSAR (HQSAR), comparative molecular field analysis (CoMFA), and comparative molecular similarity analysis (CoMSIA) studies were conducted on 35 aurone derivatives having antimalarial activity. 2D-QSAR models were developed on the training sets by Y-based ranking method. This model was validated on 50 pairs of the test and the training sets by k-Means cluster analysis method. HQSAR, CoMFA, and CoMSIA models were validated by standard techniques and each method validates the DFT-based 2D-QSAR study and in turn validates the earlier observed structural activity relationship data as well as each other. DFT-based 2D-QSAR model suggests that the increase of Mulliken charge at C and HOMO density located on C may be conducive to antimalarial activity. Ethyl group attached to C and the increase of the value of chemical potential may be beneficial for antimalarial activity. Methoxy fragment is important for better antimalarial activity by HQSAR study. CoMFA analysis shows a favorable steric green region is located near C whereas the unfavorable yellow region is far away from C. A large blue region located near C indicates the positively charged groups are favorable at this position. CoMSIA steric features correlates well with the CoMFA steric features. CoMSIA study suggests the bulky hydrophobic substitution at C is necessary for antimalarial activity. These results may be utilized to obtain potential antimalarial molecules. [ABSTRACT FROM AUTHOR]

3D-QSAR modeling of juvenile hormone (JH) mimetic compounds of Culex pipiens ( C. pipiens) larvae were analyzed. Comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) were chosen for 3D-QSAR studies. These compounds act as potential insect control agents. The dataset containing 143 JH mimetic compounds considered in this study were divided into a training set of 129 compounds and a test set of 14 compounds. The CoMFA/CoMSIA model is obtained with the statistical significance r of 0.944 (0.773) with standard error of estimate of 0.313 (0.616). Both CoMFA and CoMSIA models provide valuable insight into the structural requirements for the enhanced activity of the JH inhibitors. [ABSTRACT FROM AUTHOR]

Highlights: [•] Via 3D-QSAR modeling and molecular docking. [•] We investigated main factors influencing activity of non-purine xanthine oxidase inhibitors. [•] Several new potential inhibitors with higher activity were designed. [•] The new designed inhibitors are based on our analyses and supported by the molecular docking. [•] This study provided useful information for the development of inhibitors with novel structures. [ABSTRACT FROM AUTHOR]

A series of sulfone derivatives containing 1, 3, 4-oxadiazole moiety were prepared and evaluated for their antibacterial activities by the turbidimeter test. Most compounds inhibited growth of Ralstonia solanacearum ( R. solanacearum) from tomato and tobacco bacterial wilt with high potency, among which compounds 5a and 5b exhibited the most potent inhibition against R. solanacearum from tomato and tobacco bacterial wilts with EC50 values of 19.77 and 8.29 μg/mL, respectively. Our results also demonstrated that 5a, 5b, and a number of other compounds were more potent than commercial bactericides Kocide 3000 and Thiodiazole Copper, which inhibited R. solanacearum from tomato bacterial wilt with EC50 values of 93.59 and 99.80 μg/mL and tobacco bacterial wilt with EC50 values of 45.91 and 216.70 μg/mL, respectively. The structure-activity relationship (SAR) of compounds was studied using three-dimensional quantitative structure-activity relationship (3 D- QSAR) models created by comparative molecular field analysis ( Co MFA) and comparative molecular similarity index analysis ( Co MSIA) based on compound bioactivities against tomato and tobacco bacterial wilts. The 3 D- QSAR models effectively predicted the correlation between inhibitory activity and steric-electrostatic properties of compounds. [ABSTRACT FROM AUTHOR]

Flavonoids are a class of phenolic and polyphenolic compounds widely distributed in vegetables, fruits, grains and herbs. Organic cation transporter 2 (OCT2) mediates the renal secretion of organic cations and is a key site of drug-drug interactions (DDIs). In this study, we systematically investigated the inhibitory effect of 28 flavonoids on OCT2-mediated uptake of 4-4-dimethylaminostyryl-N-methylpyridinium (ASP + ). Among them, scullcapflavone II demonstrated the strongest inhibitory effect on OCT2-mediated uptake of ASP + (IC 50 =11.2 μM) in a competitive manner. Next, 3D-QSAR analyses of flavonoid OCT2 inhibitors were performed using both CoMFA and CoMSIA models. The date revealed that bulky substituents at the C-3 and C-4 positions of ring C as well as the C-7 position of ring A could prevent the interactions of flavonoids with OCT2. In contrast, a hydrophilic and negatively charge substituent on ring A was favorable for the interactions of flavonoids with OCT2. Consequently, baicalin (IC 50 =220.2 μM) with a uronic acid substituent on ring A exhibited a stronger inhibition than baicalein (IC 50 =294.5 μM); quercetin-3-O-galactoside (IC 50 =497.4 μM) was a stronger inhibitor of OCT2 than rhamnetin 3-galactoside (IC 50 =1409.0 μM). Taken together, our findings could be valuable in elucidating and predicting the interactions of flavonoids with OCT2., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Hydroxylated polychlorinated biphenyls (HO-PCBs), as the major metabolites of PCBs, have been reported to act as estrogen receptor β (ERβ) agonists. However, the chemical-biological interactions governing their activities toward ERβ have not been elucidated. Therefore, three dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking and molecular dynamics (MD) simulations, to the best of our knowledge, for the first time were performed to explore the correlation between the structures and activities. The best 3D-QSAR model presented higher predictive ability ( R 2 cv =0.543, R =0.6795) based on comparative molecular field analysis (CoMFA) and comparative similarity indices analysis (CoMSIA), respectively. At the same time, the derived contour maps indicated the important structural features required for improving the activity. Furthermore, molecular docking studies and MD simulations predicted the binding mode and the interactions between the ligand and the receptor. All the results would lead to a better understanding of the specific mechanism of HO-PCBs on estrogen receptor β (ERβ).Communicated by Ramaswamy H. Sarma.2 pred =0.5793/ R 2 cv =0.543, R 2 pred =0.6795) based on comparative molecular field analysis (CoMFA) and comparative similarity indices analysis (CoMSIA), respectively. At the same time, the derived contour maps indicated the important structural features required for improving the activity. Furthermore, molecular docking studies and MD simulations predicted the binding mode and the interactions between the ligand and the receptor. All the results would lead to a better understanding of the specific mechanism of HO-PCBs on estrogen receptor β (ERβ).Communicated by Ramaswamy H. Sarma.

