3D CoMFA,CoMSIA, topomer CoMFA and HQSAR studies on aromatic acid esters for carbonic anhydrase inhibitory activity

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.     

3D-QSAR and molecular docking study of LRRK2 kinase inhibitors by CoMFA and CoMSIA methods

Three-dimensional quantitative structure–activity relationship (3D-QSAR) modelling was conducted on a series of leucine-rich repeat kinase 2 (LRRK2) antagonists using CoMFA and CoMSIA methods. The data set, which consisted of 37 molecules, was divided into training and test subsets by using a hierarchical clustering method. Both CoMFA and CoMSIA models were derived using a training set on the basis of the common substructure-based alignment. The optimum PLS model built by CoMFA and CoMSIA provided satisfactory statistical results (q² = 0.589 and r² = 0.927 and q² = 0.473 and r² = 0.802, respectively). The external predictive ability of the models was evaluated by using seven compounds. Moreover, an external evaluation set with known experimental data was used to evaluate the external predictive ability of the porposed models. The statistical parameters indicated that CoMFA (after region focusing) has high predictive ability in comparison with standard CoMFA and CoMSIA models. Molecular docking was also performed on the most active compound to investigate the existence of interactions between the most active inhibitor and the LRRK2 receptor. Based on the obtained results and CoMFA contour maps, some features were introduced to provide useful insights for designing novel and potent LRRK2 inhibitors.     

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

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

CoMFA and CoMSIA 3D-quantitative structure-activity relationship model on benzodiazepine derivatives, inhibitors of phosphodiesterase IV

Recently, we reported structurally novel PDE4 inhibitors based on 1,4-benzodiazepine derivatives. The main interest in developing bezodiazepine-based PDE4 inhibitors is in their lack of adverse effects of emesis with respect to rolipram-like compounds. A large effort has thus been made toward the structural optimization of this series. In the absence of structural information on the inhibitor binding mode into the PDE4 active site, 2D-QSAR (H-QSAR) and two 3D-QSAR (CoMFA and CoMSIA) methods were applied to improve our understanding of the molecular mechanism controlling the PDE4 affinity of the benzodiazepine derivatives. As expected, the CoMSIA 3D contour maps have provided more information on the benzodiazepine interaction mode with the PDE4 active site whereas CoMFA has built the best tool for activity prediction. The 2D pharmacophoric model derived from CoMSIA fields is consistent with the crystal structure of the PDE4 active site reported recently. The combination of the 2D and 3D-QSAR models was used not only to predict new compounds from the structural optimization process, but also to screen a large library of bezodiazepine derivatives.     

A combined CoMFA and CoMSIA 3D-QSAR study of benzamide type antibacterial inhibitors of the FtsZ protein in drug-resistant Staphylococcus aureus

A major problem today is bacterial resistance to antibiotics and the small number of new therapeutic agents approved in recent years. The development of new antibiotics capable of acting on new targets is urgently required. The filamenting temperature-sensitive Z (FtsZ) bacterial protein is a key biomolecule for bacterial division and survival. This makes FtsZ an attractive new pharmacological target for the development of antibacterial agents. There have been several attempts to develop ligands able to inhibit FtsZ. Despite the large number of synthesized compounds that inhibit the FtsZ protein, there are no quantitative structure–activity relationships (QSAR) that allow for the rational design and synthesis of promising new molecules. We present the first 3D-QSAR study of a large and diverse set of molecules that are able to inhibit the FtsZ bacterial protein. We summarize a set of chemical changes that can be made in the steric, electrostatic, hydrophobic and donor/acceptor hydrogen-bonding properties of the pharmacophore, to generate new bioactive molecules against FtsZ. These results provide a rational guide for the design and synthesis of promising new antibacterial agents, supported by the strong statistical parameters obtained from CoMFA (r²_pred = 0.974) and CoMSIA (r²_pred = 0.980) analyses.     

