3D-QSAR studies of farnesyltransferase inhibitors: a comparative molecular field analysis approach

3D-QSAR analysis has been performed on a series of previously synthesized benzonitrile derivatives, which were screened as farnesyltransferase inhibitors, using comparative molecular field analysis (CoMFA) with partial least-square fit to predict the steric and electrostatic molecular field interactions for the activity. The CoMFA study was carried out using a training set of 34 compounds. The predictive ability of the model developed was assessed using a test set of eight compounds (r(pred)(2) as high as 0.770). The analyzed 3D-QSAR CoMFA model has demonstrated a good fit, having r(2) value of 0.991 and cross-validated coefficient q(2) value as 0.619. The analysis of CoMFA contour maps provided insight into the possible modification of the molecules for better activity.     

3D-QSAR analysis on benzazole derivatives as eukaryotic topoisomerase II inhibitors by using comparative molecular field analysis method

Selective topoisomerase II inhibitors have created a great deal of interest in recent years for the design of new antitumoral compounds. 3D-QSAR analysis has been performed on a series of previously synthesized benzoxazole, benzimidazole, and oxazolo(4,5-b)pyridine derivatives, which are screened as eukaryotic topoisomerase II inhibitors, using comparative molecular field analysis (CoMFA) with partial least squares fit to predict the steric and electrostatic molecular field interactions for the activity. The CoMFA study was carried out using a training set of 16 compounds. The predictive ability of the model was assessed using a test set of 7 compounds. The analyzed 3D-QSAR CoMFA model has demonstrated a good fit, having r(2) value of 0.997 and cross-validated coefficient q(2) value as 0.435 for the model. The obtained model reveals that the electronegatively charged substituents such as NO(2) or COOCH(3) group on position R and/or R(1) at the heterocyclic ring system and positively charged atom and/or atom groups located between the benzazole moiety and 2-substituted phenyl ring as a bridge element improve the activity. On the other hand, a bulky substituent, such as methoxy group, attached to the ortho position of 2-phenyl-5-nitro-benzoxazole (1) enhances the activity similar to compound 13, which is both a meta and para substituent of the phenyl group attached to the 2-position of benzimidazole ring system, fit into the favored steric region to improve the activity.     

3D-QSAR studies on PU3 analogues by comparative molecular field analysis

A comparative molecular field analysis (CoMFA) of PU3 derivatives of Hsp90 (Heat shock protein 90) inhibitors has been performed to determine the factors contributing the corresponding activities. The energy minimized conformations were obtained by molecular mechanics using SYBYL package. The developed model, with r(2) value of 0.947, was verified by performing leave-one out (LOO) cross-validation, which showed q(2) value of 0.513. The calculated model not only elucidates the relationship between compound structures and biological activities but, more importantly, facilitates design of new Hsp90 inhibitors with calculated antiproliferative activity.     

3D-QSAR studies on 4-hydroxyphenylpyruvate dioxygenase inhibitors by comparative molecular field analysis (CoMFA)

A comparative molecular field analysis (CoMFA) of alkanoic acid 3-oxo-cyclohex-1-enyl ester and 2-acylcyclohexane-1,3-dione derivatives of 4-hydroxyphenylpyruvate dioxygenase inhibitors has been performed to determine the factors required for the activity of these compounds. The substrate's conformation abstracted from dynamic modeling of the enzyme-substrate complex was used to build the initial structures of the inhibitors. Satisfactory results were obtained after an all-space searching procedure, performing a leave-one out (LOO) cross-validation study with cross-validation q(2) and conventional r(2) values of 0.779 and 0.989, respectively. The results provide the tools for predicting the affinity of related compounds, and for guiding the design and synthesis of new HPPD ligands with predetermined affinities.     

3D-QSAR studies on natural acetylcholinesterase inhibitors of Sarcococca saligna by comparative molecular field analysis (CoMFA)

We have derived a comprehensive structure–activity relationship (SAR) picture for a new series of natural acetylcholinesterase inhibitors isolated from Sarcococca saligna. A set of 32 previously isolated and tested pregnane-type steroidal alkaloids inhibitors were investigated with respect to their IC₅₀ values (pIC₅₀) against the AChE enzyme in order to derive CoMFA models using atom-based alignment. A highly significant CoMFA model was obtained with r² value of 0.974. The q² (cross validation r²) value also confirms the statistical significance of our model.     

