Studies of 3D-quantitative structure-activity relationships on a set of nitroaromatic compounds: CoMFA, advanced CoMFA and CoMSIA

Employing comparative QSAR techniques for the recognition of dibenzofuran and dibenzothiophene derivatives toward MMP-12 inhibition

Among various matrix metalloproteinases (MMPs), MMP-12 is one of the potential targets for cancer and other diseases. However, none of the MMP-12 inhibitors has passed the clinical trials to date. Therefore, designing potential MMP-12 inhibitors as new drug molecules can provide effective therapeutic strategies for several diseases. In this study, a series of dibenzofuran and dibenzothiophene derivatives were subjected to different 2D and 3D-QSAR techniques to point out the crucial structural contributions highly influential toward the MMP-12 inhibitory activity. These techniques identified some structural attributes of these compounds that are responsible for influencing their MMP-12 inhibition. The carboxylic group may enhance proper binding with catalytic Zn2+ ion at the MMP-12 active site. Again, the i-propyl sulfonamido carboxylic acid function contributed positively toward MMP-12 inhibition. Moreover, the dibenzofuran moiety conferred stable binding at the S1' pocket for higher MMP-12 inhibition. The steric and hydrophobic groups were found favourable near the furan ring substituted at the dibenzofuran moiety. Besides these ligand-based approaches, molecular docking and molecular dynamic (MD) simulation studies not only elucidated the importance of several aspects of these MMP-12 inhibitors while disclosing the significance of the finding of these QSAR studies and their influences toward MMP-12 inhibition. The MD simulation study also revealed stable and compact binding between such compounds at the MMP-12 active site. Therefore, the findings of these validated ligand-based and structure-based molecular modeling studies can aid the development of selective and potent lead molecules that can be used for the treatment of MMP-12-associated diseases.Communicated by Ramaswamy H. Sarma.

Clustering of atoms relative to vector space in the Z-matrix coordinate system and 'graphical fingerprint' analysis of 3D pharmacophore structure

The behavior of a molecule within its environment is governed by chemical fields present in 3D space. However, beyond local descriptors in 3D, the conformations a molecule assumes, and the resulting clusters also play a role in influencing structure-activity models. This study focuses on the clustering of atoms according to the vector space of four atoms aligned in the Z-Matrix Reference system for molecular similarity. Using 3D-QSAR analysis, it was aimed to determine the pharmacophore groups as interaction points in the binding region of the β2-adrenoceptor target of fenoterol stereoisomers. Different types of local reactive descriptors of ligands have been used to elucidate points of interaction with the target. Activity values for ligand-receptor interaction energy were determined using the Levenberg-Marquardt algorithm. Using the Molecular Comparative Electron Topology method, the 3D pharmacophore model (3D-PhaM) was obtained after aligning and superimposing the molecules and was further validated by the molecular docking method. Best guesses were calculated with a non-output validation (LOO-CV) method. Finally, the data were calculated using the 'graphic fingerprint' technique. Based on the eLKlopman (Electrostatic LUMO Klopman) descriptor, the Q2 value of this derivative set was calculated as 0.981 and the R2ext value is calculated as 0.998.

Prediction of octanol-air partition coefficients for polychlorinated biphenyls (PCBs) using 3D-QSAR models

