👤 Yakovlev DS

Early in the evolution of life, a proto-metabolic network was encapsulated within a membrane compartment. The permeability characteristics of the membrane determined several key functions of this network by determining which compounds could enter the compartment and which compounds could not. One key feature of known life is the utilization of right-handed d-ribose and d-deoxyribose sugars and left-handed l-amino acid stereochemical isomers (enantiomers); however, it is not clear why life adopted this specific chirality. Generally, archaea have l-phospholipid membrane chemistries and bacteria and eukaryotes have d-phospholipid membrane chemistries. We previously demonstrated that an l-archaeal and a d-intermediate membrane mimic, bearing a mixture of bacterial and archaeal lipid characteristics (a 'hybrid' membrane), displayed increased permeability for several key compounds compared to bacterial-like membranes. Here, we investigate if these membranes can drive stereochemical selection on pentose sugars, hexose sugars, and amino acids. Using permeability assays of homogenous unilamellar vesicles, we demonstrate that both membranes select for d-ribose and d-deoxyribose sugars while the hybrid membrane uniquely selects for a reduced alphabet of l-amino acids. This repertoire includes alanine, the plausible first l-amino acid utilized. We conclude such compartments could provide stereochemical compound selection matching those used by the core metabolism of life. Show less

In the healthcare industry, the ever-increasing volume of clinical trial data presents challenges for ensuring drug safety and detecting adverse drug reactions (ADRs). This study aims to address the challenge of accurately detecting Serious Adverse Events (SAEs) in pharmacovigilance, a critical component in ensuring drug safety during and after clinical trials. The key problem lies in the underreporting and delayed detection of Adverse Drug Reactions (ADRs) due to the heterogeneous nature of medical data, class imbalance, and the limited scope of traditional monitoring techniques. This study proposes a hybrid AI-driven framework that integrates structured (e.g., patient demographics, lab results) and unstructured data (e.g., clinical notes) to detect ADRs using advanced deep learning and NLP methods. The objective is to outperform traditional signal detection methods and provide interpretable predictions to aid clinicians in real-time. By leveraging advanced Machine Learning (ML) and Deep Learning (DL) techniques, including Random Forests, Gradient Boosting Machines, and Convolutional Neural Networks (CNNs), our model aims to identify potential ADRs across different patient subgroups. Through meticulous feature engineering and the application of techniques to address data imbalance, our model demonstrates improved accuracy and interpretability in predicting ADRs. The CNN model achieved an accuracy of 85 %, outperforming traditional models, such as Logistic Regression (78 %) and Support Vector Machines (80 %). These findings suggest that specific demographic and clinical factors significantly influence the likelihood of adverse reactions, offering valuable insights for targeted monitoring and risk mitigation strategies[11]. This research underscores the potential of predictive modeling to enhance pharmacovigilance efforts and ensure safer clinical trial outcomes.•The research methodology includes a comparison of supervised learning algorithms, such as Logistic Regression, Random Forest, Gradient Boost, CNN, and genetic algorithms, to identify patterns and anomalies in clinical trial data. BERT and GPT, were also employed to provide the functionality of textual interactions over medical data.•Performance metrics such as accuracy, precision, recall, and F1-score were systematically applied to evaluate each model's performance. Among the models tested, the CNN model with BERT achieved the highest accuracy, providing valuable insights into the potential of deep learning for enhancing pharmacovigilance practices.•These findings suggest that an inclusion of diverse clinical data when supplied to advanced ML and NLP techniques can significantly improve the detection of ADRs, leading to better alignment with the fundamental principles of Good Clinical Practice (GCP). Show less

Title: A Bioactive Benzimidazole-Cyclometalated Iridium(III) Complex as an Epigenetic Regulator through Effectively Interrupting the EED-EZH2 Interaction. Abstract: Epigenetic regulation plays a fundamental role in controlling gene expression and maintaining cellular identity. Among epigenetic processes, the translocation of methyltransferases is critical for the modification of chromatin structure and transcriptional activity. The regulation of these translocation events and the mechanisms involved are complex, yet critical for understanding and manipulating epigenetic states. Therefore, novel strategies are required for detecting and visualizing the movement and interaction of methyltransferases within cells. Using enhancer of zeste homolog 2 (EZH2) methyltransferase as an example, a bifunctional compound capable of both monitoring and disrupting its translocation process is developed by targeting the protein-protein interaction (PPI) between embryonic ectoderm development (EED) and EZH2. The Ir(III) complex 1 bound enthalpically to EED and effectively inhibited the methyltransferase activity of EZH2. Moreover, disruption of the EED-EZH2 PPI led to increased transcriptional activity of P21 and P27, resulting in the suppression of triple-negative breast cancer (TNBC) cell proliferation. Excitingly, 1 suppressed tumor metastasis in a TNBC mouse model in vivo. To our knowledge, complex 1 is the first metal-based bifunctional therapeutic agent designed to probe and inhibit the EED-EZH2 PPI, highlighting the feasibility and significance of using metal complexes to monitor and influence methyltransferase translocations for therapeutic applications. Show less

This study is dedicated to the development of multimodal anticancer agents. We have obtained ruthenium complexes conjugated with the steroid-type antitumor drug abiraterone acetate in order to take advantage of the dual antitumor properties of both ruthenium and abiraterone. The compounds exhibit good antiproliferative activity against cancer cells, with selectivity over primary fibroblasts. Real-time cell analysis revealed that compound dichlorido(η⁶-p-cymene)(abiraterone acetate)ruthenium(II) had pronounced antiproliferation activity compared to abiraterone acetate. Flow cytometric studies on the mechanism of cell death have revealed that the most active compound induces apoptosis more effectively than abiraterone acetate. Our findings demonstrate the potential of this novel dual-action compound as promising candidates for further development as anticancer agents. Show less

