Synthesis and structure–activity relationship of nuciferine derivatives as potential acetylcholinesterase inhibitors

Acetylcholinesterase inhibitors (AChEIs) are currently the best available pharmacotherapy for Alzheimer patients, but because of bioavailability issues, there is still great interest in discovering better AChEIs. The aporphine alkaloid is an important class of natural products, which shows diverse biological activity, such as acetylcholinesterase inhibitory activity. To find new lead AChEIs compounds, eight aporphine alkaloids were synthesized by O-dealkylation, N-dealkylation, and ring aromatization reactions using nuciferine as raw material. The anti-acetylcholinesterase activity of synthesized compounds was measured using modified Ellman’s method. The results showed that some synthesized compounds exhibited higher affinity to AChE than the parent compound nuciferine. Among these compounds, 1,2-dihydroxyaporphine (2) and dehydronuciferine (5) were the most active compounds (IC₅₀ = 28 and 25 μg/mL, respectively). Preliminary analysis of structure–activity relationships suggested that aromatization of the C ring, the presence of the alkoxyl group at C1 and the hydroxy group at C2 position as well as the alkyl substituent at the N atom were favorable to the acetylcholinesterase inhibition. Molecular docking was also applied to predict the binding modes of compounds 1, 2, and 9 into the huperzine A binding site of AChE.     

Docking and three-dimensional quantitative structure–activity relationship analyses of imidazole and thiazolidine derivatives as Aurora A kinase inhibitors

Aurora A kinase is involved in the inactivation of apoptosis leading to ovarian, breast, colon, and pancreatic cancers. Inhibitors of Aurora A kinase promote aberrant mitosis resulting in arrest at a pseudo G1 state to induce mitotic catastrophe, ultimately leading to apoptosis. In this study, ligand-based and docking-based three-dimensional quantitative structure–activity relationship (3D-QSAR) analyses of imidazole and thiazolidine derivatives as potential Aurora A kinase inhibitors were performed. The results provided highly reliable and predictive 3D-QSAR comparative molecular similarity index analysis (CoMSIA) models with a cross-validated q² value of 0.768, non-cross-validated r² value of 0.983, and predictive coefficient \({\text{r}}_{\text{pred}}^{2}\) value of 0.978. CoMSIA contour maps suggested that the NH and benzyl hydroxy groups in R₉, and the CO group in the thiazolidine ring and pyridine ring were important components for biological activity. The maps also suggest that the introduction of hydroxy groups at C₂ of the imino-phenyl ring, C₅ in the pyridine ring, or the substitution of the imino-phenyl ring for the imino-2-pyridine ring could be applied to enhance biological activity.     

Three-dimensional quantitative structure–activity relationship (CoMSIA) analysis of bis-coumerine analogues as urease inhibitors

As a basis for predicting structural features that may lead to the design of more potent and selective inhibitors of urease, the three-dimensional quantitative structure–activity relationship (3D-QSAR) studies were carried out on a series of 30 bis-coumerine analogs, which are known urease inhibitors. Five different properties: steric, electrostatic, hydrophobic, H-bond donor, and H-bond acceptor, assumed to cover the major contributions to ligand binding, were used to generate the 3D-QSAR model. A significant cross-validated correlation coefficient q2 (0.51), r ² (0.962) for CoMSIA were obtained, indicating the statistical significance of this class of compounds. Actual urease inhibitory activities of this class, and the predicted values were in good agreement with the experimental results. This model offer insight into the structural requirements for activity of bis-coumerine analogues as urease inhibitors, since there is only speculative knowledge of their target in protein.     

The imidazolidone analogs as phospholipase D1 inhibitors: analysis of the three-dimensional quantitative structure–activity relationship

Phospholipase D1 (PLD1) is one of the important enzymes in cell proliferation, apoptosis, and tumor progression. Quantitative structure–activity relationship (QSAR) analysis of PLD1 inhibitors was performed to obtain a good predictive model for providing structural rationale for the activity of inhibitors. The 3D-QSAR analysis was carried out on 31 imidazolidone-based analogs of PLD1 inhibitors in the training set. The molecular field analysis (MFA) with G/PLS method was used to generate a statistically significant 3D-QSAR model (r ²?=?0.930) based on molecular field generated by electrostatic and steric probes. The QSAR model was validated using leave-one-out cross-validation, bootstrapping and randomization methods, and finally with an external test set comprising nine inhibitors. The analysis of the best MFA model provided insights into possible modifications for the rational design of imidazolidone analogs as PLD1 inhibitors for better activity.     