3D-QSAR Study on dihydro-1,3,5-triazines and their spiro derivatives as DHFR inhibitors by comparative molecular field analysis (CoMFA)

A 3D-QSAR/CoMFA was performed for a series of triazine and its spiro derivative based DHFR inhibitors displaying IC(50) values ranging from 0.002 to 58.8 μM. Analyses resulted in a reliable computational model with the parameters of n=46, r(2)=0.986, q(2)=0.724, SE=0.164, F=275.889. It is shown that the steric and electrostatic properties predicted by CoMFA contours can be related to the DHFR inhibitory activity. The predictive ability of the resultant model was evaluated using a test set comprised of 18 molecules and the results show that the CoMFA model is able to correctly predict the poor inhibitory activities of the compounds in the testing set. This model is a significant guide to trace the features that really matter especially with respect to the design of novel compounds.     

A novel 3D-QSAR comparative molecular field analysis (CoMFA) model of imidazole and quinazolinone functionalized p38 MAP kinase inhibitors

In this study we describe a new comparative molecular field analysis (CoMFA) model of dihydroquinazolinone and tetrasubstituted imidazole compounds with p38 MAPK inhibitory activity. A series of 51 (a training set of 40 and a test set of 11) dihydroquinazolinone [Bioorg. Med. Chem. Lett. 2003, 13, 277.] and tetrasubstituted imidazole [J. Med. Chem. 1999, 42, 2180.] derivatives known as p38 mitogen-activated protein kinase (p38 MAPK) selective inhibitors was studied by quantitative structure-activity relationship (3D-QSAR) analysis using comparative molecular field analysis. The 3D-QSAR models were generated and evaluated by a scheme that combines a genetic algorithm (GA) optimization with partial least squares (PLS) regression and by crossvalidation using the leave-one-out technique. The model was able to efficiently predict the activities of the compounds of the test set, suggesting that it can be used for the planning of new p38 MAPK inhibitor candidates useful to treat chronic inflammatory states.     

3D-QSAR analysis of sialyltransferase inhibitors

A predictive 3D-QSAR model that correlates the biological activities with the chemical structures of a series of sialyltransferase inhibitors, exemplified by the sugar:nucleotide derivatives, was developed by means of comparative molecular field analysis (CoMFA). The resulting cross-validated value (q(2)=0.629), non-cross-validated value (r(2)=0.965) and standard error of estimate (SEE=0.288) indicate that the obtained pharmacophore model indeed mimics the steric and electrostatic environment where inhibitors bind to the enzyme. The developed model also possesses promising predictive ability as discerned by the testing on the external test set, and should be useful to further understand the molecular nature of inhibitor-enzyme interactions and to aid in the design of more potent sialyltransferase inhibitors.     

Probing the structural requirements of A-type Aurora kinase inhibitors using 3D-QSAR and molecular docking analysis

Aurora-A, the most widely studied isoform of Aurora kinase overexpressed aberrantly in a wide variety of tumors, has been implicated in early mitotic entry, degradation of natural tumor suppressor p53 and centrosome maturation and separation; hence, potent inhibitors of Aurora-A may be therapeutically useful drugs in the treatment of various forms of cancer. Here, we report an in silico study on a group of 220 reported Aurora-A inhibitors with six different substructures. Three-dimensional quantitative structure–activity relationship (3D-QSAR) studies were carried out using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques on this series of molecules. The resultant optimum 3D-QSAR models exhibited an r _cv² value of 0.404-0.582 and their predictive ability was validated using an independent test set, ending in r _pred² 0.512-0.985. In addition, docking studies were employed to explore these protein–inhibitor interactions at the molecular level. The results of 3D-QSAR and docking analyses validated each other, and the key structural requirements affecting Aurora-A inhibitory activities, and the influential amino acids involved were identified. To the best of our knowledge, this is the first report on 3D-QSAR modeling of Aurora-A inhibitors, and the results can be used to accurately predict the binding affinity of related analogues and also facilitate the rational design of novel inhibitors with more potent biological activities.     

3D-QSAR analysis of a new type of acetylcholinesterase inhibitors

Acetylcholinesterase (AChE) inhibitors are an important class of medicinal agents used for the treat- ment of Alzheimer's disease. A screening model of AChE inhibitor was used to evaluate the inhibition of a series of phenyl pentenone derivatives. The assay result showed that some compounds displayed higher inhibitory effects. In order to study the relationship between the bioactivities and the structures, 26 compounds with phenyl pentenone scaffold were analyzed. A 3D-QSAR model was constructed us- ing the method of comparative molecular field analysis (CoMFA). The results of cross-validated R2cv=0.629, non-cross-validated R2=0.972, SE=0.331, and F=72.41 indicate that the 3D-model pos- sesses an ability to predict the activities of new inhibitors, and the CoMFA model would be useful for the future design of new AChE inhibitors.     