3D-QSAR studies on glycogen phosphorylase inhibitors by flexible comparative molecular field analysis

Canceling grids accommodating probes in comparative molecular field analysis (CoMFA), the idea of flexibleness is introduced into the CoMFA, and in combination with swarm intelligent algorithm which attempts to optimize distributions of diverse probes around drug molecules, a new 3D-QSAR method is proposed in this context as flexible comparative molecular field analysis (FCoMFA). In preliminary at-tempts to performing QSAR studies on 47 glycogen phosphorylase inhibitors, FCoMFA is employed and confirmed to be potent to exploring ligand-receptor interaction manners at active positions and thus to generating stable and predictable models. Simultaneously by an intuitive graphics regarding probe distribution patterns, impacts of different substituted groups on activities is also given an insight into.     

QSAR studies on hepatitis C virus NS5A protein tetracyclic inhibitors in wild type and mutants by CoMFA and CoMSIA

ABSTRACT

Several 3D-QSAR models were built based on 196 hepatitis C virus (HCV) NS5A protein inhibitors. The bioactivity values EC₉₀ for three types of inhibitors, the wild type (GT1a) and two mutants (GT1a Y93H and GT1a L31V), were collected to build three datasets. The programs OMEGA and ROCS were used for generating conformations and aligning molecules of the dataset, respectively. Each dataset was randomly divided into a training set and a test set three times to reduce the contingency of only one random selection. QSAR models were computed by comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). For the datasets GT1a, GT1a Y93H, and GT1a L31V, the best models CoMFA-INDX, CoMSIA-SEHA, and CoMSIA-SEHA showed an r² value of 0.682 ± 0.033, 0.779 ± 0.036, and 0.782 ± 0.022 on the test sets, respectively. From the contour maps of the three best models, we summarized the favourable and unfavourable substituents on the tetracyclic core, the Z group, the proline group, and the valine group of inhibitors. We guessed the mutants could change the electrostatic surfaces of the wild type active pocket. In addition, we used ECFP analyses to find important substructures and could intuitively understand the results from QSAR models.     

3D-QSAR studies on indole and 7-azoindole derivatives as ROCK-2 inhibitors: An integrative computational approach

Rho Kinases (ROCK) has been found to regulate a wide range of fundamental cell functions such as contraction, motility, proliferation, and apoptosis. Recent experiments have defined new functions of ROCKs in cells, including centrosome positioning and cell-size regulation, which might contribute to various physiological and pathological states. In this study, we have performed pharmacophore modeling and 3D QSAR studies on a series of 36 indoles and 7-azoindoles derivatives as ROCK2 inhibitors to elucidate the structural variations with their inhibitory activities. Ligand based CoMFA and CoMSIA models were generated based on three different alignment methods such as systematic search, simulated annealing and pharmacophore. A total of 15 CoMFA models and 27 CoMSIA were generated using different alignments. One model from each alignment is selected based on the statistical values. Contour maps of the selected models were compared, analysed and reported. The 3D QSAR study revealed that electro positive group linked to the methoxy-benzene ring position of the structure will enhance the biological activity and bulkier substitutions are preferred in the methyl dihydroindole region. Also, it is found that the hydrogen bond donor substituted at the R₁ position enhances the inhibitory activity. In future, this study would give proper guidelines to further enhance the activity of novel inhibitors for ROCK2.     

CoMFA and CoMSIA studies on a new series of xanthone derivatives against the oral human epidermoid carcinoma (KB) cancer cell line

Abstract  A new series of xanthone derivatives against the oral human epidermoid carcinoma (KB) cancer cell line is examined to determine the relationship between the structural properties and the biological activity of these compounds—the 3-D quantitative structure–activity relationship (3D-QSAR)—using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The best CoMFA and CoMSIA models were obtained using the atom-based alignment of 33 compounds, 22 training compounds and 11 tested compounds, and these give desirable statistics; those for the CoMFA standard model were: r _cv² = 0.691, r ² = 0.998, S _press = 0.178, s = 0.014 and F = 1080.765, while CoMSIA combined steric, electrostatic, hydrophobic and hydrogen-bond acceptor fields: r _cv² = 0.600, r ² = 0.988, S _press = 0.206, s = 0.034 and F = 284.433. The 3D-QSAR models calculated satisfactory test set activities. The 3D-QSAR contour plots correlated strongly with the experimental data for the binding topology. For this reason, these results would be beneficial for predicting affinities with the compounds of interest, and they are advantageous for guiding the design and synthesis of new and more effective anticancer agents. Graphical abstract   A new and more effective anticancer agent of xanthone derivatives against the oral human epidermoid carcinoma (KB) cell line, as investigated by CoMFA and CoMSIA analysis     

