QSAR study of substituted 1,3,4-oxadiazole naphthyridines as HIV-1 integrase inhibitors

Molecular Descriptors and QSAR Models for Sedative Activity of Sesquiterpenes Administered to Mice via Inhalation

Essential oils are often utilized for therapeutic purposes and are composed of complex structural molecules, including sesquiterpenes, with high molecular weight and potential for stereochemistry. A detailed study on the properties of selected sesquiterpenes was conducted as part of a broader investigation on the effects of sesquiterpenes on the central nervous system. A set of 18 sesquiterpenes, rigorously selected from an original list of 114, was divided into 2 groups i.e., the training and test sets, with each containing 9 compounds. The training set was evaluated for the sedative activity in mice through inhalation, and all compounds were sedatives at any dose in the range of 4 × 10-4-4 × 10-2 mg/cage, except for curzerene. Molecular determinants of the sedative activities of sesquiterpenes were evaluated using quantitative structure-activity relationship (QSAR) and structure-activity relationship (SAR) analyses. An additional test set of six compounds obtained from the literature was utilized for validating the QSAR model. The parental carbonyl cation and an oxygen-containing groups are possible determinants of sedative activity. The QSAR study using multiple regression models could reasonably predict the sedative activity of sesquiterpenes with statistical parameters such as the correlation coefficient r2 = 0.82 > 0.6 and q2 LOO = 0.71 > 0.5 obtained using the leave-one-out cross-validation technique. Molar refractivity and the number of hydrogen bond acceptors were statistically important in predicting the activities. The present study could help predict the sedative activity of additional sesquiterpenes, thus accelerating the process of drug development.

Quantitative structure activity relationship (QSAR) modeling study of some novel thiazolidine 4-one derivatives as potent anti-tubercular agents

This study aims to develop a QSAR model for Antitubercular activity. The quantitative structure-activity relationship (QSAR) approach predicted the thiazolidine-4-ones derivative's Antitubercular activity. For the QSAR study, 53 molecules with Antitubercular activity on H37Rv were collected from the literature. Compound structures were drawn by ACD/Labs ChemSketch. The energy minimization of the 2D structure was done using the MM2 force field in Chem3D pro. PaDEL Descriptor software was used to construct the molecular descriptors. QSARINS software was used in this work to develop the 2D QSAR model. A series of thiazolidine 4-one with MIC data were taken from the literature to develop the QSAR model. These compounds were split into a training set (43 compounds) and a test set (10 compounds). The PaDEL software calculated 2300 descriptors for this series of thiazolidine 4-one derivatives. The best predictive Model 4, which has R2 of 0.9092, R2adj of 0.8950 and LOF parameter of 0.0289 identify a preferred fit. The QSAR study resulted in a stable, predictive, and robust model representing the original dataset. In the QSAR equation, the molecular descriptor of MLFER_S, GATSe2, Shal, and EstateVSA 6 positively correlated with Antitubercular activity. While the SpMAD_Dzs 6 is negatively correlated with Antitubercular activity. The high polarizability, Electronegativities, Surface area contributions and number of Halogen atoms in the thiazolidine 4-one derivatives will increase the Antitubercular activity.

A Four-Component Domino Reaction: An Eco-Compatible and Highly Efficient Construction of 1,8-Naphthyridine Derivatives, Their In Silico Molecular Docking, Drug Likeness, ADME, and Toxicity Studies

A multicomponent domino reaction of enaminone, malononitrile, and o-phthalaldehyde has been established, providing direct access to novel highly functionalized pentacyclic cyclopenta [b] indeno [1, 2, 3-de] [1,8] naphthyridine derivatives. The simplicity of execution, readily available substrates, high yields, excellent functional group tolerance, scalability, and good scores of environmental parameters make this synthetic strategy more sustainable and worthy of further attention. This one-pot transformation, which involved multiple steps and did not require the use of a catalyst, constructed four new C-C bonds, two new C-N bonds, and three new rings, with efficient use of all reactants. Furthermore, we performed in silico molecular docking analysis for prediction of anticancer (against human topoisomerase IIβ protein) and antimicrobial (against E.coli. DNA gyrase B protein) activities. Drug likeness and ADMET studies were also predicted. Overall investigation indicates that compound 6i may serve as a candidate that could be developed as potential anticancer and antimicrobial agent among all.

Quantitative structure–activity relationships study of potent pyridinone scaffold derivatives as HIV-1 integrase inhibitors with therapeutic applications

Human immunodeficiency virus-1 (HIV-1) integrase appears to be a crucial target for developing new anti-HIV-1 therapeutic agents. Different quantitative structure–activity relationships (QSARs) algorithms have been used in order to develop efficient model(s) to predict the activity of new pyridinone derivatives against HIV-1 integrase. Multiple linear regression (MLR) and combined principal component analysis (PCA) with MLR have been applied to build QSAR models for a set of new pyridinone derivatives as potent anti-HIV-1 therapeutic agents. Four different approaches based on MLR method including; concrete-MLR, stepwise-MLR, concrete PCA–MLR and stepwise PCA–MLR were utilized for this aim. Twenty two different sets of descriptors containing 1613 descriptors were constructed for each optimized molecule. Comparison between predictability of the “concrete” and “stepwise” procedure in two different algorithms of MLR and PCA models indicated the advantage of the stepwise procedure over that of the simple concrete method. Although the PCA was employed for dimension reduction, using stepwise PCA–MLR model showed that the method has higher ability to predict the compounds’ activity. The stepwise PCA–MLR model showed highly validated statistical results both in fitting and prediction processes ([Formula: see text] and [Formula: see text]). Therefore, using stepwise PCA approach is suitable to remove ineffective descriptors, which results in remaining efficient descriptors for building good predictability stepwise PCA–MLR. The stepwise hybrid approach of PCA–MLR may be useful in derivation of highly predictive and interpretable QSAR models.