3D-QSAR analysis of a new type of acetylcholinesterase inhibitors

Acetylcholinesterase (AChE) inhibitors are an important class of medicinal agents used for the treatment of Alzheimer’s disease. A screening model of AChE inhibitor was used to evaluate the inhibition of a series of phenyl pentenone derivatives. The assay result showed that some compounds displayed higher inhibitory effects. In order to study the relationship between the bioactivities and the structures, 26 compounds with phenyl pentenone scaffold were analyzed. A 3D-QSAR model was constructed using the method of comparative molecular field analysis (CoMFA). The results of cross-validated R²cv=0.629, non-cross-validated R²=0.972, SE=0.331, and F=72.41 indicate that the 3D-model possesses an ability to predict the activities of new inhibitors, and the CoMFA model would be useful for the future design of new AChE inhibitors.     

Study on molecular mechanism and 3D-QSAR of influenza neuraminidase inhibitors

Neuraminidase (NA) is a critical enzyme of the influenza virus and many inhibitors targeting to this enzyme are quite efficient and encouraging as anti-influenza agents. In this paper the binding model of five series of inhibitors to NA was examined using molecular simulation method. The resulted conformation and orientation of the compounds were directly put into CoMSIA study. The most significant amino acid residues at binding sites and the requirement for features of substituents were applied to direct design of new inhibitors. The robust QSAR model and its three-dimensional contour map provided guidelines to building novel compounds with new scaffold and for structural optimization of current molecules.     

3D-QSAR and molecular docking studies of 2-pyrimidinecarbonitrile derivatives as inhibitors against falcipain-3

The three dimensional-quantitative structure activity relationship (3D-QSAR) studies were performed on a series of falcipain-3 inhibitors using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. A training set containing 42 molecules served to establish the QSAR models. The optimum CoMFA and CoMSIA models obtained for the training set were statistically significant with cross-validated correlation coefficients r(cv)(2) (q(2)) of 0.549 and 0.608, and conventional correlation coefficients (r(2)) of 0.976 and 0.932, respectively. An independent test set of 12 molecules validated the external predictive power of both models with predicted correlation coefficients (r(pred)(2)) for CoMFA and CoMSIA as 0.697 and 0.509, respectively. The docking of inhibitors into falcipain-3 active site using GOLD software revealed the vital interactions and binding conformation of the inhibitors. The CoMFA and CoMSIA field contour maps agree well with the structural characteristics of the binding pocket of falcipain-3 active site, which suggests that the information rendered by 3D-QSAR models and the docking interactions can provide guidelines for the development of improved falcipain-3 inhibitors.     

3D-QSAR study of c-Src kinase inhibitors based on docking

Cancer is a significant world health problem for which efficient therapies are in urgent demand. c-Src has emerged as an attractive target for drug discovery efforts toward antitumor therapies. Toward this target several series of c-Src inhibitors that showed activity in the assay have been reported. In this article, 3D-QSAR models have been built with 156 anilinoquinazoline and quinolinecarbonitrile derivative inhibitors by using CoMFA and CoMSIA methods. These studies indicated that the QSAR models were statistically significant with high predictabilities (CoMFA model, q ² = 0.590, r ² = 0.855; CoMSIA model, q ² = 0.538, r ² = 0.748). The details of c-Src kinase/inhibitor binding interactions in the crystal structure of complex provided new information for the design of new inhibitors. As a result, docking simulations were also conducted on the series of potent inhibitors. The flexible docking method, which was performed by the DOCK program, positioned all of the inhibitors into the active site to determine the probable binding conformation. The CoMFA and CoMSIA models based on the flexible docking conformations also yielded statistically significant and highly predictive QSAR models (CoMFA model, q ² = 0.507, r ² = 0.695; CoMSIA model, q ² = 0.463, r ² = 0.734). Our models would offer help to better comprehend the structure-activity relationships that exist for this class of compounds and also facilitate the design of novel inhibitors with good chemical diversity.     

