Achintya Saha

Exploring quantitative structure–activity relationship studies of antioxidant phenolic compounds obtained from traditional Chinese medicinal plants

In the present work, quantitative structure–activity relationship (QSAR) models have been built for a wide variety of antioxidant phenolic compounds obtained from traditional Chinese medicinal plants, with their Trolox equivalent antioxidant capacity measured using 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical and 2,2′-azinobis-(3-ethylbenzothiazoline-6-sulphonic acid) radical (ABTS√+) assay methods. Non-linear models obtained using genetic partial least-squares technique were acceptable both in terms of internal and external predictivity. Validation of developed models using metrics and randomisation technique yielded results indicating the predictivity and robustness, respectively, of the developed models. The models signify that the presence of ketonic oxygen within the molecular structure favours their antioxidant activity. In addition, the number of hydroxyl groups, extent of branching, degree of methoxylation and the number of methyl and methylene substituents also dictate the antioxidant activity of these molecules. Thus, the QSAR models developed here can be utilised for the antioxidant activity prediction of a new series of molecules.

Genotoxicity of Sennosides on the Bone Marrow Cells of Mice

Preparations of a number of plants which contain hydroxyanthraquinones as active constituents are used worldwide for their laxative effect. Anthraquinone glycosides of Cassia angustifolia and C. fistula were investigated for their ability to induce a clastogenic effect on the bone marrow cells of Swiss albino mice. The endpoints screened were chromosomal aberrations and frequency of aberrant cells. Oral exposure to doses of these anthraquinones and their equivalent amount in leaf and pod extracts did not induce significant numbers of chromosomal aberrations or aberrant cells. The results indicate that anthraquinone sennoside B and rhein are weakly genotoxic.

Quantitative structure-activity relationship modeling of antioxidant activities of hydroxybenzalacetones using quantum chemical, physicochemical and spatial descriptors.

We have modeled antioxidant activities of hydroxybenzalacetones against lipid peroxidation induced by t‐butyl hydroperoxide (pC1), γ‐irradiation (pC2) and also their 1,1‐diphenyl‐2‐picryl hydrazyl (DPPH) free radical scavenging activity (pC3) using quantitative structure–activity relationship technique. The quantitative structure–activity relationship models were developed using different statistical methods like stepwise multiple linear regression, genetic function approximation and genetic partial least squares with descriptors of different categories (quantum chemical, physicochemical, spatial and substituent constants). The models were validated by internal validation and randomization techniques. The model predictivity was judged on the basis of their cross‐validated squared correlation coefficient (Q2) and modified r2 () values. The best models for the two responses, pC1 and pC2, were obtained by genetic partial least squares technique while the best model for the third response, pC3, was obtained by genetic function approximation technique. The developed models suggest that the distribution of charges on the phenolic nucleus and the phenolic oxygen as well as the charged surface areas of the molecules together with the geometry and orientation of the substituents significantly influence all the three types of responses (pC1, pC2 and pC3). The developed models may be used to design hydroxybenzalacetones with better antioxidant activities.

Pharmacophore mapping of arylamino-substituted benzo[b]thiophenes as free radical scavengers

AbstractPredictive pharmacophore models have been developed for a series of arylamino-substituted benzo[b]thiophenes exhibiting free radical scavenging activity. 3D pharmacophore models were generated using a set of 20 training set compounds and subsequently validated by mapping 6 test set compounds using Discovery Studio 2.1 software. Further model validation was performed by randomizing the data using Fischer’s validation technique at the 95% confidence level. The most predictive pharmacophore model developed using the conformers obtained from the BEST method showed a correlation coefficient (r) of 0.942 and consisted of three features: hydrogen bond donor, hydrogen bond acceptor and aromatic ring. Acceptable values of external validation parameters, like

Chemometric QSAR modeling and in silico design of antioxidant NO donor phenols.

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Comparative validated molecular modeling of p53-HDM2 inhibitors as antiproliferative agents.

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Molecular shape analysis of antioxidant and squalene synthase inhibitory activities of aromatic tetrahydro-1,4-oxazine derivatives.

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