3D-QSAR studies on fluroquinolones derivatives as inhibitors for tuberculosis

A quantitative structure activity relationship (QSAR) study was performed on the fluroquinolones known to have anti-tuberculosis activity. The 3D-QSAR models were generated using stepwise variable selection of the four methods - multiple regression (MR), partial least square regression (PLSR), principal component regression (PCR) and artificial neural networks (kNN-MFA). The statistical result showed a significant correlation coefficient q(2) (90%) for MR model and an external test set of (pred_r(2)) -1.7535, though the external predictivity showed to improve using kNN-MFA method with pred_r(2) of -0.4644. Contour maps showed that steric effects dominantly determine the binding affinities. The QSAR models may lead to a better understanding of the structural requirements of anti-tuberculosis compounds and also help in the design of novel molecules.     

2D-QSAR model development and analysis on variant groups of anti-tuberculosis drugs

A quantitative structure activity relationship study was performed on different groups of anti-tuberculosis drug compound for establishing quantitative relationship between biological activity and their physicochemical /structural properties. In recent years, a large number of herbal drugs are promoted in treatment of tuberculosis especially due to the emergence of MDR (multi drug resistance) and XDR (extensive drug resistance) tuberculosis. Multidrug-resistant TB (MDR-TB) is resistant to front-line drugs (isoniazid and rifampicin, the most powerful anti-TB drugs) and extensively drug-resistant TB (XDR-TB) is resistant to front-line and second-line drugs. The possibility of drug resistance TB increases when patient does not take prescribed drugs for defined time period. Natural products (secondary metabolites) isolated from the variety of sources including terrestrial and marine plants and animals, and microorganisms, have been recognized as having antituberculosis action and have recently been tested preclinically for their growth inhibitory activity towards Mycobacterium tuberculosis or related organisms. A quantitative structure activity relationship (QSAR) studies were performed to explore the antituberculosis compound from the derivatives of natural products . Theoretical results are in accord with the in vitro experimental data with reported growth inhibitory activity towards Mycobacterium tuberculosis or related organisms. Antitubercular activity was predicted through QSAR model, developed by forward feed multiple linear regression method with leave-one-out approach. Relationship correlating measure of QSAR model was 74% (R(2) = 0.74) and predictive accuracy was 72% (RCV(2) = 0.72). QSAR studies indicate that dipole energy and heat of formation correlate well with anti-tubercular activity. These results could offer useful references for understanding mechanisms and directing the molecular design of new lead compounds with improved anti-tubercular activity. The generated QSAR model revealed the importance of structural, thermodynamic and electro topological parameters. The quantitative structure activity relationship provides important structural insight in designing of potent antitubercular agent.     

A structure–activity relationship study of flavonoids as inhibitors of E. coli by membrane interaction effect

Flavonoids exhibit a broad range of biological activities including antibacterial activity. However, the mechanism of their antibacterial activity has not been fully investigated. The antibacterial activity and membrane interaction of 11 flavonoids (including 2 polymethoxyflavones and 4 isoflavonoids) against Escherichia coli were examined in this study. The antibacterial capacity was determined as flavonoids > polymethoxyflavones > isoflavonoids. Using fluorescence, it was observed that the 5 flavonoids rigidified the liposomal membrane, while the polymethoxyflavones and isoflavonoids increased membrane fluidity. There was a significant positive correlation between antibacterial capacity and membrane rigidification effect of the flavonoids. A quantitative structure–activity relationship (QSAR) study demonstrated that the activity of the flavonoid compounds can be related to molecular hydrophobicity (CLogP) and charges on C atom at position3 (C3). The QSAR model could be used to predict the antibacterial activity of flavonoids which could lead to natural compounds having important use in food and medical industry.     

QSAR-based prediction of anti-HCV activity of thiourea derivatives

Quantitative structure–activity relationship (QSAR) studies were performed on a series of thioureas to explore the physico-chemical parameters responsible for their activity against the hepatitis C virus (HCV)-infected AVa5 cell. The physico-chemical parameters were calculated using WIN CAChe 6.1. Multiple linear regression analysis, after the variables selection by factor analysis, was performed to derive QSAR models which were further evaluated for their statistical significance and predictive power by internal and external validation. The developed QSAR model had the correlation coefficient (R) = 0.928 and cross-validated squared correlation coefficient (Q ²) = 0.751. The selected significant QSAR model indicates that hydrophobicity, dielectric energy, valence connectivity index (order 1), conformational minimum energy and highest occupied molecular orbital of the whole molecule play an important role in the anti-HCV activity of thioureas.     

Quantitative analysis of the relationship between structure and antioxidant activity of tripeptides

Peptides from enzymatic hydrolysates of food proteins exhibit significant antioxidant activity. Several studies have attempted to determine the factors contributing to the antioxidant activity of peptides; however, the physicochemical properties and factors essential for the antioxidant activity of peptides are still unclear. In this study, in order to clarify the factors important for peptide antioxidant activity based on the properties of component amino acids, 55 tripeptides were synthesized from 20 natural amino acids and their antioxidant activity was measured using the Trolox equivalent antioxidant capacity (TEAC) assay system. The tripeptides were divided into two data sets: a training set comprising 50 compounds and a validated set comprising five compounds. The structure‐activity relationship of the training set was then analyzed using classical quantitative structure‐activity relationship (QSAR) analysis. The study findings demonstrate that the presence of a cysteine residue at any position, an aromatic amino acid at the C‐terminus, higher hydrophobicity of the N‐terminal residue, and smaller HOMO‐LUMO energy gap of the middle residue can significantly enhance the antioxidant activity. The activities of the five validated compounds were predicted using the constructed QSAR model, and a good correlation between measured and predicted activities was observed. The information obtained from the QSAR model could be useful for effective production of antioxidant peptides from food proteins such as egg white proteins.     