Discover potential inhibitors for PFKFB3 using 3D-QSAR,virtual screening,molecular docking and molecular dynamics simulation

Abstract

The 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase-3 (PFKFB3) is a master regulator of glycolysis in cancer cells by synthesizing fructose-2,6-bisphosphate (F-2,6-BP), a potent allosteric activator of phosphofructokinase-1 (PFK-1), which is a rate-limiting enzyme of glycolysis. PFKFB3 is an attractive target for cancer treatment. It is valuable to discover promising inhibitors by using 3D-QSAR pharmacophore modeling, virtual screening, molecular docking and molecular dynamics simulation. Twenty molecules with known activity were used to build 3D-QSAR pharmacophore models. The best pharmacophore model was ADHR called Hypo1, which had the highest correlation value of 0.98 and the lowest RMSD of 0.82. Then, the Hypo1 was validated by cost value method, test set method and decoy set validation method. Next, the Hypo1 combined with Lipinski's rule of five and ADMET properties were employed to screen databases including Asinex and Specs, total of 1,048,159 molecules. The hits retrieved from screening were docked into protein by different procedures including HTVS, SP and XP. Finally, nine molecules were picked out as potential PFKFB3 inhibitors. The stability of PFKFB3-lead complexes was verified by 40?ns molecular dynamics simulation. The binding free energy and the energy contribution of per residue to the binding energy were calculated by MM-PBSA based on molecular dynamics simulation.     

Exploration of potential RSK2 inhibitors by pharmacophore modelling,structure-based 3D-QSAR,molecular docking study and molecular dynamics simulation

Abstract

The p90 ribosomal s6 kinase 2 (RSK2) is a promising target because of its over expression and activation in human cancer cells and tissues. Over the last few years, significant efforts have been made in order to develop RSK2 inhibitors to treat myeloma, prostatic cancer, skin cancer and etc., but with limited success so far. In this paper, pharmacophore modelling, molecular docking study and molecular dynamics (MD) simulation have been performed to explore the novel inhibitors of RSK2. Pharmacophore models were developed by 95 molecules having pIC₅₀ ranging from 4.577 to 9.000. The pharmacophore model includes one hydrogen bond acceptor (A), one hydrogen bond donor (D), one hydrophobic feature (H) and one aromatic ring (R). It is the best pharmacophore hypothesis that has the highest correlation coefficient (R² = 0.91) and cross validation coefficient (Q² = 0.71) at 5 component PLS factor. It was evaluated using enrichment analysis and the best model was used for virtual screening. The constraints used in this study were docking score, ADME properties, binding free energy estimates and IFD Score to screen the database. Ultimately, 12 hits were identified as potent and novel RSK2 inhibitors. A 15 ns molecular dynamics (MD) simulation was further employed to validate the reliability of the docking results.     

Development of a receptor-based 3D-QSAR study for the analysis of MMP2, MMP3, and MMP9 inhibitors

The ability of Gold software to predict the binding disposition of matrix metalloproteinase (MMP) inhibitors was evaluated using MMP3 and MMP8. The best procedure was subsequently employed to dock into MMP2, MMP3 and MMP9 nearly 70 compounds that were tested for their inhibitory activity against the three MMP subtypes. The best binding poses were used as an alignment tool for the development of 3D-QSAR studies. Evaluation of the three resulting 3D-QSAR models allowed us to indicate the ligand properties and residues important for activity and selectivity. MMP2 is an important anticancer drug target, while MMP3 and MMP9 are considered to be anti-targets for tumor pathologies. As such, our results could predict the binding affinities of new MMP2 inhibitors, providing additional information regarding the selectivity against MMP3 and MMP9. Furthermore, this strategy may be used also for the investigation of other MMPs.     

Computational investigations of gram-negative bacteria phosphopantetheine adenylyltransferase inhibitors using 3D-QSAR,molecular docking and molecular dynamic simulations

Abstract

Phosphopantetheine adenylyltransferase (PPAT) has been recognized as a promising target to develop novel antimicrobial agents, which is a hexameric enzyme that catalyzes the penultimate step in coenzyme A biosynthesis. In this work, molecular modeling study was performed with a series of PPAT inhibitors using molecular docking, three-dimensional qualitative structure-activity relationship (3D-QSAR) and molecular dynamic (MD) simulations to reveal the structural determinants for their bioactivities. Molecular docking study was applied to understand the binding mode of PPAT with its inhibitors. Subsequently, 3D-QSAR model was constructed to find the features required for different substituents on the scaffolds. For the best comparative molecular field analysis (CoMFA) model, the Q² and R² values of which were calculated as 0.702 and 0.989, while they were calculated as 0.767 and 0.983 for the best comparative molecular similarity index analysis model. The statistical data verified the significance and accuracy of our 3D-QSAR models. Furthermore, MD simulations were carried out to evaluate the stability of the receptor–ligand contacts in physiological conditions, and the results were consistent with molecular docking studies and 3D-QSAR contour map analysis. Binding free energy was calculated with molecular mechanics generalized born surface area approach, the result of which coincided well with bioactivities and demonstrated that van der Waals accounted for the largest portion. Overall, our study provided a valuable insight for further research work on the recognition of potent PPAT inhibitors.

Communicated by Ramaswamy H. Sarma