Novel (E)-3-(3-Oxo-4-substituted-3,4-dihydro-2H-benzo[b][1,4]oxazin-6-yl)-N-hydroxypropenamides as Histone Deacetylase Inhibitors: Design,Synthesis and Bioevaluation

Herein, we report the design, synthesis and evaluation of novel (E)-3-(3-oxo-4-substituted-3,4-dihydro-2H-benzo[b][1,4]oxazin-6-yl)-N-hydroxypropenamides ( 4 a – i , 7 a – g ) targeting histone deacetylases. Three human cancer cell lines were used to test the cytotoxicity of the synthesized compounds (SW620, colon; PC-3, prostate; NCI−H23, lung cancer); inhibitory activity towards HDAC; anticancer activity; as well as their impact on the cell cycle and apoptosis. As a result, compounds 4 a – i bearing the alkyl substituents seemed to be less potent than the benzyl-containing compounds 7 a – g in all biological assays. Compounds 7 e – f were found to be the most active HDAC inhibitors with IC₅₀ of 1.498±0.020 μM and 1.794±0.159 μM, respectively. In terms of cytotoxicity and anticancer assay, 7 e and 7 f also showed good activity with IC₅₀ values in the micromolar range. In addition, the cell cycle and apoptosis of SW620 were affected by compound 7 f in almost a similar manner to that of reference compound SAHA. Docking assays were carried out for analysis the binding mode and selectivity of this compound toward 8 HDAC isoforms. Overall, our data confirmed that the inhibition of HDAC plays a pivotal role in their anticancer activity.     

A transformer architecture for retention time prediction in liquid chromatography mass spectrometry-based proteomics

Accurate retention time (RT) prediction is important for spectral library-based analysis in data-independent acquisition mass spectrometry-based proteomics. The deep learning approach has demonstrated superior performance over traditional machine learning methods for this purpose. The transformer architecture is a recent development in deep learning that delivers state-of-the-art performance in many fields such as natural language processing, computer vision, and biology. We assess the performance of the transformer architecture for RT prediction using datasets from five deep learning models Prosit, DeepDIA, AutoRT, DeepPhospho, and AlphaPeptDeep. The experimental results on holdout datasets and independent datasets exhibit state-of-the-art performance of the transformer architecture. The software and evaluation datasets are publicly available for future development in the field.     

Low genetic diversity and population connectivity fuel vulnerability to climate change for the Tertiary relict pine Pinus bungeana

Endemic species are important components of regional biodiversity and hold the key to understanding local adaptation and evolutionary processes that shape species distributions. This study investigated the biogeographic history of a relict conifer Pinus bungeana Zucc. ex Endl. confined to central China. We examined genetic diversity in P. bungeana using genotyping-by-sequencing and chloroplast and mitochondrial DNA markers. We performed spatial and temporal inference of recent genetic and demographic changes, and dissected the impacts of geography and environmental gradients on population differentiation. We then projected P. bungeana's risk of decline under future climates. We found extremely low nucleotide diversity (average π 0.0014), and strong population structure (global F_ST 0.234) even at regional scales, reflecting long-term isolation in small populations. The species experienced severe bottlenecks in the early Pliocene and continued to decline in the Pleistocene in the western distribution, whereas the east expanded recently. Local adaptation played a small (8%) but significant role in population diversity. Low genetic diversity in fragmented populations makes the species highly vulnerable to climate change, particularly in marginal and relict populations. We suggest that conservation efforts should focus on enhancing gene pool and population growth through assisted migration within each genetic cluster to reduce the risk of further genetic drift and extinction.     

Systematics of Mukdenia and Oresitrophe (Saxifragaceae): Insights from genome skimming data

Oresitrophe and Mukdenia (Saxifragaceae) are epilithic sister genera used in traditional Chinese medicine. The taxonomy of Mukdenia, especially of M. acanthifolia, has been controversial. To address this, we produced plastid and mitochondrial data using genome skimming for Mukdenia acanthifolia and Mukdenia rossii, including three individuals of each species. We assembled complete plastomes, mitochondrial CDS and nuclear ribosomal ETS/ITS sequences using these data. Comparative analysis shows that the plastomes of Mukdenia and Oresitrophe are relatively conservative in terms of genome size, structure, gene content, RNA editing sites and codon usage. Five plastid regions that represent hotspots of change (trnH-psbA, psbC-trnS, trnM-atpE, petA-psbJ and ccsA-ndhD) are identified within Mukdenia, and six regions (trnH-psbA, petN-psbM, trnM-atpE, rps16-trnQ, ycf1 and ndhF) contain a higher number of species-specific parsimony-informative sites that may serve as potential DNA barcodes for species identification. To infer phylogenetic relationships between Mukdenia and Oresitrophe, we combined our data with published data based on three different datasets. The monophyly of each species (Oresitrophe rupifraga, M. acanthifolia and M. rossii) and the inferred topology ((M. rossii, M. acanthifolia), O. rupifraga) are well supported in trees reconstructed using the complete plastome sequences, but M. acanthifolia and M. rossii did not form a separate clade in the trees based on ETS + ITS data, while the mitochondrial CDS trees are not well-resolved. We found low recovery of genes in the Angiosperms353 target enrichment panel from our unenriched genome skimming data. Hybridization or incomplete lineage sorting may be the cause of discordance between trees reconstructed from organellar and nuclear data. Considering its morphological distinctiveness and our molecular phylogenetic results, we strongly recommend that M. acanthifolia be treated as a distinct species.     

First chemical synthesis of a scorpion alpha-toxin affecting sodium channels: the Aah I toxin of Androctonus australis hector.

Aah I is a 63-residue alpha-toxin isolated from the venom of the Buthidae scorpion Androctonus australis hector, which is considered to be the most dangerous species. We report here the first chemical synthesis of Aah I by the solid-phase method, using a Fmoc strategy. The synthetic toxin I (sAah I) was renatured in DMSO-Tris buffer, purified and subjected to thorough analysis and comparison with the natural toxin. The sAah I showed physico-chemical (CD spectrum, molecular mass, HPLC elution), biochemical (amino-acid composition, sequence), immunochemical and pharmacological properties similar to those of the natural toxin. The synthetic toxin was recognized by a conformation-dependent monoclonal anti-Aah I antibody, with an IC50 value close to that for the natural toxin. Following intracerebroventricular injection, the synthetic and the natural toxins were similarly lethal to mice. In voltage-clamp experiments, Na(v) 1.2 sodium channel inactivation was inhibited by the application of sAah I or of the natural toxin in a similar way. This work describes a simple protocol for the chemical synthesis of a scorpion alpha-toxin, making it possible to produce structural analogues in time.