PHYSICAL AND PHYTO-CHEMICAL EVALUATION OF GLYCYRRHIZA GLABRA LINN (YASHTIMADHU)

Glycyrrhiza glabra Linn (Yashtimadhu) is a perennial herb commonly known as liquorice. The drug is used in many Ayurvedic formulations like Dasamoolarishtam, Aswagandharishtam, Phalasarpighrita, Khadiragulika, Madhuyastyaditaila etc. Ascertaining the identity, genuineness and purity of herbal drugs has an important role in the maintenance of the quality of the drug and its formulations. The present study was undertaken to assess the preliminary Phyto-chemical constituents of the drug. The preliminary phyto-chemical analysis including quantitative data, qualitative chemical analysis, Thin Layer Chromatography, High Performance Thin Layer Chromatography and Atomic Absorption Spectroscopy were determined. The preliminary Phyto-chemical characteristics observed in the herb may help in standardization, identification and in carrying out further research in Glycyrrhiza glabra Linn

Removal of PCR Error Products and Unincorporated Primers by Metal-Chelate Affinity Chromatography

Immobilized Metal Affinity Chromatography (IMAC) has been used for decades to purify proteins on the basis of amino acid content, especially surface-exposed histidines and “histidine tags” genetically added to recombinant proteins. We and others have extended the use of IMAC to purification of nucleic acids via interactions with the nucleotide bases, especially purines, of single-stranded RNA and DNA. We also have demonstrated the purification of plasmid DNA from contaminating genomic DNA by IMAC capture of selectively-denatured genomic DNA. Here we describe an efficient method of purifying PCR products by specifically removing error products, excess primers, and unincorporated dNTPs from PCR product mixtures using flow-through metal-chelate affinity adsorption. By flowing a PCR product mixture through a Cu2+-iminodiacetic acid (IDA) agarose spin column, 94–99% of the dNTPs and nearly all the primers can be removed. Many of the error products commonly formed by Taq polymerase also are removed. Sequencing of the IMAC-processed PCR product gave base-calling accuracy comparable to that obtained with a commercial PCR product purification method. The results show that IMAC matrices (specifically Cu2+-IDA agarose) can be used for the purification of PCR products. Due to the generality of the base-specific mechanism of adsorption, IMAC matrices may also be used in the purification of oligonucleotides, cDNA, mRNA and micro RNAs

Science Opportunities offered by Mercury's Ice-Bearing Polar Deposits

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FMR1 CGG repeat expansion mutation detection and linked haplotype analysis for reliable and accurate preimplantation genetic diagnosis of fragile X syndrome

10.1017/erm.2017.10EXPERT REVIEWS IN MOLECULAR MEDICINE1

PLAS-20k: Extended Dataset of Protein-Ligand Affinities from MD Simulations for Machine Learning Applications

Abstract Computing binding affinities is of great importance in drug discovery pipeline and its prediction using advanced machine learning methods still remains a major challenge as the existing datasets and models do not consider the dynamic features of protein-ligand interactions. To this end, we have developed PLAS-20k dataset, an extension of previously developed PLAS-5k, with 97,500 independent simulations on a total of 19,500 different protein-ligand complexes. Our results show good correlation with the available experimental values, performing better than docking scores. This holds true even for a subset of ligands that follows Lipinski’s rule, and for diverse clusters of complex structures, thereby highlighting the importance of PLAS-20k dataset in developing new ML models. Along with this, our dataset is also beneficial in classifying strong and weak binders compared to docking. Further, OnionNet model has been retrained on PLAS-20k dataset and is provided as a baseline for the prediction of binding affinities. We believe that large-scale MD-based datasets along with trajectories will form new synergy, paving the way for accelerating drug discovery