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Metal Tolerance in Plants: The Role of Phytochelatins and Metallothioneins
Published in Norman Terry, Gary Bañuelos, of Contaminated Soil and Water, 2020
The discovery of PCs in plants led to the proposal that plants do not possess metallothionein (MT) proteins, i.e., gene-encoded, cysteine-rich proteins translated from in RNAs, but instead utilized PCs to fulfill the functions of metal homeostasis and detoxification (Grill et al., 1987). However, only 2 years after the first reports of PCs in plants, Lane et al. (1987) purified the Ec protein from wheat embryos and demonstrated that the amino acid sequence of this protein was consistent with that of an MT and that this protein bound Zn2+. This was followed by the cloning of genes that encoded MT-like proteins from several plant species. While the functions of these MT genes are still unknown, it is clear that plants are equipped with at least two ligands that use cysteine coordination of metals, namely PCs and MTs. Because this is the most extensively documented gene family, the Arabidopsis MT gene family will be used as a model to discuss the structure, expression, and possible function of MTs in plants. Studies on MTs from other species will be discussed where they add to the overall view of the function of plant MTs.
Endocrine Disruptors
Published in Brian D. Fath, Sven E. Jørgensen, Megan Cole, Managing Global Resources and Universal Processes, 2020
Aside from triazoles, the organic fungicide fenarimol possesses estrogenic properties[33] and acts both as an estrogen agonist and as an androgen antagonist.[34] In addition, fenarimol affects rat aromatase activity in vivo, inhibiting estrogen biosynthesis in rat microsomes[35] and in human tissues.[3]This compound also affects other enzymes of the cytochrome P450 gene family that are involved in the metabolism of steroids.[36]
Computer-Aided Drug Design for the Identification of Multi-Target Directed Ligands (MTDLs) in Complex Diseases: An Overview
Published in Peter Grunwald, Pharmaceutical Biocatalysis, 2019
A preliminary study is certainly helpful for initial selection of possible MTDLs and/or target proteins. In such study, the potential ligand as MTDLs can be selected by finding a set of structurally similar ligands with known binding affinity to different protein targets (from same or different protein families). Here, the similar ligands can be identified based on a similarity/distance-based metric like Tanimoto similarity coefficient, Euclidean distance, etc. The potential target proteins can be selected via a binding site similarity study, where, the binding site can be estimated using several available computational tools, such as LIGSITE, Q-SiteFinder, SURFNET, or PASS (Henrich et al., 2010). Proteins that belong to the same gene family, or proteins showing complete sequence homology are more likely to have similar binding sites. Ligand binding-site similarities among unrelated proteins are interesting viewpoint in MTDD approach (Haupt et al., 2013). Another approach is drug-repurposing or drug re-profiling studies, where, the goal is to find already known and approved drugs as potential candidate for MTDD via studying the side effects or beneficial effects caused by binding to multiple off-target proteins (Zhang et al., 2017). Moreover, network pharmacology (Hopkins, 2008) can also be employed to create a chemical network that relates proteins that bind to similar ligand.
Tetramethylpyrazine production from edible materials by the probiotic Bacillus coagulans
Published in Preparative Biochemistry & Biotechnology, 2020
Haoxuan Zhong, Jie Shen, Zhe Meng, Jing-yi Zhao, Zijun Xiao
Then, we selected strains ATCC 7050, GBI-30 and S-Lac, the three strains with the most extensive applications among the 11 strains of B. coagulans, and conducted gene family analysis with strain CICC 20138. During genome evolution, a gene can be duplicated to two or more copies, and multiple copies of similar genes make up a gene family. Usually, each gene within a gene family has similar biochemical functions. All the sequences to be analyzed were merged into one file to build the database, all-vs-all BLASTP analysis was performed, and the threshold for serial alignment was set to 1e-5. The sequence alignment were performed using OrthoMCL (version 1.4) software and processed for gene family analysis,[17] and then the results were represented by a Venn diagram.