Shiv Nadar University

About: Shiv Nadar University is a education organization based out in Dadri, Uttar Pradesh, India. It is known for research contribution in the topics: Population & Graphene. The organization has 1015 authors who have published 1924 publications receiving 18420 citations.

Genome-wide profiling of miRNAs during seed development reveals their functional relevance in seed size/weight determination in chickpea.

Abstract: MicroRNAs (miRNAs) are non-coding small RNAs that regulate gene expression at transcriptional and post-transcriptional levels. The role of miRNAs in seed development and seed size/weight determination is poorly understood in legumes. In this study, we profiled miRNAs at seven successive stages of seed development in a small-seeded and a large-seeded chickpea cultivar via small RNA sequencing. In total, 113 known and 243 novel miRNAs were identified. Gene ontology analysis revealed the enrichment of seed/reproductive/post-embryonic development and signaling pathways processes among the miRNA target genes. A large fraction of the target genes exhibited antagonistic correlation with miRNA expression. The sets of co-expressed miRNAs showing differential expression between the two cultivars were recognized. Known transcription factor (TF) encoding genes involved in seed size/weight determination, including SPL, GRF, MYB, ARF, HAIKU1, SHB1, KLUH/CYP78A5, and E2Fb along with novel genes were found to be targeted by the predicted miRNAs. Differential expression analysis revealed higher transcript levels of members of SPL and REVOLUTA TF families and lower expression of their corresponding miRNAs in the large-seeded cultivar. At least 19 miRNAs known to be involved in seed development or differentially expressed between small-seeded and large-seeded cultivars at late-embryogenesis and/or mid-maturation stages were located within known quantitative trait loci (QTLs) associated with seed size/weight determination. Moreover, 41 target genes of these miRNAs were also located within these QTLs. Altogether, we revealed important roles of miRNAs in seed development and identified candidate miRNAs and their target genes that have functional relevance in determining seed size/weight in chickpea.

Local Electric Fields Dictate Function: The Different Product Selectivities Observed for Fatty Acid Oxidation by Two Deceptively Very Similar P450-Peroxygenases OleT and BSβ

Abstract: Cytochrome P450 peroxygenases use hydrogen peroxide to hydroxylate long-chain fatty acids by bypassing the use of O2 and a redox partner. Among the peroxygenases, P450OleT uniquely performs decarboxylation of fatty acids and production of terminal olefins. This route taken by P450OleT is intriguing, and its importance is augmented by the practical importance of olefin production. As such, this mechanistic choice merits elucidation. To address this puzzle, we use hybrid QM/MM calculations and MD simulations for the OleT enzyme as well as for the structurally analogous enzyme, P450BSβ. The study of P450OleT reveals that the protonated His85 in the wild-type P450OleT plays a crucial role in steering decarboxylation activity by stabilizing the corresponding hydroxoiron(IV) intermediate (Cpd II). In contrast, for P450BSβ in which Q85 replaces H85, the respective Cpd II species is unstable and it reacts readily with the substrate radical by rebound, producing hydroxylation products. As shown, this single-site difference creates in P450OleT a local electric field (LEF), which is significantly higher than that in P450BSβ. In turn, these LEF differences are responsible for the different stabilities of the respective Cpd II/radical intermediates and hence for different functions of the two enzymes. P450BSβ uses the common rebound mechanism and leads to hydroxylation, whereas P450OleT proceeds via decarboxylation and generates terminal olefins. Olefin production projects the power of a single residue to alter the LEF and the enzyme's function.

Role of Molecular Docking in Computer-Aided Drug Design and Development

Abstract: Molecular Docking is widely used in CADD (Computer-Aided Drug Designing), SBDD (Structure-Based Drug Designing) and LBDD (Ligand-Based Drug Designing). It is a method used to predict the binding orientation of one molecule with the other and used for any kind of molecule based on the interaction like, small drug molecule with its protein target, protein – protein binding or a DNA – protein binding. Docking is very much popular technique due to its reliable prediction properties. This book chapter will provide an overview of diverse docking methodologies present that are used in drug design and development. There will be discussion on several case studies, pertaining to each method, followed by advantages and disadvantages of the discussed methodology. It will typically aim professionals in the field of cheminformatics and bioinformatics, both in academia and in industry and aspiring scientists and students who want to take up this as a profession in the near future. We will conclude with our opinion on the effectiveness of this technology in the future of pharmaceutical industry.