Three-dimensional quantitative structure-activity relationship studies on novel series of benzotriazine based compounds acting as Src inhibitors using CoMFA and CoMSIA

Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on a series of benzotriazine derivatives, as Src inhibitors. Ligand molecular superimposition on the template structure was performed by database alignment method. The statistically significant model was established of 72 molecules, which were validated by a test set of six compounds. The CoMFA model yielded a q(2)=0.526, non cross-validated R(2) of 0.781, F value of 88.132, bootstrapped R(2) of 0.831, standard error of prediction=0.587, and standard error of estimate=0.351 while the CoMSIA model yielded the best predictive model with a q(2)=0.647, non cross-validated R(2) of 0.895, F value of 115.906, bootstrapped R(2) of 0.953, standard error of prediction=0.519, and standard error of estimate=0.178. The contour maps obtained from 3D-QSAR studies were appraised for activity trends for the molecules analyzed. Results indicate that small steric volumes in the hydrophobic region, electron-withdrawing groups next to the aryl linker region, and atoms close to the solvent accessible region increase the Src inhibitory activity of the compounds. In fact, adding substituents at positions 5, 6, and 8 of the benzotriazine nucleus were generated new compounds having a higher predicted activity. The data generated from the present study will further help to design novel, potent, and selective Src inhibitors as anticancer therapeutic agents.     

Comparative molecular field analysis and comparative molecular similarity indices analysis of human thymidine kinase 1 substrates

Thymidine kinase 1 (TK1) is a key target for antiviral and anticancer chemotherapy. Three-dimensional quantitative structure-activity relationship (3D-QSAR) using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques was applied to analyze the phosphorylation capacity of a series of 31 TK1 substrates. The optimal predictive CoMFA model with 26 molecules provided the following values: cross-validated r(2) (q(2))=0.651, non-cross-validated r(2)=0.980, standard error of estimate (s)=0.207, F=129.3. For the optimal CoMSIA model the following values were found: q(2)=0.619, r(2)=0.994, s=0.104, F=372.2. The CoMSIA model includes steric, electrostatic, and hydrogen bond donor fields. The predictive capacity of both models was successfully validated by calculating known phosphorylation rates of five TK1 substrates that were not included in the training set. Contour maps obtained from CoMFA and CoMSIA models correlated with the experimentally developed SAR.     

DAT/SERT selectivity of flexible GBR 12909 analogs modeled using 3D-QSAR methods

The dopamine reuptake inhibitor GBR 12909 (1-{2-[bis(4-fluorophenyl)methoxy]ethyl}-4-(3-phenylpropyl)piperazine, 1) and its analogs have been developed as tools to test the hypothesis that selective dopamine transporter (DAT) inhibitors will be useful therapeutics for cocaine addiction. This 3D-QSAR study focuses on the effect of substitutions in the phenylpropyl region of 1. CoMFA and CoMSIA techniques were used to determine a predictive and stable model for the DAT/serotonin transporter (SERT) selectivity (represented by pK(i) (DAT/SERT)) of a set of flexible analogs of 1, most of which have eight rotatable bonds. In the absence of a rigid analog to use as a 3D-QSAR template, six conformational families of analogs were constructed from six pairs of piperazine and piperidine template conformers identified by hierarchical clustering as representative molecular conformations. Three models stable to y-value scrambling were identified after a comprehensive CoMFA and CoMSIA survey with Region Focusing. Test set correlation validation led to an acceptable model, with q(2)=0.508, standard error of prediction=0.601, two components, r(2)=0.685, standard error of estimate=0.481, F value=39, percent steric contribution=65, and percent electrostatic contribution=35. A CoMFA contour map identified areas of the molecule that affect pK(i) (DAT/SERT). This work outlines a protocol for deriving a stable and predictive model of the biological activity of a set of very flexible molecules.     

Stereoselective synthesis of phosphoramidate alpha(2-6)sialyltransferase transition-state analogue inhibitors

The asymmetric synthesis of novel, potent phosphoramidate alpha(2-6)sialyltransferase transition-state analogue inhibitors such as (R)-9 (K(i)=68 microM) is described, via condensation of cytidine phosphitamide 6 with key chiral, non-racemic alpha-aminophosphonates, prepared in >98% ee by Mitsunobu azidation followed by Staudinger reduction of the corresponding chiral, non-racemic alpha-hydroxyphosphonates.     

