Comparative antioxidant activity of individual herbal components used in Ayurvedic medicine

Four aqueous extracts from different parts of medicinal plants used in Ayurveda (an ancient Indian Medicine) viz., Momardica charantia Linn (AP1), Glycyrrhiza glabra (AP2), Acacia catechu (AP3), and Terminalia chebula (AP4) were examined for their potential as antioxidants. The antioxidant activity of these extracts was tested by studying the inhibition of radiation induced lipid peroxidation in rat liver microsomes at different doses in the range of 100-600 Gy as estimated by thiobarbituric acid reactive substances (TBARS). Of all these extracts, AP4 showed maximum inhibition in the TBARS formation and hence is considered the best antioxidant among these four extracts. The extracts were found to restore antioxidant enzyme superoxide dismutase (SOD) from the radiation induced damage. The antioxidant capacities were also evaluated in terms of ascorbate equivalents by different methods such as cyclic voltammetry, decay of ABTS(.-) radical by pulse radiolysis and decrease in the absorbance of DPPH radicals. The results were found to be in agreement with the lipid peroxidation data and AP4 showed maximum value of ascorbate equivalents. Therefore AP4, with high antioxidant activity, is considered as the best among these four extracts.     

Clustering of protein structural fragments reveals modular building block approach of nature

Structures of peptide fragments drawn from a protein can potentially occupy a vast conformational continuum. We co-ordinatize this conformational space with the help of geometric invariants and demonstrate that the peptide conformations of the currently available protein structures are heavily biased in favor of a finite number of conformational types or structural building blocks. This is achieved by representing a peptides' backbone structure with geometric invariants and then clustering peptides based on closeness of the geometric invariants. This results in 12,903 clusters, of which 2207 are made up of peptides drawn from functionally and/or structurally related proteins. These are termed "functional" clusters and provide clues about potential functional sites. The rest of the clusters, including the largest few, are made up of peptides drawn from unrelated proteins and are termed "structural" clusters. The largest clusters are of regular secondary structures such as helices and beta strands as well as of beta hairpins. Several categories of helices and strands are discovered based on geometric differences. In addition to the known classes of loops, we discover several new classes, which will be useful in protein structure modeling. Our algorithm does not require assignment of secondary structure and, therefore, overcomes the limitations in loop classification due to ambiguity in secondary structure assignment at loop boundaries.