Genome-wide identification, phylogeny, and expression analysis of the CA gene family in tomato

Dependence on linkers' flexibility designed for benzenesulfonamides targeting discovery of novel hCA IX inhibitors as potent anticancer agents

Herein we reported the design and synthesis of two series comprising twenty-two benzenesulfonamides that integrate the s-triazine moiety. Target compounds successfully suppressed the hCA IX, with IC₅₀ ranging from 28.6 to 871 nM. Compounds 5d, 11b, 5b, and 7b were the most active analogues, which inhibited hCA IX isoform in the low nanomolar range (K_I = 28.6, 31.9, 33.4, and 36.6 nM, respectively). Furthermore, they were assessed for their cytotoxic activity against a panel of 60 cancer cell lines following US-NCI protocol. According to five-dose assay, 13c showed significant anticancer activity than 5c with GI₅₀-MID values of 25.08 and 189.01 µM, respectively. Additionally, 13c's effects on wound healing, cell cycle disruption, and apoptosis induction in NCI-H460 cancer cells were examined. Further, docking studies combined with molecular dynamic simulation showed a stable complex with high binding affinity of 5d to hCA IX, exploiting a favourable H-bond and lipophilic interactions.HIGHLIGHTSCarbonic anhydrase (CA) inhibitors comprising rigid and flexible linkers were developed.Compound 5d is the most potent CA IX inhibitor in the study (IC50: 28.6 nM).Compounds 5c and 13c displayed the greatest antiproliferative activity towards 60 cell lines.Compound 13c exposed constructive outcomes on normal cell lines, metastasis, and wound healing.Molecular docking and molecular dynamics (MDs) simulation was utilised to study binding mode.

Genome-wide identification studies - A primer to explore new genes in plant species

Genome data have accumulated rapidly in recent years, doubling roughly after every 6 months due to the influx of next-generation sequencing technologies. A plethora of plant genomes are available in comprehensive public databases. This easy access to data provides an opportunity to explore genome datasets and recruit new genes in various plant species not possible a decade ago. In the past few years, many gene families have been published using these public datasets. These genome-wide studies identify and characterize gene members, gene structures, evolutionary relationships, expression patterns, protein interactions and gene ontologies, and predict putative gene functions using various computational tools. Such studies provide meaningful information and an initial framework for further functional elucidation. This review provides a concise layout of approaches used in these gene family studies and demonstrates an outline for employing various plant genome datasets in future studies.