Pharmacophore generation and atom-based 3D-QSAR of novel quinoline-3-carbonitrile derivatives as Tpl2 kinase inhibitors

Tumour progression locus-2 (Tpl2) is a serine/threonine kinase, which regulates the expression of tumour necrosis factor α. The article describes the development of a robust pharmacophore model and the investigation of structure-activity relationship analysis of quinoline-3-carbonitrile derivatives reported for Tpl2 kinase inhibition. A five point pharmacophore model (ADRRR) was developed and used to derive a predictive atom-based 3-dimensional quantitative structure activity relationship (3D-QSAR) model. The obtained 3D-QSAR model has an excellent correlation coefficient value (r(2)= 0.96), Fisher ratio (F = 131.9) and exhibited good predictive power (q(2) = 0.79). The QSAR model suggests that the inclusion of hydrophobic substituents will enhance the Tpl2 kinase inhibition. In addition, H-bond donating groups, negative ionic groups and electron withdrawing groups positively contribute to the Tpl2 kinase inhibition. Further, pharmacophoric model was validated by the receiver operating characteristic curve analysis and was employed for virtual screening to identify six potential Tpl2 kinase inhibitors. The findings of this study provide a set of guidelines for designing compounds with better Tpl2 kinase inhibitory potency.     

2D QSAR and similarity studies on cruzain inhibitors aimed at improving selectivity over cathepsin L

Hologram quantitative structure-activity relationships (HQSAR) were applied to a data set of 41 cruzain inhibitors. The best HQSAR model (Q(2)=0.77; R(2)=0.90) employing Surflex-Sim, as training and test sets generator, was obtained using atoms, bonds, and connections as fragment distinctions and 4-7 as fragment size. This model was then used to predict the potencies of 12 test set compounds, giving satisfactory predictive R(2) value of 0.88. The contribution maps obtained from the best HQSAR model are in agreement with the biological activities of the study compounds. The Trypanosoma cruzi cruzain shares high similarity with the mammalian homolog cathepsin L. The selectivity toward cruzain was checked by a database of 123 compounds, which corresponds to the 41 cruzain inhibitors used in the HQSAR model development plus 82 cathepsin L inhibitors. We screened these compounds by ROCS (Rapid Overlay of Chemical Structures), a Gaussian-shape volume overlap filter that can rapidly identify shapes that match the query molecule. Remarkably, ROCS was able to rank the first 37 hits as being only cruzain inhibitors. In addition, the area under the curve (AUC) obtained with ROCS was 0.96, indicating that the method was very efficient to distinguishing between cruzain and cathepsin L inhibitors.     

Comparative molecular field analysis (CoMFA) of phthalazine derivatives as phosphodiesterase IV inhibitors

A comparative molecular field analysis (CoMFA) of phthalazine class of phosphodiesterase IV (PDE IV) inhibitors has been performed to correlate their chemical structures with their observed biological activity. A statistically valid model with good correlative and predictive power is reported. The leave one out cross-validation study gave cross-validation r(2)(cv) of value 0.507 at six optimum components and conventional r(2) of value 0.98. The predictive ability of the model was tested by predicting the seven molecules belonging to the test set giving predictive correlation coefficient of 0.59. This model is potentially helpful in the design of novel and more potent PDE IV inhibitors.     

3D QSAR studies on T-type calcium channel blockers using CoMFA and CoMSIA

Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on a series of isoxazolyl compounds as a potent T-type calcium channel blockers. A set of 24 structurally similar compounds served to establish the model. Four different conformations of the most active compound were used as template structures for the alignment, three of which were obtained from Catalyst pharmacophore modeling and one by using SYBYL random search option. All CoMFA and CoMSIA models gave cross-validated r(2) (q(2)) value of more than 0.5 and conventional r(2) value of more than 0.85. The predictive ability of the models was validated by an external test set of 10 compounds, which gave satisfactory pred r(2) values ranging from 0.577 to 0.866 for all models. Best predictions were obtained with CoMFA std model of Conformer no: 3 alignment (q(2)=0.756, r(2)=0.963), giving predictive r(2) value of 0.866 for the test set. CoMFA and CoMSIA contour maps were used to analyze the structural features of the ligands accounting for the activity in terms of positively contributing physicochemical properties: steric, electrostatic, hydrophobic and hydrogen bonding fields.     

Beta-amino acid substitutions and structure-based CoMFA modeling of hepatitis C virus NS3 protease inhibitors

In an effort to develop a new type of HCV NS3 peptidomimetic inhibitor, a series of tripeptide inhibitors incorporating a mix of alpha- and beta-amino acids has been synthesized. To understand the structural implications of beta-amino acid substitution, the P(1), P(2), and P(3) positions of a potent tripeptide scaffold were scanned and combined with carboxylic acid and acyl sulfonamide C-terminal groups. Inhibition was evaluated and revealed that the structural changes resulted in a loss in potency compared with the alpha-peptide analogues. However, several compounds exhibited muM potency. Inhibition data were compared with modeled ligand-protein binding poses to understand how changes in ligand structure affected inhibition potency. The P(3) position seemed to be the least sensitive position for beta-amino acid substitution. Moreover, the importance of a proper oxyanion hole interaction for good potency was suggested by both inhibition data and molecular modeling. To gain further insight into the structural requirements for potent inhibitors, a three-dimensional quantitative structure-activity relationship (3D-QSAR) model has been constructed using comparative molecular field analysis (CoMFA). The most predictive CoMFA model has q(2)=0.48 and r(pred)(2)=0.68.     