Based on the experimental data of octanol-air partition coefficients (KOA) for 19 polychlorinated biphenyl (PCB) congeners, two types of QSAR methods, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA), are used to establish 3D-QSAR models using the structural parameters as independent variables and using logKOA values as the dependent variable with the Sybyl software to predict the KOA values of the remaining 190 PCB congeners. The whole data set (19 compounds) was divided into a training set (15 compounds) for model generation and a test set (4 compounds) for model validation. As a result, the cross-validation correlation coefficient (q(2)) obtained by the CoMFA and CoMSIA models (shuffled 12 times) was in the range of 0.825-0.969 (>0.5), the correlation coefficient (r(2)) obtained was in the range of 0.957-1.000 (>0.9), and the SEP (standard error of prediction) of test set was within the range of 0.070-0.617, indicating that the models were robust and predictive. Randomly selected from a set of models, CoMFA analysis revealed that the corresponding percentages of the variance explained by steric and electrostatic fields were 23.9% and 76.1%, respectively, while CoMSIA analysis by steric, electrostatic and hydrophobic fields were 0.6%, 92.6%, and 6.8%, respectively. The electrostatic field was determined as a primary factor governing the logKOA. The correlation analysis of the relationship between the number of Cl atoms and the average logKOA values of PCBs indicated that logKOA values gradually increased as the number of Cl atoms increased. Simultaneously, related studies on PCB detection in the Arctic and Antarctic areas revealed that higher logKOA values indicate a stronger PCB migration ability. From CoMFA and CoMSIA contour maps, logKOA decreased when substituents possessed electropositive groups at the 2-, 3-, 3'-, 5- and 6- positions, which could reduce the PCB migration ability. These results are expected to be beneficial in predicting logKOA values of PCB homologues and derivatives and in providing a theoretical foundation for further elucidation of the global migration behaviour of PCBs.

An in silico exploration of the interaction mechanism of pyrazolo[1,5-a]pyrimidine type CDK2 inhibitors

CDK2, which interacts with cyclin A and cyclin E, is an important member of the CDK family. Having been proved to be associated with many diseases for its vital role in cell cycle, CDK2 is a promising target of anti-cancer drugs dealing with cell cycle disorders. In the present work, a total of 111 pyrazolo[1,5-a]pyrimidines (PHTPPs) as CDK2/cyclin A inhibitors were studied to conduct three-dimensional quantitative structure-activity (3D-QSAR) analyses. The optimal comparative molecular similarity indices analysis (CoMSIA) model shows that Q(2) = 0.516, Rncv(2) = 0.912, Rpre(2) = 0.914, Rm(2) = 0.843, SEP = 0.812, SEE = 0.347 with 10 components using steric, hydrophobic and H-bond donor field descriptors, indicating its effective internal and external predictive capacity. The contour maps further indicate that (1) bulky substituents in R1 are beneficial while H-bond donor groups at this position are detrimental; (2) hydrophobic contributions in the R2 area are favorable; (3) large and hydrophilic groups are well tolerated at the R3 position (a close H-bond donor moiety is favorable while a distal H-bond donor moiety in this area is disfavored); (4) bulky and hydrophobic features in the R4 region are beneficial for the biological activities and (5) the 7-N-aryl substitution is crucial to boost the inhibitory activities of the PHTPP inhibitors. Finally, docking and MD simulations demostrate that PHTPP derivatives are stabilized in a 'flying bat' conformation mainly through the H-bond interactions and hydrophobic contacts. Comparative studies indicate that PHTPP derivatives fit well within the ATP binding cleft in CDK2, with the core heterocyclic ring overlapping significantly with the adenine group of ATP despite a small deflection. In comparison to numerous other inhibitors binding to the ATP pocket, PHTPP analogues follow the binding fashion of purine inhibitors of this kinase. It is anticipated that the binding mechanism and structural features of PHTPP inhibitors studied in the present work will benefit the discovery of more potent CDK2 inhibitors, and the valid pyrazolo[1,5-a]pyrimidine-7-N-yl inhibitors will soon emerge from the large number of screening programmes to enter in clinical studies.

Genotoxicity of quinolones: substituents contribution and transformation products QSAR evaluation using 2D and 3D models

The genotoxicity of 21 quinolones antibiotics was determined using SOS/umu assay. Some quinolones exhibited high genotoxicity, and the chemical substituent on quinolone ring significantly affected genotoxicity. To establish the relationship between genotoxicity and substituent, a 2D-QSAR model based on quantum chemical parameters was developed. Calculation suggested that both steric and electrostatic properties were correlated well with genotoxicity. Furthermore, the specific effect on three key active sites (1-, 7- and 8-positions) of quinolone ring was investigated using a 3D-QSAR (comparative molecular field analysis, CoMFA) method. From our modeling, the genotoxicity increased when substituents had: (1) big volume and/or positive charge at 1-position; (2) negative charge at 7-position; and (3) small volume and/or negative charge at 8-position. The developed QSAR models were applicable to estimate genotoxicity of quinolones antibiotics and their transformation products. It is noted that some of the transformation products exhibited higher genotoxicity comparing to their precursor (e.g., ciprofloxacin). This study provided an alternative way to understand the molecule genotoxicity of quinolones derivatives, as well as to evaluate their potential environmental risks.