Background: JAK2 inhibitors have been proposed as a new therapeutic option for thalassemia therapy. The objective of this study was to discover the key structural features for improving 2-aminopyrimidine derivatives as potential JAK2 inhibitors. Materials & methods: Quantitative structure-activity relationship (QSAR) approaches (hologram QSAR and comparative molecular similarity indices analysis), molecular dynamics simulations, binding energy calculations and pharmacokinetic predictions were employed. Results: Reliable QSAR models, binding mode and binding interactions of JAK2 inhibitors were obtained and these obtained results were used as the key information for rational design of highly potent JAK2 inhibitors. Conclusion: The concept of new potential JAK2 inhibitors integrated from the obtained results was proved, producing two newly designed compounds, D01 and D02, with potential for use as JAK2 inhibitors.

• Constructed a reliable 3D-QSAR model of Thiazole derivatives. • Design of five thiazole compounds as new inhibitors of PIN1 with high predicted activities. • Molecular docking, molecular dynamics and MM/GBSA calculations were used for studying the interactions. For three systems, the most active compound, the control compound, and a newly designed compound. • ADMET study indicated that these compounds had a good predictive activity. Due to the role of enzyme PIN1 in cancer cells, PIN1 is a promising therapeutic target. The study of the mechanism between PIN1 and thiazole inhibitors was carried out operating 3D-QSAR modeling, molecular docking, molecular dynamics simulations, in order to design high activity inhibitors. The optimal CoMSIA / SH model showed good reliability and satisfactory predictability Q2 = 0.717, R2 = 0.961, R2 pred = 0.740. The predictability and precision of the generated model were assessed by the criteria of Golbraikh and Tropsha. The CoMSIA model with a contribution from steric and hydrophobic fields (CoMSIA/SH) passes all these validation protocols successfully, therefore the established model is reliable. The analysis of Contour map analysis may provide structural information to improve inhibitory function. Furthermore, molecular docking and MD simulations show stability and provide information on ligand-receptor interactions. The results served as the basis for developing new compounds and their expected inhibitory activities. The result of the physicochemical and ADMET / pharmacokinetic properties showed that these five proposed molecules are bioavailable by the oral route, high gastrointestinal absorption, good permeability and therefore do not inhibit CYP3A4 and CYP2D6. In addition, nontoxic to the Ames test and therefore these results would provide the necessary physicochemical and pharmacokinetic properties and relevant information in the analysis drug discovery [ABSTRACT FROM AUTHOR]

• 3D-QSAR studies on 37 reported 2-phenylquinazolin-4-one derivatives was performed. • CoMFA, CoMSIA, topomer CoMFA and HQSAR techniques were used to generate the QSAR models. • Statistical results and contour maps of each QSAR model were analyzed and interpreted. • Critical ligand substitutions required for the design of novel potent tankyrase inhibitors were summarized. Tankyrase is an emerging target of 17 membered poly(ADP-ribose)polymerase enzyme family for the treatment of Wnt driven cancers. TNKS are associated with many cellular functions; Wnt–β-catenin signaling, telomere homeostasis, mitotic spindle formation etc. The inhibition of cell growth could be achieved by the inhibition of TNKS through Wnt-signaling mechanism. To develop novel lead molecules as tankyrase inhibitors, we performed 3D-QSAR studies on 37 reported 2-phenylquinazolin-4-one derivatives. Training set contained 29 while test set contained 8 molecules. Four different techniques, CoMFA, CoMSIA, Topomer CoMFA and HQSAR were used to generate the QSAR models. Distill alignment based CoMFA analysis showed q2 value of 0.605, r2 ncv value of 0.958 and r2 pred value of 0.553. Optimized CoMSIA analysis (SEHD) showed q2 value of 0.580, r2 ncv value of 0.953 and r2 pred value of 0.723. Topomer CoMFA analysis showed q2 value of 0.684, r2 (conventional correlation coefficient) value of 0.955 and r2 pred value of 0.721. HQSAR analysis showed q2, r2 and r2 pred values of 0.833, 0.951 and 0.753, respectively. Combined results of all studies provided significant output in terms of substitutions required for activity and can be used for the design of novel quinazolinone derivatives as potent tankyrase inhibitors. [Display omitted] [ABSTRACT FROM AUTHOR]