3D-QSAR Studies on Barbituric Acid Derivatives as Urease Inhibitors and the Effect of Charges on the Quality of a Model

Functionalized Homologues and Positional Isomers of Rabbit 15-Lipoxygenase RS75091 Inhibitor

BACKGROUND

RS75091 is a cinnamic acid derivative that has been used for the crystallization of the rabbit ALOX15-inhibitor complex. The atomic coordinates of the resolved ALOX15-inhibitor complex were later used to define the binding sites of other mammalian lipoxygenase orthologs, for which no direct structural data with ligand has been reported so far.

INTRODUCTION

The putative binding pocket of the human ALOX5 was reconstructed on the basis of its structural alignment with rabbit ALOX15-RS75091 inhibitor. However, considering the possible conformational changes the enzyme may undergo in solution, it remains unclear whether the existing models adequately mirror the architecture of the ALOX5 active site.

METHODS

In this study, we prepared a series of RS75091 derivatives using a Sonogashira coupling reaction of regioisomeric bromocinnamates with protected acetylenic alcohols and tested their inhibitory properties on rabbit ALOX15.

RESULTS

A bulky pentafluorophenyl moiety linked to either ortho- or metha-ethynylcinnamates via aliphatic spacer does not significantly impair the inhibitory properties of RS75091.

CONCLUSION

Hydroxylated 2- and 3-alkynylcinnamates may be suitable candidates for incorporation of an aromatic linker group like tetrafluorophenylazides for photoaffinity labeling assays.

Monte-Carlo method-based QSAR model to discover phytochemical urease inhibitors using SMILES and GRAPH descriptors

Urease inhibitors are known to play a vital role in the field of medicine as well as agriculture. Special attention is attributed to the development of novel urease inhibitors with a view to treat the Helicobacter pylori infection. Amongst a number of urease inhibitors, a large number of molecules fail in vivo and in clinical trials due to their hydrolytic instability and toxicity profile. The search for potential inhibitors may require screening of large and diverse databases of small molecules and to design novel molecules. We developed a Monte-Carlo method-based QSAR model to predict urease inhibiting potency of molecules using SMILES and GRAPH descriptors on an existing diverse database of urease inhibitors. The QSAR model satisfies all the statistical parameters required for acceptance as a good model. The model is applied to identify urease inhibitors among the wide range of compounds in the phytochemical database, NPACT, as a test case. We combine the ligand-based and structure-based drug discovery methods to improve the accuracy of the prediction. The method predicts pIC₅₀ and estimates docking score of compounds in the database. The method may be applied to any other database or compounds designed in silico to discover novel drugs targeting urease.Communicated by Ramaswamy H. Sarma.

Enzyme Inhibitory Kinetics and Molecular Docking Studies of Halo-Substituted Mixed Ester/Amide-Based Derivatives as Jack Bean Urease Inhibitors

A series of halo-substituted mixed ester/amide-based analogues 4a-l have been prepared as jack bean urease inhibitor, which showed good to excellent inhibition of enzyme activity. The role of halo-substituted benzoyl moieties and alkyl substituted anilines in urease inhibitory kinetics was also investigated. The alkyl-substituted anilines 1a-b reacted with chloroacetyl chloride to afford intermediates 2a-b, which were then reacted with different halo-substituted benzoic acids 3a-f to prepare the title compounds 4a-l. The chemical structures of final products 4a-l were ascertained by FTIR, 1H NMR, 13C NMR, and mass spectra. The compound 4b showed remarkable activity with IC501.6 ± 0.2 nM, better than the standard thiourea having IC50472.1 ± 135.1 nM. The 2-chloro-substituted phenyl ring on one side of compound 4b and 4-isopropyl-substituted benzene on the other side play an essential role in inhibition of urease activity. Lineweaver-Burk plots (kinetics study) indicated about 4b derivative as a mixed type of inhibitor. The virtual screening performed against urease enzyme (PDBID 4H9M) showed that compounds 4b and 4e have binding energies of -7.8 and -7.9 Kcal/mol, respectively. Based upon our results, it was found that derivative 4b is a highly potent urease inhibitor, better than the standard thiourea.