Substituent contribution to the genotoxicity of benzophenone-type UV filters

Benzophenones (BPs) are widely used in UV filters, fragrance enhancers, and plastic additives. In this study, the genotoxicity of 14 BPs was tested using the SOS/umu assay, and the related substituent contribution was disclosed. The results of this study revealed that the major contributor to the genotoxicity of the BPs was the ortho,para-di-substitution, and the increasing hydroxy substitution on the benzene ring. In addition, the higher the dispersion of the substituent species on the two benzene rings, the lower the genotoxicity exhibited by the compound. Furthermore, 2 dimensional and 3 dimenional quantitative structure-activity relationships (2D- and 3D-QSAR) studies indicated that hydrogen-bond interactions and electrostatic effects were determinants for the genotoxicity of the BPs. The current results provide useful information for the assessment of the potential ecological risk and health effects of BP-type UV filters.

Accurate prediction of the toxicity of benzoic acid compounds in mice via oral without using any computer codes

Most of benzoic acid derivatives are toxic, which may cause serious public health and environmental problems. Two novel simple and reliable models are introduced for desk calculations of the toxicity of benzoic acid compounds in mice via oral LD(50) with more reliance on their answers as one could attach to the more complex outputs. They require only elemental composition and molecular fragments without using any computer codes. The first model is based on only the number of carbon and hydrogen atoms, which can be improved by several molecular fragments in the second model. For 57 benzoic compounds, where the computed results of quantitative structure-toxicity relationship (QSTR) were recently reported, the predicted results of two simple models of present method are more reliable than QSTR computations. The present simple method is also tested with further 324 benzoic acid compounds including complex molecular structures, which confirm good forecasting ability of the second model.

Caco-2 cells cytotoxicity of nifuroxazide derivatives with potential activity against Methicillin-resistant Staphylococcus aureus (MRSA)

It is important to determine the toxicity of compounds and co-solvents that are used in cell monolayer permeability studies to increase confidence in the results obtained from these in vitro experiments. This study was designed to evaluate the cytotoxicity of new nifuroxazide derivatives with potential activity against Methicillin-resistant Staphylococcus aureus (MRSA) in Caco-2 cells to select analogues for further in vitro permeability analyses. In this study, nitrofurantoin and nifuroxazide, in addition to 6 furanic and 6 thiophenic nifuroxazide derivatives were tested at 2, 4, 6, 8 and 10 μg/mL. In vitro cytotoxicity assays were performed according to the MTT (methyl tetrazolium) assay protocol described in ISO 10993-5. The viability of treated Caco-2 cells was greater than 83% for all tested nitrofurantoin concentrations, while those treated with nifuroxazide at 2, 4 and 6 μg/mL had viabilities greater than 70%. Treatment with the nifuroxazide analogues resulted in viability values greater than 70% at 2 and 4 μg/mL with the exception of the thiophenic methyl-substituted derivative, which resulted in cell viabilities below 70% at all tested concentrations. Caco-2 cells demonstrated reasonable viability for all nifuroxazide derivatives, except the thiophenic methyl-substituted compound. The former were selected for further permeability studies using Caco-2 cells.

Investigation on quantitative structure activity relationships and pharmacophore modeling of a series of mGluR2 antagonists

