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 analysis of antimalarial farnesyltransferase inhibitors based on a 2,5-diaminobenzophenone scaffold

With annual death tolls in the millions and emerging resistance to existing drugs, novel therapies are needed against malaria. Wiesner et al. recently developed a novel class of antimalarials derived from farnesyltransferase inhibitors based on a 2,5-diaminobenzophenone scaffold. The compounds displayed a wide range of activity, including submicromolar, against the multi-drug resistant Plasmodium falciparum strain Dd2. In order to investigate quantitatively the local physicochemical properties involved in the interaction between drug and biotarget, we used the 3D-QSAR methods CoMFA and CoMSIA to study some of the series, including the screened lead compound 2,5-bis-acylaminobenzophenone, 28 cinnamic acid derivatives, 29 N-(3-benzoyl-4-tolylacetylaminophenyl)-3-(5-aryl-2-furyl)acrylic acid amides, and 34 N-(4-substituted-amino-3-benzoylphenyl)-[5-(4-nitrophenyl)-2-furyl]acrylic acid amides. We found that steric, electrostatic, and hydrophobic properties of substituent groups play key roles in the bioactivity of the series of compounds, while hydrogen bonding interactions show no obvious impact. We built several highly predictive 3D-QSAR models, including a CoMSIA one composed of steric, electrostatic, and hydrophobic fields, with r(2)=0.94, q(2)=0.63, and r(pred)(2)=0.63. The results provide insight for optimization of this class of antimalarials for better activity and may prove helpful for further lead optimization.     

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.     

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 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.     

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.     

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 studies of checkpoint kinase 1 inhibitors based on molecular docking and CoMFA

Three-dimensional quantitative structure–activity relationship (3D-QSAR) studies were performed on a series of substituted 1,4-dihydroindeno[1,2-c]pyrazoles inhibitors, using molecular docking and comparative molecular field analysis (CoMFA). The docking results from GOLD 3.0.1 provide a reliable conformational alignment scheme for the 3D-QSAR model. Based on the docking conformations and alignments, highly predictive CoMFA model was built with cross-validated q ² value of 0.534 and non-cross-validated partial least-squares analysis with the optimum components of six showed a conventional r ² value of 0.911. The predictive ability of this model was validated by the testing set with a conventional r ² value of 0.812. Based on the docking and CoMFA, we have identified some key features of the 1,4-dihydroindeno[1,2-c]pyrazoles derivatives that are responsible for checkpoint kinase 1 inhibitory activity. The analyses may be used to design more potent 1,4-dihydroindeno[1,2-c]pyrazoles derivatives and predict their activity prior to synthesis.     

3D-QSAR and molecular docking studies of azaindole derivatives as Aurora B kinase inhibitors

The Aurora kinases have been regarded as attractive targets for the development of new anticancer agents. Recently a series of azaindole derivatives with Aurora B inhibitory activities were reported. To explore the relationship between the structures of substituted azaindole derivatives and their inhibition of Aurora B, 3D-QSAR and molecular docking studies were performed on a dataset of 41 compounds. 3D-QSAR, including CoMFA and CoMSIA, were applied to identify the key structures impacting their inhibitory potencies. The CoMSIA model showed better results than CoMFA, with r ² _cv value of 0.575 and r ² value of 0.987. 3D contour maps generated from CoMFA and CoMSIA along with the docking binding structures provided enough information about the structural requirements for better activity. Based on the structure-activity relationship revealed by the present study, we have designed a set of novel Aurora B inhibitors that showed excellent potencies in the developed models. Thus, our results allowed us to design new derivatives with desired 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.     