Quantum mechanics and 3D-QSAR studies on thienopyridine analogues: inhibitors of IKKβ

Inhibitor of kappa B kinase subunit β (IKKβ) is a main regulator of nuclear factor kappa B (NF-κB) and has received considerable attention as an attractive therapeutic target for the treatment of lung cancer or other inflammatory disease. A group of diversified thienopyridine derivatives exhibited a wide range of biological activity was used to investigate its structural requirements by using DFT and 3D-Quantitative structure activity relationship. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were established using the experimental activity of thienopyridine derivatives. The cross-validation coefficient (q2) values for CoMFA and CoMSIA are 0.671 and 0.647 respectively, were achieved, demonstrating high predictive capability of the model. The contour analysis indicate that presence of hydrophobic and electrostatic field is highly desirable for biological activity. The results indicate that substitution of hydrophobic group with electron withdrawing effect at R4 and R6 position have more possibility to increase the biological activity of thienopyridine derivatives. Subsequently molecular docking and DFT calculation were performed to assess the potency of the compounds.

Two- and three-dimensional QSAR studies on hURAT1 inhibitors with flexible linkers: topomer CoMFA and HQSAR

hURAT1 (human urate transporter 1) is a successful target for hyperuricemia. Recently, the modification work on hURAT1 inhibitors showed that the flexible linkers would benefit biological activity. The study aimed to investigate the contribution of the linkers and give modification strategies on this kind of structures based on QSAR models (HQSAR and topomer CoMFA). The most effective HQSAR and topomer CoMFA models were generated by applying the training set containing 63 compounds, with the cross-validated q² values of 0.869/0.818 and the non-cross-validated correlation coefficients r² of 0.951/0.978, respectively. The Y-randomization test was applied to ensure the robustness of the models. The external predictive correlation coefficient (r_pred²) grounded on the external test set (21 compounds) of two models was 0.910 and 0.907, respectively. In addition, the models were validated by Golbraikh-Tropsha and Roy methods, as well as other statistical metrics. The results showed that both models were reliable. Topomer CoMFA steric/electrostatic contours and HQSAR atomic contribution maps illustrated the structural features which governed their inhibitory potency. The dependable results could provide important insights to guide the designing of more potential hURAT1 inhibitors.

Investigations of Structural Requirements for BRD4 Inhibitors through Ligand- and Structure-Based 3D QSAR Approaches

The bromodomain containing protein 4 (BRD4) recognizes acetylated histone proteins and plays numerous roles in the progression of a wide range of cancers, due to which it is under intense investigation as a novel anti-cancer drug target. In the present study, we performed three-dimensional quantitative structure activity relationship (3D-QSAR) molecular modeling on a series of 60 inhibitors of BRD4 protein using ligand- and structure-based alignment and different partial charges assignment methods by employing comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) approaches. The developed models were validated using various statistical methods, including non-cross validated correlation coefficient (r²), leave-one-out (LOO) cross validated correlation coefficient (q²), bootstrapping, and Fisher’s randomization test. The highly reliable and predictive CoMFA (q² = 0.569, r² = 0.979) and CoMSIA (q² = 0.500, r² = 0.982) models were obtained from a structure-based 3D-QSAR approach using Merck molecular force field (MMFF94). The best models demonstrate that electrostatic and steric fields play an important role in the biological activities of these compounds. Hence, based on the contour maps information, new compounds were designed, and their binding modes were elucidated in BRD4 protein’s active site. Further, the activities and physicochemical properties of the designed molecules were also predicted using the best 3D-QSAR models. We believe that predicted models will help us to understand the structural requirements of BRD4 protein inhibitors that belong to quinolinone and quinazolinone classes for the designing of better active compounds.

Data Analysis in Chemistry and Bio-Medical Sciences

n/a.