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.     

QSAR studies for the inhibition of the transmembrane isozymes XII and XIV of human carbonic anhydrase with a series of sulfonamides

A diverse series of aromatic/heterocyclic sulfonamides possessing inhibitory action against the human transmembrane isoforms XII (cancer-associated) and XIV of the metalloenzyme carbonic anhydrase (CA, EC 4.2.1.1) has been used to develop QSAR models. Including all the 55 investigated sulfonamides in the calibration set, the predictive qualities of the QSAR equations were weak (r(2)=0.1771, F=5.70) for CA XII and good for CA XIV inhibition (r(2)=0.8222, F=57.04 before eliminating the outliers, and r(2)=0.8911, F=67.07 after eliminating them). The obtained models suggest a slightly different inhibition mechanism for the two isoforms. 3-Halogeno-4-amino-benzenesulfonamides were outliers for scaffold hopping for the inhibition of CA XIV. CA XIV inhibitory activity was proportional to the degree of molecular surface rugosity. For compounds of the type X-Ar-SO(2)NH(2) and Ar'-Ar-SO(2)NH(2) type, best inhibitors were detected when Ar/Ar' incorporates a heterocyclic moiety. These studies may be helpful for the design of more specific CA XII/XIV inhibitors, since this is the first QSAR model investigating them.     

Design, syntheses and 3D-QSAR studies of novel N-phenyl pyrrolidin-2-ones and N-phenyl-1H-pyrrol-2-ones as protoporphyrinogen oxidase inhibitors

The characteristics of low application rates, good crop selectivity, low residue and environmental safety exhibited by Protoporphyrinogen oxidase (PPO, EC 1.3.3.4)-inhibiting herbicides have attracted a world-wide research interests. As continuation of our research work on the development of new PPO inhibitors, a series of mono-carbonyl analogues of cyclic imides, N-phenyl pyrrolidin-2-ones and N-phenyl-1H-pyrrol-2-ones, were designed and synthesized based on previously established DFT-QSAR results. The PPO inhibition activities of 29 newly synthesized compounds were tested and a predictive comparative molecular field analysis (CoMFA) model was established with the conventional correlation coefficient r(2)=0.980 and the cross-validated coefficient q(2)=0.518. According to the CoMFA model, the substituent effects on the PPO inhibition activity were explained reasonably. Further greenhouse assay showed that 2-(4-chloro-2-fluoro-5-propoxy-phenyl)-2,3,4,5,6,7-hexahydro-isoindol-1-one (C(6), k(i)=0.095μM) and 2-(5-allyloxy-4-chloro-2-fluorophenyl)-2,3,4,5,6,7-hexahydro-isoindol-1-one (C(7), k(i)=0.12μM) displayed excellent post-emergency herbicidal activity at the concentration of 150g.ai/ha against seven tested weeds. Due to their high PPO inhibition effect and broad spectrum herbicidal activity, these two compounds have the potential for further study on crop selectivity and field trial. These results confirmed once again that only one of the carbonyl groups of cyclic imides is essential to the PPO inhibition activity.     

Computational characterisation of the interactions between human ST6Gal I and transition‐state analogue inhibitors: insights for inhibitor design

Human β‐galactoside α‐2,6‐sialyltransferase I (hST6Gal I) catalyses the synthesis of sialylated glycoconjugates involved in cell–cell interactions. Overexpression of hST6Gal I is observed in many different types of cancers, where it promotes metastasis through altered cell surface sialylation. A wide range of sialyltransferase (ST) inhibitors have been developed based on the natural donor, cytidine 5′‐monophosphate N‐acetylneuraminic acid (CMP‐Neu5Ac). Of these, analogues that are structurally similar to the transition state exhibit the highest inhibitory activity. In order to design inhibitors that are readily accessible synthetically and with favourable pharmacokinetic properties, an investigation of the replacement of the charged phosphodiester‐linker, present in many ST inhibitors, with a potential neutral isostere such as a carbamate or a 1,2,3‐triazole has been undertaken. To investigate this, molecular docking and molecular dynamics simulations were performed. These simulations provided an insight into the binding mode of previously reported phosphodiester‐linked ST inhibitors and demonstrated that targeting the proposed sialyl acceptor site is a viable option for producing selective inhibitors. The potential for a carbamate‐ or triazole‐linker as an isosteric replacement for the phosphodiester in transition‐state analogue ST inhibitors was established using molecular docking. Molecular dynamics simulations of carbamate‐ and phosphodiester‐linked compounds revealed that both classes exhibit consistent interactions with hST6Gal I. Overall, the results obtained from this study provide a rationale for synthetic and biological evaluation of triazole‐ and carbamate‐linked transition‐state analogue ST inhibitors as potential new antimetastatic agents. Copyright © 2015 John Wiley & Sons, Ltd.     

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 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.