Studies on molecular mechanism between SHP2 and pyridine derivatives by 3D-QSAR,molecular docking and MD simulations

BackgroundSrc homology 2 (SH2)-containing protein tyrosine phosphatase 2 (SHP2) as a major phosphatase would affect the development of tumors by regulating several cellular processes, and is a significant potential target for cancer treatment.MethodsIn the present work, a series of pyridine derivatives possessing a wide range of inhibitory activity was employed to investigate the structural requirements by developing three dimensional quantitative structure–activity relationship (3D-QSAR) models using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods. The results show that CoMFA (R²_cv = 0.646, R²_pred = 0.5587) and CoMSIA (R²_cv = 0.777, R²_pred = 0.7131) have excellent stability and predictability. The relationship between the inhibitory activity and structure of the inhibitors was analyzed by the derived contour maps. Furthermore, the QSAR models were validated by molecular docking and molecular dynamics simulations, which were also applied to reveal the potential molecular mechanism of these inhibitors.FindingsIt was found that Arg110, Asn216, Thr218, Thr252 and Pro490 play a crucial role in stabilizing the inhibitors. Additionally, MM/PBSA calculations provided the binding free energy were also conducted to explain the discrepancy of binding activities. Overall, the outcomes of this work could provide useful information and theoretical guidance for the development of novel and potent SHP2 inhibitors.     

Molecular structural investigations of quinoxaline derivatives through 3D-QSAR,molecular docking,ADME prediction and pharmacophore modeling studies for the search of novel antimalarial agent

In the present article, a dataset of 63 quinoxaline derivatives were taken for antimalarial activity and pharmacophore were developed. Atom based method was used to develop a three dimensional quantitative structure activity relationship (3D-QSAR) model. On comparison of all statistical parameters, model AHRRR23 was found to be the most effective and predictive QSAR model as it satisfied all statistical parameters of a good model. The model AHRRR23 showed an adequate R² value for the training set 0.9446, good predictive power with Q² of 0.6409, good F- value, low SD 0.1218 value and outstanding Pearson-R values and low RMSE 0.2779 values of the model. The docking studies also gives very good results with good RMSD values. 3D QSAR, docking and ADME studies exhibits that the developed model could be employed as a potential lead for further study as antimalarial drug.     

Identification of novel nt-MGAM inhibitors for potential treatment of type 2 diabetes: Virtual screening,atom based 3D-QSAR model,docking analysis and ADME study

In this study, a virtual screening procedure was applied to identify new potential nt-MGAM inhibitors as a possible medication for type 2 diabetes. To this aim, a series of salacinol analogues were first investigated by docking analysis for their binding to the X-ray structure of the biological target nt-MGAM. Key interactions for ligand binding into the receptor active site were identified which shared common features to those found for other known inhibitors, which strengthen the results of this study. 3D QSAR model was then built and showed to be statistically significant and with a good predictive power for the training (R² = 0.99, SD = 0.17, F = 555.3 and N = 27) and test set (Q² = 0.81, Pearson(r) = 0.92, RMSE = 0.52, N = 08). The model was then used to virtually screen the ZINC database with the aim of identifying novel chemical scaffolds as potential nt-MGAM inhibitors. Further, in silico predicted ADME properties were investigated for the most promising molecules. The outcome of this investigation sheds light on the molecular characteristics of the binding of salacinol analogues to nt-MGAM enzyme and identifies new possible inhibitors which have the potential to be developed into drugs, thus significantly contributing to the design and optimization of therapeutic strategies against type 2 diabetes.     

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.