MGluR2 is G protein-coupled receptor that is targeted for diseases like anxiety, depression, Parkinson’s disease and schizophrenia. Herein, we report the three-dimensional quantitative structure–activity relationship (3D-QSAR) studies of a series of 1,3-dihydrobenzo[ b][1,4]diazepin-2-one derivatives as mGluR2 antagonists. Two series of models using two different activities of the antagonists against rat mGluR2, which has been shown to be very similar to the human mGluR2, (activity I: inhibition of [³H]-LY354740; activity II: mGluR2 (1S,3R)-ACPD inhibition of forskolin stimulated cAMP.) were derived from datasets composed of 137 and 69 molecules respectively. For activity I study, the best predictive model obtained from CoMFA analysis yielded a Q² of 0.513, R²_ncv of 0.868, R²_pred = 0.876, while the CoMSIA model yielded a Q² of 0.450, R²_ncv = 0.899, R²_pred = 0.735. For activity II study, CoMFA model yielded statistics of Q² = 0.5, R²_ncv = 0.715, R²_pred = 0.723. These results prove the high predictability of the models. Furthermore, a combined analysis between the CoMFA, CoMSIA contour maps shows that: (1) Bulky substituents in R₇, R₃ and position A benefit activity I of the antagonists, but decrease it when projected in R₈ and position B; (2) Hydrophilic groups at position A and B increase both antagonistic activity I and II; (3) Electrostatic field plays an essential rule in the variance of activity II. In search for more potent mGluR2 antagonists, two pharmacophore models were developed separately for the two activities. The first model reveals six pharmacophoric features, namely an aromatic center, two hydrophobic centers, an H-donor atom, an H-acceptor atom and an H-donor site. The second model shares all features of the first one and has an additional acceptor site, a positive N and an aromatic center. These models can be used as guidance for the development of new mGluR2 antagonists of high activity and selectivity. This work is the first report on 3D-QSAR modeling of these mGluR2 antagonists. All the conclusions may lead to a better understanding of the mechanism of antagonism and be helpful in the design of new potent mGluR2 antagonists.

Studies of H4R antagonists using 3D-QSAR, molecular docking and molecular dynamics

Three-dimensional quantitative structure-activity relationship studies were performed on a series of 88 histamine receptor 4 (H4R) antagonists in an attempt to elucidate the 3D structural features required for activity. Several in silico modeling approaches, including comparative molecular field analysis (CoMFA), comparative similarity indices analysis (CoMSIA), molecular docking, and molecular dynamics (MD), were carried out. The results show that both the ligand-based CoMFA model (Q (2) = 0.548, R (ncv) (2)  = 0.870, R (pre) (2)  = 0.879, SEE = 0.410, SEP = 0.386) and the CoMSIA model (Q (2) = 0.526, R (ncv) (2) =0.866, R (pre) (2)  = 0.848, SEE = 0.416, SEP = 0.413) are acceptable, as they show good predictive capabilities. Furthermore, a combined analysis incorporating CoMFA, CoMSIA contour maps and MD results shows that (1) compounds with bulky or hydrophobic substituents at positions 4-6 in ring A (R2 substituent), positively charged or hydrogen-bonding (HB) donor groups in the R1 substituent, and hydrophilic or HB acceptor groups in ring C show enhanced biological activities, and (2) the key amino acids in the binding pocket are TRP67, LEU71, ASP94, TYR95, PHE263 and GLN266. To our best knowledge, this work is the first to report the 3D-QSAR modeling of these H4R antagonists. The conclusions of this work may lead to a better understanding of the mechanism of antagonism and aid in the design of new, more potent H4R antagonists.

Studies of new fused benzazepine as selective dopamine D3 receptor antagonists using 3D-QSAR, molecular docking and molecular dynamics

In recent years, great interest has been paid to the development of compounds with high selectivity for central dopamine (DA) D3 receptors, an interesting therapeutic target in the treatment of different neurological disorders. In the present work, based on a dataset of 110 collected benzazepine (BAZ) DA D3 antagonists with diverse kinds of structures, a variety of in silico modeling approaches, including comparative molecular field analysis (CoMFA), comparative similarity indices analysis (CoMSIA), homology modeling, molecular docking and molecular dynamics (MD) were carried out to reveal the requisite 3D structural features for activity. Our results show that both the receptor-based (Q(2) = 0.603, R(2) (ncv) = 0.829, R(2) (pre) = 0.690, SEE = 0.316, SEP = 0.406) and ligand-based 3D-QSAR models (Q(2) = 0.506, R(2) (ncv) =0.838, R(2) (pre) = 0.794, SEE = 0.316, SEP = 0.296) are reliable with proper predictive capacity. In addition, a combined analysis between the CoMFA, CoMSIA contour maps and MD results with a homology DA receptor model shows that: (1) ring-A, position-2 and R(3) substituent in ring-D are crucial in the design of antagonists with higher activity; (2) more bulky R(1) substituents (at position-2 of ring-A) of antagonists may well fit in the binding pocket; (3) hydrophobicity represented by MlogP is important for building satisfactory QSAR models; (4) key amino acids of the binding pocket are CYS101, ILE105, LEU106, VAL151, PHE175, PHE184, PRO254 and ALA251. To our best knowledge, this work is the first report on 3D-QSAR modeling of the new fused BAZs as DA D3 antagonists. These results might provide information for a better understanding of the mechanism of antagonism and thus be helpful in designing new potent DA D3 antagonists.