Synthesis and Biological Activities of Ethyl 2-(2-pyridylacetate) Derivatives Containing Thiourea, 1,2,4-triazole, Thiadiazole and Oxadiazole Moieties

Thirty six novel heterocyclic derivatives of ethyl 2-(2-pyridylacetate) were efficiently synthesized. The new compounds involve the linkage of a 2-pyridyl ring with thiosemicarbazide (compounds 1–7), 1,2,4-triazole (compounds 1a–7a), 1,3,4-thiadiazole (compounds 1b–7b), and 1,3,4-oxadiazole (compounds 1f–7f) moieties. The last group of compounds 1e–7e involves the connection of a 2-pyridyl ring with 1,2,4-triazole and thiourea. ¹H-NMR, ¹³C-NMR and MS methods were used to confirm the structures of the obtained derivatives. The molecular structures of 3, 3b, 7a and 7f were further confirmed by X-ray crystallography. All obtained compounds were tested in vitro against a number of microorganisms, including Gram-positive cocci, Gram-negative rods and Candida albicans. In addition, the obtained compounds were tested for cytotoxicity and antiviral activity against HIV-1.

Domino synthesis of functionalized 1,6-naphthyridines and their in vitro anti-inflammatory and anti-oxidant efficacies

One-pot and multicomponent reaction of ketones with malononitrile and pyrrolidine in ethanol affords 1,6-naphthyridines.

Design, synthesis, and herbicidal activity of novel substituted 3-(pyridin-2-yl)benzenesulfonamide derivatives

A series of novel substituted 3-(pyridin-2-yl)benzenesulfonamide derivatives were designed and synthesized using 2-phenylpridines as the lead compound by intermediate derivatization methods in an attempt to obtain novel compound candidates for weed control. The herbicidal activity assay in glasshouse tests showed several compounds (II6, II7, II8, II9, II10, II11, III2, III3, III4, and III5) could efficiently control velvet leaf, youth-and-old age, barnyard grass, and foxtail at the 37.5 g/ha active substance. Especially, the activities of II6, II7, III2, and III4 were proved roughly equivalent to the saflufenacil and better than 95% sulcotrione at the same concentration. The result of the herbicidal activity assay in field tests demonstrated that II7 at 60 g/ha active substance could give the same effect as bentazon at 1440 g/ha active substance to control dayflower and nightshade, meanwhile II7 showed better activity than oxyfluorfen to control arrowhead and security to rice. The present work indicates that II7 may be a novel compound candidate for potential herbicide.

QSAR studies for the computational prediction of HMG-CoA reductase inhibitors by genetic function approximation technique

Two-dimensional quantitative structure−activity relationship (2D-QSAR) models are useful in understanding how chemical structure is related to the biological activity of natural and synthetic chemicals. Also, they could be usefully employed for designing newer and better therapeutics. A 2D-QSAR study was performed for 52 compounds of a series of thiophenyl quinolines and α-asarone derivatives as potential hypocholesterolemic inhibitors using different types of physicochemical descriptors, which correlated significantly with the activity. Linear QSAR models were developed using multiple linear regression, where the genetic algorithm (genetic function approximation technique) was adopted for selecting the most appropriate descriptors. The results are discussed on the basis of regression data and the cross-validation technique. Model A is the best 2D-QSAR model describing the inhibition efficiency of HMG-CoA reductase with cross-validated squared correlation coefficient (Q 2 = 0.700) and the squared correlation coefficient (R 2 = 0.752), which is able to describe 70% of the variance in the experimental activity. The good agreement between the experimental and the predicted values of pIC50 (micromoles per litre) (R = 0.876) confirms the reliability and the predictability of the proposed model. The results obtained from the present QSAR study explained the importance of the electronic, structural, spatial, and electrotopological descriptors in enhancing the biological activity of the investigated inhibitors.

Designing hypothesis of substituted benzoxazinones as HIV-1 reverse transcriptase inhibitors: QSAR approach

A linear quantitative structure activity relationship (QSAR) model is presented for predicting human immunodeficiency virus-1 (HIV-1) reverse transcriptase enzyme inhibition. The 2D QSAR and 3D-QSAR models were developed by stepwise multiple linear regression, partial least square (PLS) regression and k-nearest neighbor-molecular field analysis, PLS regression, respectively using a database consisting of 33 recently discovered benzoxazinones. The primary findings of this study is that the number of hydrogen atoms, number of (-NH2) group connected with solitary single bond alters the inhibition of HIV-1 reverse transcriptase. Further, presence of electrostatic, hydrophobic and steric field descriptors significantly affects the ability of benzoxazinone derivatives to inhibit HIV-1 reverse transcriptase. The selected descriptors could serve as a primer for the design of novel and potent antagonists of HIV-1 reverse transcriptase.