Loganathan Arul

Computer-Aided Drug Design for Cancer-Causing H-Ras p21 Mutant Protein

GTP-bound mutant form H-Ras (Harvey-Ras) proteins are found in 30% of human tumors. Activation of H-Ras is due to point mutation at positions 12, 13, 59 and/or 61 codon. Mutant form of H-Ras proteins is continuously involved in signal transduction for cell growth and proliferation through interaction of downstream-regulated protein Raf. In this paper, we have reported the virtual screening of lead compounds for H-Ras P 21 mutant protein from ChemBank and DrugBank databases using LigandFit and DrugBank-BLAST. The analysis resulted in 13 hits which were docked and scored to identify structurally active leads that make similar interaction to those of bound complex of H-Ras P 21 mutant- Raf. This approach produced two different leads, 3-Aminopropanesulphonic acid (docked energy -3.014 kcal/mol) and Hydroxyurea (docked energy -0.009 kcal/mol) with finest Lipinskis rule-of-five. Their docked energy scores were better than the complex structure of H-Ras P 21 mutant protein bound with Raf (1.18 kcal/mol). All the leads were docked into ef- fector region forming interaction with ILE36, GLU37, ASP38 and SER39.

Functional insight for β-glucuronidase in Escherichia coli and Staphylococcus sp. RLH1

Glycosyl hydrolases hydrolyze the glycosidic bond either in carbohydrates or between carbohydrate and non-carbohydrate moiety. The β-glucuronidase (beta D-glucuronoside glucuronosohydrolase; EC 3.2.1.31) enzyme belongs to the family-2 glycosyl hydrolase. The E. coli borne β-glucuronidase gene (uidA) was devised as a gene fusion marker in plant genetic transformation experiments. Recent plant transformation vectors contain a novel β-glucuronidase (gusA) derived from Staphylococcus sp. RLH1 for E. coli uidA. It is known to have a ten fold higher sensitivity compared to E. coli β-glucuronidase. The functional superiority of Staphylococcus (gusA) over E. coli (uidA) activity is not fully known. The comparison of secondary structural elements among them revealed an increased percentage of random coils in Staphylococcus β-glucuronidase. The 3D model of gusA shows catalytic site residues 396Glu, 508Glu and 471Tyr of gusA in loop regions. Accessible surface area (ASA) calculations on the 3D model showed increased ASA for active site residues in Staphylococcus β-glucuronidase. Increased random coil, the presence of catalytic residues in loops, greater solvent accessibility of active residues and increased charged residues in gusA of Staphylococcus might facilitate interaction with the solvent. This hypothesizes the enhanced catalytic activity of β-glucuronidase in Staphylococcus sp. RLH1 compared to that in E. coli.

β‐glucuronidase of family‐2 glycosyl hydrolase: A missing member in plants

Glycosyl hydrolases hydrolyze the glycosidic bond in carbohydrates or between a carbohydrate and a non‐carbohydrate moiety. β‐glucuronidase (GUS) is classified under two glycosyl hydrolase families (2 and 79) and the family‐2 β‐glucuronidase is reported in a wide range of organisms, but not in plants. The family‐79 endo-β-glucuronidase (heparanase) is reported in microorganisms, vertebrates and plants. The E. coli family‐2 β‐glucuronidase (uidA) had been successfully devised as a reporter gene in plant transformation on the basis that plants do not have homologous GUS activity. On the contrary, histochemical staining with X‐Gluc was reported in wild type (non-transgenic) plants. Data shows that, family‐2 β‐glucuronidase homologous sequence is not found in plants. Further, β‐glucuronidases of family‐2 and 79 lack appreciable sequence similarity. However, the catalytic site residues, glutamic acid and tyrosine of the family‐2 β‐glucuronidase are found to be conserved in family‐79 β‐glucuronidase of plants. This led to propose that the GUS staining reported in wild type plants is largely because of the broad substrate specificity of family‐79 β-glucuronidase on X‐Gluc and not due to the family‐2 β‐glucuronidase, as the latter has been found to be missing in plants.