Synthesis and structure–activity relationship of acylthiourea derivatives as inhibitors of microsomal epoxide hydrolase

Microsomal epoxide hydrolase (mEH) is a liver enzyme involved in hepatic and extrahepatic metabolism of xenobiotics, namely, the hydrolysis of epoxides and arene oxides to the corresponding diols. In some cases, the action of mEH activates xenobiotics, such as 7,12-dimethylbenz[a]anthracene, potentiating their ability to induce mammary, ovarian, skin, and other types of cancer according to Rajapaksa et al. (Toxicol. Sci 96:327–334, 2006). Similarly, mEH polymorphisms have been linked to several types of cancer as stated by Benhamou et al. (Cancer Res. 58:5291–5293, 1998), and also to emphysema according to Smith and Harrison (Lancet 350:630–633, 1997). mEH inhibitors would provide insight into the multiple roles of this enzyme and potentially have clinical relevance for preventing disease in high-risk individuals. In this article, we describe the design and synthesis of acylthiourea analogs as inhibitors of mEH.     

Docking and quantitative structure–activity relationship studies for imidazo[1,2-a]pyrazines as inhibitors of checkpoint kinase-1

We have performed docking of imidazo[1,2-a]pyrazines complexed with checkpoint kinase1 (Chk1) to better understand the structural requirements and preferred conformations of these inhibitors. The study was performed on a selected set of 33 compounds with variation in structure and activity. In addition, the predicted inhibitor concentrations (IC₅₀) of the imidazo[1,2-a]pyrazines as Chk1 inhibitors were obtained by comparative molecular similarity analysis (CoMSIA). The best CoMSIA model included electrostatic and hydrophobic fields, had a good Q ² value of 0.589, and adequately predicted the compounds contained in the test set. Furthermore, plots of the CoMSIA fields allowed conclusions to be drawn for the selection of suitable inhibitors.     

3D quantitative structure–activity relationship for quinoline, benzimidazole and benzofuran-based analogs as phosphodiesterases IV (PDE-IV) inhibitors

PDE-IV is one of the important targets in the treatment of asthma, COPD, and rheumatoid arthritis. In the search for novel PDE-IV inhibitors a 3D-QSAR study was performed on PDE-IV inhibitors by means of pharmacophore mapping using PHASE, Schrödinger-9. The 3D-QSAR obtained from AAHHRR-1024 hypothesis was found to be statistically significant with r ² = 0.9766 and q ² = 0.8759 with 7 PLS factors. The statistical significance of the model was confirmed by a very low value of RMSE 0.4795. The "Pearson-R" value of 0.9376 suggests a very good predictive ability of the hypothesis generated. The present study demonstrates a robust 3D-QSAR model of PDE-IV inhibitor with the help of AAHHRR-1024 hypothesis, which will help in designing novel inhibitors.     

Structure–toxicity relationship and structure–activity relationship study of 2-phenylaminophenylacetic acid derived compounds

2-Phenylaminophenylacetic acid is a widely-exploited chemical scaffold whereby notable NSAIDs such as diclofenac and lumiracoxib were derived. Yet, their clinical usage has been associated with toxicities in the liver. While some studies have attributed toxicities to the bioactivation of both drugs to reactive intermediates, the structural predisposition for toxicity, as well as relationship between this toxicity and COX inhibitory activity has not been elucidated. In this study, we aimed to address their intricate link by synthesizing compounds that possess the 2-phenylaminophenylacetic acid backbone with varying alkyl and halogen substituents at three positions critical to the COX inhibitory pharmacophore. These compounds were subjected to cytotoxicity testing on two liver cell lines of contrasting metabolic competencies. We observed higher toxicity in the more metabolically competent cell line, supporting the role of bioactivation as a prerequisite for toxicity. We have also shown that structural changes on the chemical scaffold exerted pronounced effect on liver cytotoxicity. The most lipophilic and brominated compound (24) was identified as the most cytotoxic of all the compounds. A concurrent determination of their pharmacological activity using COX inhibition assays allowed us to derive a safety profile, which showed that selectivity towards COX-2 negatively affected activity and toxicity.     