Computational studies of COX-2 inhibitors: 3D-QSAR and docking

The 3D-QSAR (three-dimensional quantitative structure-activity relationships) studies for 88 selective COX-2 (cyclooxygenase-2) inhibitors belonging to three chemical classes (triaryl rings, diaryl cycloalkanopyrazoles, and diphenyl hydrazides) were conducted using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Partial least squares analysis produced statistically significant models with q(2) values of 0.84 and 0.79 for CoMFA and CoMSIA, respectively. The binding energies calculated from flexible docking were correlated with inhibitory activities by the least-squares fit method. The three chemical classes of inhibitors showed reasonable internal predictability (r(2)=0.51, 0.49, and 0.54), but the sulfonyl-containing inhibitors demonstrated distinctively low binding energy compared to the others. The electrostatic interaction energy between the Arg513 of the COX-2 active site and sulfonyl group of the triaryl rings seemed to have the responsibility for difference in binding energy. Comparative binding energy (COMBINE) analyses gave q(2) values of 0.64, 0.63, and 0.50 for triaryl rings, diaryl cycloalkanopyrazoles, and diphenyl hydrazides, respectively. In this COMBINE model, some protein residues were highlighted as particularly important for inhibitory activity. The combination of ligand-based and structure-based models provided an improved understanding in the interaction between the three chemical classes and the COX-2.     

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.     

3D-QSAR studies on malonyl coenzyme A decarboxylase inhibitors

Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on a series of Malonyl Co-A decarboxylase (MCD) inhibitors (Cheng et al. J. Med. Chem.2006, 49, 1517-1525 and Cheng et al. Bioorg. Med. Chem. Lett.2006, 16, 695-700). These inhibitors have shown protective action on the ischemic heart by inhibiting fatty acid oxidation. The CoMFA model produced statistically significant results, with the cross-validated and conventional correlation coefficients being 0.544 and 0.986, respectively. The best results were obtained by combining steric, electrostatic, hydrophobic, and H-bond acceptor fields in CoMSIA, in which case the respective cross-validated and conventional correlation coefficients were 0.551 and 0.918. The predictive ability of CoMFA and CoMSIA, determined using a test set of 24 compounds, gave predictive correlation coefficients of 0.718 and 0.725, respectively. The information obtained from CoMFA and CoMSIA 3D contour maps may be of utility in the design of more potent MCD inhibitors.     

3D-QSAR and QSSR studies of 3,8-diazabicyclo[4.2.0]octane derivatives as neuronal nicotinic acetylcholine receptors by comparative molecular field analysis (CoMFA)

High subtype selectivity (α4β2 over α2β3) of neuronal nicotinic acetylcholine receptor (nAChR) agonists is critical for the rational design of less toxic drugs used for the treatment of neurodegenerative and psychiatric diseases. Here, three CoMFA models of pEC₅₀(α4β2), pEC₅₀(α2β3) and p[EC₅₀(α4β2)/EC₅₀(α2β3)] (pEC₅₀(α4β2)pEC₅₀(α2β3)) were developed to study the quantitative structure–activity relationship (QSAR) and quantitative structure–selectivity relationship (QSSR) of the 3,8-diazabicyclo[4.2.0]octane derivatives as nAChRs agonists. The parameters of the three models were 0.584, 0.792, and 0.599 for cross-validated r² (r²_CV), 0.924, 0.935 and 0.875 for conventional r². Analyses indicated that both the steric and electrostatic factors should be considered in the rational design of more active and selective nAChR agonists.     

Molecular modeling studies of atorvastatin analogues as HMGR inhibitors using 3D-QSAR,molecular docking and molecular dynamics simulations

3-Hydroxy-3-methylglutaryl coenzyme-A reductase (HMGR) is generally regarded as targets for the treatment of hypercholesterolemia. HMGR inhibitors (more commonly known as statins) are discovered as plasma cholesterol lowering molecules. In this work, 120 atorvastatin analogues were studied using a combination of molecular modeling techniques including three-dimensional quantitative structure–activity relationship (3D-QSAR), molecular docking and molecular dynamics (MD) simulation. The results show that the best CoMFA (comparative molecular field analysis) model has q² = 0.558 and r² = 0.977, and the best CoMSIA (comparative molecular similarity indices analysis) model has q² = 0.582 and r² = 0.919. Molecular docking and MD simulation explored the binding relationship of the ligand and the receptor protein. The calculation results indicated that the hydrophobic and electrostatic fields play key roles in QSAR model. After MD simulation, we found four vital residues (Lys735, Arg590, Asp690 and Asn686) and three hydrophobic regions in HMGR binding site. The calculation results show that atorvastatin analogues obtained by introduction of F atoms or gem-difluoro groups could obviously improve the inhibitory activity. The new HMGR inhibitor analogues design in this Letter had been submitted which is being currently synthesized by our laboratories.