Self-organizing molecular field analysis on pregnane derivatives as human steroidal 5alpha-reductase inhibitors

Normal growth and development of human prostate is regulated by the androgens which balances cell proliferation and apoptosis. Testosterone (T) and dihydrotestosterone (DHT) are the two key androgens that stimulate most of the androgen action in prostate. Testosterone is converted to DHT by the membrane bound NADPH-dependent 5alpha-reductase enzyme. As a consequence of the important observation that progesterone and deoxycortisone inhibits the synthesis of DHT by competing with 4-en-3-one function of the testosterone for the 5alpha-reductase enzyme a number of pregnane derivatives were synthesized and have been reported as inhibitors of human 5alpha-reductase enzyme. Due to lack of information on the crystal structure of human 5alpha-reductase, ligand-based 3D-QSAR study has been performed on pregnane derivatives using self-organizing molecular field analysis (SOMFA) for rationalizing the molecular properties and human 5alpha-reductase inhibitory activities. The statistical results having good cross-validated r(cv)(2) (0.881), non-cross-validated r(2) (0.893) and F-test value (175.527), showed satisfied predictive ability r(pred)(2) (0.777). Analysis of SOMFA models through electrostatic and shape grids provide useful information for the design and optimization of steroidal structure as novel human 5alpha-reductase inhibitors.

Three-dimensional quantitative structure activity relationship (3D-QSAR) analysis for in vitro toxicity of chlorophenols to HepG2 cells

In the present paper, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were applied to investigate two 3D-QSAR models for the cytotoxicity of chlorophenols. These models have evaluated the intensity of chlorophenols' toxicity on HepG2 cells in vitro. The CoMFA model has both high consistency and predictability. The contribution of the electrostatic field to biological activity is greater than that of the steric field. The CoMSIA model used in this study includes two fields, one is hydrophobic field, and the other is electrostatic field. The relative contribution of them is 0.789:0.211. Consisted with the CoMFA model, the CoMSIA electrostatic filed also plays a dominant role. The CoMFA and CoMSIA contour maps significantly elucidated that the electrostatic field is more important than the other fields and might be one of the reasons resulting in potential reactive mechanism involved in cell proliferation inhibition.

A comparative study of quantitative structure-activity relationship methods based on gallic acid derivatives

By using hologram quantitative structure-activity relationship (HQSAR) and comparative molecular field analysis (CoMFA) methods, the relationships between the structures of 49 gallic acid derivatives and their analgesic activity have been investigated to yield statistically reliable models with considerable predictive power. The best HQSAR model was generated using atoms, bond and connectivity as fragment distinction parameters and fragment size 5-7 from a hologram length of 307 with 3 components. High conventional r2 (r2 = 0.825) and cross-validation r2 (r2(cv) = 0.726) values were obtained. CoMFA analyses varying lattice size and location, grid spacing, probe charges and using, Tripos standard and Indicator force field were performed. The best model was developed with 4 components using sp3-hybridized carbon atom with +1.0 charge as probe, grid spacing (2 A), lattice offset (1.0, 3.0, -2.5). The CoMFA model showed a conventional correlation coefficient r2 of 0.889 and across-validation r2(cv) equals to 0.633. The robustness and predictive ability of the HQSAR and CoMFA models have been validated by means of an external test set. The results indicate that both models possess high statistical quality in the prediction of analgesic potency of novel gallic acid analogs.