Engineering Disease Resistance in Rice

Rice diseases cause substantial yield loss in rice. Through conventional breeding, resistance genes (R-gene) were transferred into elite rice genotypes particularly against the fungal blast and bacterial blight diseases. Main drawback of this approach is that, in the long term, breakdown of resistance occurs due to evolution of new virulent pathogen strains. In the current scenario, developing rice with durable broad-spectrum resistance through genetic transformation is gaining importance. In this direction, genetic transformation of rice was being carried out for the past two decades via expressing pathogenesis-related (PR) proteins, antimicrobial peptide, and genes governing signaling pathways as well as elicitor proteins. In spite of several reports, the expression of PR proteins and antimicrobial peptides did not yield desirable disease control in rice. Better understanding of disease resistance mechanism in plants helped in identifying critical transcription factors (TFs) involved in disease resistance. Overexpression of NPR1 encoding non-expressor of pathogenesis-related protein 1 and OsWRKY45 transcription factors in rice showed strong disease resistance to multiple pathogens and at the same time resulted in fitness cost. Recently, transgenic rice with high level of resistance to important rice diseases was achieved by expressing NPR1 and WRKY45 under tissue-specific/pathogen-responsive promoter; thereby agronomic traits are not altered. Rice transformants expressing the pathogen-derived elicitor proteins particularly from rice blast pathogen, Magnaporthe oryzae is a promising approach for imparting broad-spectrum disease resistance without yield penalty. Host-delivered RNAi technology is the latest of the approaches toward enhancing disease resistance against sheath blight and viral disease of rice. Recently, genome-editing tools are being deployed in rice to enhance resistance against diseases of rice.

Efficacy of cry2AX1 Gene in Transgenic Tomato Plants against Helicoverpa armigera and Spodoptera litura

Tomato crop is infested by large number of insect pests, causing significant yield loss. Fruit borer (Helicoverpa armigera) feeds on fruits which leads to quality detoriation and economic loss. Genetic engineering is recognised as a viable tool to engineer resistance in crops against insect pests. Transgenic tomato plants over-expressing cry2AX1 gene under the control of CaMV35S promoter were developed. The T0 and T1 plants were characterized by PCR for the presence and segregation of transgenes. Segregation of cry2AX1 gene in T1 progeny plants followed the Mendelian pattern of monogenic inheritance of 3:1 ratio. The expression of Cry2AX1 at 55 days after sowing ranged from 0.034 to 0.219 μg/g of fresh leaf tissue and 0.030 to 0.249 μg/g of fresh leaf tissue at 80 days after sowing. Insect bioassay of detached leaf bits performed on the ELISA positive transgenic tomato plants against Helicoverpa armigera and Spodoptera litura resulted in mortality of neonates upto 100 per cent in H. armigera and 53 per cent in S. litura.

TNAURice: Database on rice varieties released from Tamil Nadu Agricultural University.

We developed, TNAURice: a database comprising of the rice varieties released from a public institution, Tamil Nadu Agricultural University (TNAU), Coimbatore, India. Backed by MS-SQL, and ASP-Net at the front end, this database provide information on both quantitative and qualitative descriptors of the rice varities inclusive of their parental details. Enabled by an user friendly search utility, the database can be effectively searched by the varietal descriptors, and the entire contents are navigable as well. The database comes handy to the plant breeders involved in the varietal improvement programs to decide on the choice of parental lines. TNAURice is available for public access at http://www.btistnau.org/germdefault.aspx.

ExSer: A standalone tool to mine protein data bank (PDB) for secondary structural elements.

Detailed structural analysis of protein necessitates investigation at primary, secondary and tertiary levels, respectively. Insight into protein secondary structures pave way for understanding the type of secondary structural elements involved (α-helices, β-strands etc.), the amino acid sequence that encode the secondary structural elements, number of residues, length and, percentage composition of the respective elements in the protein. Here we present a standalone tool entitled “ExSer” which facilitate an automated extraction of the amino acid sequence that encode for the secondary structural regions of a protein from the protein data bank (PDB) file. Availability ExSer is freely downloadable from http://code.google.com/p/tool-exser/