Structure-activity relationships of seco-prezizaane and picrotoxane/picrodendrane terpenoids by Quasar receptor-surface modeling

The seco-prezizaane-type sesquiterpenes pseudoanisatin and parviflorolide from Illicium are noncompetitive antagonists at housefly (Musca domestica) gamma-aminobutyric acid (GABA) receptors. They show selectivity toward the insect receptor and thus represent new leads toward selective insecticides. Based on the binding data for 13 seco-prezizaane terpenoids and 17 picrotoxane and picrodendrane-type terpenoids to housefly and rat GABA receptors, a QSAR study was conducted by quasi-atomistic receptor-surface modeling (Quasar). The resulting models provide insight into the structural basis of selectivity and properties of the binding sites at GABA receptor-coupled chloride channels of insects and mammals.     

Prediction of HIV-1 protease inhibitory activity of 4-hydroxy-5,6-dihydropyran-2-ones: QSAR study

Inhibition of human immunodeficiency virus 1 (HIV-1) protease is an important strategy for the treatment of HIV and acquired immune deficiency syndrome (AIDS). Therefore, HIV-1 protease inhibitory activity of dihydropyranone derivatives has been analyzed with different physico-chemical parameters. In the present work, QSAR studies were performed on a series of 4-hydroxy-5,6-dihydropyran-2-ones to explore the physico-chemical parameters responsible for their HIV-1 protease inhibitory activity. Physico-chemical parameters were calculated using WIN CAChe 6.1. Stepwise multiple linear regression analysis was performed to derive QSAR models which were further evaluated for statistical significance and predictive power by internal and external validation. The selected best QSAR model was having correlation coefficient (R)?=?0.875 and cross-validated squared correlation coefficient (Q²)?=?0.707. The developed significant QSAR model indicates that hydrophobicity of whole molecule and the substituent present at sixth position of dihydropyranones play an important role in the HIV-1 protease inhibitory activities of 4-hydroxy-5,6-dihydropyran-2-ones.     

Three-dimensional quantitative structure–activity relationship (3D-QSAR) of 3-aryloxazolidin-2-one antibacterials

Three-dimensional quantitative structure–activity relationship (3D-QSAR) studies for 3-aryloxazolidin-2-one antibacterials were performed using the genetic function approximation algorithm. This study was performed using 60 compounds, in which the QSAR models were developed using a training set of 50 compounds. The in vitro minimum inhibitory concentration (MIC) against Staphylococcus aureus SFCO-1a was used for the study. The predictive ability of the QSAR model was evaluated by using a test set of 10 compounds. The statistical quality of the QSAR models was assessed using statistical parameters r², r²_cv (cross-validated r²), r²_pred (predictive r²) and lack of fit measure (LOF). The results obtained indicate that the antibacterial activity of the 3-aryloxazolidin-2-ones is strongly dependent on electronic factor as expressed by lowest unoccupied molecular orbital energy (LUMO), spatial factor as expressed by density and thermodynamic factors accounted for by molar refractivity and heat of formation. The model is presently being used to design and predict new potent molecules prior to synthesis.     

Anti-inflammatory, antioxidant and analgesic amides

The synthesis of some new aryl acetic acids and amides and a pharmacochemical study and quantitative structure-activity relationships (QSAR) on them are described. The compounds were screened for their biological activity using the carrageenin induced rat paw oedema model and a significant inhibition of oedema occurred (44.1-80.1%) at a concentration of 0.01 mmol/1 kg. The analgesic activity, based on the inhibition of acetic acid-induced writhing in rats was also found to be significant. The compounds were found to interact with the stable free radical 1,1-diphenylhydrazyl DPPH and with DMSO (for hydroxyl radicals). The compounds were screened for radical scavenging activity with the xanthine/xanthine oxidase system for O2-* and for inhibition of soybean lipoxygenase (LOX). The results are discussed in terms of the structural and physicochemical characteristics of the compounds.     

Computational modeling and design of renin inhibitors

The recently introduced field-based QSAR was employed to develop robust quantitative 3D QSAR models to comprehend the activity of several structurally diverse classes of small molecule renin inhibitors reported in literature. A reasonable predictive model with an r² (pred) of ～0.67 and rmse of 0.79 was achieved for an external validation set of ～150 compounds centered on the model developed using ～450 training set compounds. Based on the developed 3D QSAR models and additional insights gained from reported X-ray structures, opportunity for activity improvements in the [aza]indole scaffold was explored using a carefully designed virtual library of ～2300 compounds. The potential for success of such combined structure-guided and ligand-based approach was justified when the resulting prediction was compared against a representative with supporting experimental results.