Plant-derived molecules (PDMs) are known to be a rich source of diverse scaffolds that could serve as the basis for rational drug design. Structured compilation of phytochemicals from traditional medicinal plants can facilitate prospection for novel PDMs and their analogs as therapeutic agents. Atropa belladonna, Catharanthus roseus, Heliotropium indicum, Picrorhiza kurroa and Podophyllum hexandrum are important Himalayan medicinal plants, reported to have immense therapeutic properties against various diseases. We present Phytochemica, a structured compilation of 963 PDMs from these plants, inclusive of their plant part source, chemical classification, IUPAC names, SMILES notations, physicochemical properties and 3-dimensional structures with associated references. Phytochemica is an exhaustive resource of natural molecules facilitating prospection for therapeutic molecules from medicinally important plants. It also offers refined search option to explore the neighbourhood of chemical space against ZINC database to identify analogs of natural molecules at user-defined cut-off. Availability of phytochemical structured dataset may enable their direct use in in silico drug discovery which will hasten the process of lead identification from natural products under proposed hypothesis, and may overcome urgent need for phytomedicines. Compilation and accessibility of indigenous phytochemicals and their derivatives can be a source of considerable advantage to research institutes as well as industries.Database URL: home.iitj.ac.in/∼bagler/webservers/Phytochemica
Aldose Reductase (AR) is implicated in the development of secondary complications of diabetes, providing an interesting target for therapeutic intervention. Extracts of Rauvolfia serpentina, a medicinal plant endemic to the Himalayan mountain range, have been known to be effective in alleviating diabetes and its complications. In this study, we aim to prospect for novel plant-derived inhibitors from R. serpentina and to understand structural basis of their interactions. An extensive library of R. serpentina molecules was compiled and computationally screened for inhibitory action against AR. The stability of complexes, with docked leads, was verified using molecular dynamics simulations. Two structurally distinct plant-derived leads were identified as inhibitors: indobine and indobinine. Further, using these two leads as templates, 16 more leads were identified through ligand-based screening of their structural analogs, from a small molecules database. Thus, we obtained plant-derived indole alkaloids, and their structural analogs, as potential AR inhibitors from a manually curated dataset of R. serpentina molecules. Indole alkaloids reported herein, as a novel structural class unreported hitherto, may provide better insights for designing potential AR inhibitors with improved efficacy and fewer side effects.
Nitrate is the main source of inorganic nitrogen for plants, which also act as signaling molecule. Present study was aimed to understand nitrate regulatory mechanism in Brassica juncea cultivars, with contrasting nitrogen-use-efficiency (NUE) viz. Pusa Bold (PB, high-NUE) and Pusa Jai Kisan (PJK, low-NUE), employing RNA-seq approach. A total of 4031, 3874 and 3667 genes in PB and 2982, 2481 and 2843 genes in PJK were differentially expressed in response to early, low (0.25 mM KNO3), medium (2 mM KNO3) and high (4 mM KNO3) nitrate treatments, respectively, as compared to control (0 mM KNO3). Genes of N-uptake (NRT1.1, NRT1.8, and NRT2.1), assimilation (NR1, NR2, NiR, GS1.3, and Fd-GOGAT) and remobilization (GDH2, ASN2–3 and ALaT) were highly-upregulated in PB than in PJK in response to early nitrate treatments. We have also identified transcription factors and protein kinases that were rapidly induced in response to nitrate, suggesting their involvement in nitrate-mediated signaling. Co-expression network analysis revealed four nitrate specific modules in PB, enriched with GO terms like, “Phenylpropanoid pathway”, “Nitrogen compound metabolic process” and “Carbohydrate metabolism”. The network analysis also identified HUB transcription factors like mTERF, FHA, Orphan, bZip and FAR1, which may be the key regulators of nitrate-mediated response in B. juncea.
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