Three-dimensional quantitative structure–activity relationship CoMFA/CoMSIA on pyrrolidine-based tartrate diamides as TACE inhibitors

A series of pyrrolidine-based tartrate diamides having selective tumor necrosis factor-α converting enzyme (TACE) inhibitory activity was selected for the three-dimensional quantitative structure–activity relationship (3D-QSAR) studies. Total 76 compounds were selected by considering a high deviation in the biological activity and structural variations. The quality and predictive power of 3D-QSAR, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models for the atom-based, centroid/atom-based, data-based alignments were performed. Various models were developed with the help of these alignments. The best model was developed with data-based alignment. The optimal predictive CoMFA model was obtained with cross-validated r ² = 0.53 with six component, non-cross-validated r ² = 0.94, standard error of estimates 0.23, F-value = 121.98 and optimal CoMSIA model was obtained with cross-validated r ² = 0.53 with five components, non-cross-validated r ² = 0.93, standard error of estimates = 0.24 and F-value = 138.83. These models also showed the best test set prediction with predictive r ² value of 0.65 and 0.73, respectively. Thus, on the basis of predictive power COMSIA model appeared to be the best one. The statistical parameters from these models indicate that the data are being well fitted and also have high predictive ability. Moreover, the resulting 3D-CoMFA/CoMSIA contour maps provide useful guidance for designing of highly active TACE inhibitors.     

Inhibitory effect and structure–activity relationship of some Biginelli-type pyrimidines against HSV-1

Inevitable emergence of multi-drug resistant strains to current available drugs makes an impetus for finding new therapeutic agents against herpes simplex virus (HSV). In this study, a series of novel derivatives of Biginelli-type pyrimidines were evaluated as potential anti-HSV-1 compounds by plaque reduction method. The cellular toxicity was assessed by XTT proliferation assay. The time course of anti-HSV activity of the most active compound was studied to show the anti-viral effect in various intervals of replication cycle. Compounds 2, 6, 8, 11, 12, 17, 18, 20, and 40 had the highest activity for inhibition of HSV. Compound 40 inhibited HSV replication with IC₅₀ of 0.9 μmol/l and had CC₅₀ of up to 100 μmol/l. This compound was a noteworthy inhibitor against HSV with TI value of 111. Compound 20 also showed considerable inhibitory activity with IC₅₀ of 1.8 μmol/l. Result of time-of-addition study showed that compound 40 inhibits HSV replication at a stage after entry of virions to the target cells. Analysis of structure of the studied compounds demonstrated clear relationships with their anti-HSV effects. Some of the compounds seem to be promising candidates for future anti-HSV drug discovery researches. Structural manipulation based on the obtained structure–activity relationships would propose some new leads for anti-HSV drug discovery programs.     

Advances in quantitative structure–activity relationship models of antioxidants

Background: During the past decade a large number of reports described the roles of active oxygen species in the development or exacerbation of various kinds of diseases. The systemic antioxidant defense system often fails to control the excess free radicals. Such a condition necessitates external antioxidant supplementation either in the form of drugs or vitamins. Quantitative structure–activity relationship (QSAR) serves as an effective computational tool for search and design of active molecules that may eventually be synthesized and assayed. Objective/method: This review presents the current knowledge about QSAR studies of diverse groups of molecules with free radical scavenging activity. The QSAR studies summarized here would help to understand the proper mechanism underlying the interaction between the free radicals and antioxidant molecules. Conclusion: The primary determinant factors for potent antioxidant activity include the electronic distribution of the molecules together with their lipophilicity and size and orientation of the substituents attached to the parent molecules. The potency of the antioxidants depends on the degree of reactivity of these molecules with the nearby free radicals and the stability of the oxidized antioxidant molecules thus obtained. The nature of substitution at the parent moiety plays a key role in the design of antioxidant molecules.     

Advances in quantitative structure–activity relationship models of antimalarials

Importance of the field: Malaria still remains one of the deadliest infectious diseases having a tremendous morbidity and mortality impact in the developing world. Computational tools such as quantitative structure–activity relationship (QSAR) studies help medicinal chemists to understand the consistent relationship between antimalarial activity and molecular properties, and design new potent and selective ligands that may act on different classes of antimalarial drug targets so that these compounds may eventually be synthesized and assayed.

Area covered in this review: In the present review, we focus on the current knowledge of QSARs and pharmacophore models of different classes of antimalarial drugs. In this context, we also review the reported docking studies of antimalarial compounds acting on different targets to explore the interaction pattern at the molecular level.

What the reader will gain: The reader will gain an overview of advances of QSAR and related theoretical models of antimalarial drug compounds.

Take home message: This review infers that most of the reported QSAR models are analog based QSARs with a limited applicability domain, but QSAR models based on diverse chemical structures acting on a particular target have been reported in very few cases.