Title: Cyrene™ as a green alternative to Abstract: Ruthenium(II) polypyridyl complexes (RPCs) that emit from triplet metal-to-ligand charge transfer (MLCT) states find a wide variety of uses ranging from luminophores to potential anti-cancer or anti-bacterial therapeutics. Herein we describe a greener, microwave-assisted synthetic pathway for the preparation of homoleptic [Ru(N^N)3]2+ and bis-heteroleptic [Ru(N^N)2(N'^N')]2+ type complexes. This employs the bio-renewable solvent Cyrene™, dihydrolevoglucosenone, as a green alternative to N,N'-dimethylformamide (DMF) in the synthesis of Ru(N^N)2Cl2 intermediate complexes, obtaining comparable yields for N^N = 2,2'-bipyridine, 1,10-phenanthroline and methylated derivatives. Employing these intermediates, a range of RPCs were prepared and we verify that the ubiquitous luminophore [Ru(bpy)3]2+ (bpy = 2,2'-bipyridine) can be prepared by this two-step green pathway where it is virtually indistinguishable from a commercial reference. Furthermore, the novel complexes [Ru(bpy)2(10,11-dmdppz)]2+ (10,11-dmdppz = 10,11-dimethyl-dipyridophenazine) and [Ru(5,5'-dmbpy)2(10,11-dmdppz)]2+ (5,5'-dmbpy = 5,5'-dimethyl-bpy) intercalate duplex DNA with high affinity (DNA binding constants, Kb = 5.7 × 107 and 1.0 × 107 M-1, respectively) and function as plasma membrane and nuclear DNA dyes for confocal and STED microscopies courtesy of their long-lived MLCT luminescence. Show less

One of the deepest branches in the tree of life separates the Archaea from the Bacteria. These prokaryotic groups have distinct cellular systems including fundamentally different phospholipid membrane bilayers. This dichotomy has been termed the lipid divide and possibly bestows different biophysical and biochemical characteristics on each cell type. Classic experiments suggest that bacterial membranes (formed from lipids extracted from Escherichia coli, for example) show permeability to key metabolites comparable to archaeal membranes (formed from lipids extracted from Halobacterium salinarum), yet systematic analyses based on direct measurements of membrane permeability are absent. Here, we develop a new approach for assessing the membrane permeability of approximately 10 μm unilamellar vesicles, consisting of an aqueous medium enclosed by a single lipid bilayer. Comparing the permeability of 18 metabolites demonstrates that diether glycerol-1-phosphate lipids with methyl branches, often the most abundant membrane lipids of sampled archaea, are permeable to a wide range of compounds useful for core metabolic networks, including amino acids, sugars, and nucleobases. Permeability is significantly lower in diester glycerol-3-phosphate lipids without methyl branches, the common building block of bacterial membranes. To identify the membrane characteristics that determine permeability, we use this experimental platform to test a variety of lipid forms bearing a diversity of intermediate characteristics. We found that increased membrane permeability is dependent on both the methyl branches on the lipid tails and the ether bond between the tails and the head group, both of which are present on the archaeal phospholipids. These permeability differences must have had profound effects on the cell physiology and proteome evolution of early prokaryotic forms. To explore this further, we compare the abundance and distribution of transmembrane transporter-encoding protein families present on genomes sampled from across the prokaryotic tree of life. These data demonstrate that archaea tend to have a reduced repertoire of transporter gene families, consistent with increased membrane permeation. These results demonstrate that the lipid divide demarcates a clear difference in permeability function with implications for understanding some of the earliest transitions in cell origins and evolution. Show less

Three new ruthenium(II) complexes were synthesized from different substituted isothiazole ligands 5-(methylamino)-3-pyrrolidine-1-ylisothiazole-4-carbonitrile (1), 5-(methylamino)-3-(4-methylpiperazine-1-yl)isothiazole-4-carbonitrile (2) and 5-(methylamino)-3-morpholine-4-ylisothiazole-4-carbonitrile (3): [Ru(η⁶-p-cymene)Cl₂(L1)]·H₂O (4), [Ru(η⁶-p-cymene)Cl₂(L2)] (5) and [Ru(η⁶-p-cymene)Cl₂(L3)] (6). All complexes were characterized by IR, UV-Vis, NMR spectroscopy, and elemental analysis. The molecular structures of all ligands and complexes 4 and 6 were determined by an X-ray. The results of the interactions of CT-DNA (calf thymus deoxyribonucleic acid) and HSA (human serum albumin) with ruthenium (II) complexes reveal that complex 4 binds well to CT-DNA and HSA. Kinetic and thermodynamic parameters for the reaction between complex and HSA confirmed the associative mode of interaction. The results of Quantum mechanics (QM) modelling and docking experiments toward DNA dodecamer and HSA support the strongest binding of the complex 4 to DNA major groove, as well as its binding to IIa domain of HSA with the lowest ΔG energy, which agrees with the solution studies. The modified GOLD docking results are indicative for Ru(p-cymene)LCl··(HSA··GLU292) binding and GOLD/MOPAC(QM) docking/modelling of DNA/Ligand (Ru(II)-N(7)dG7) covalent binding. The cytotoxic activity of compounds was evaluated by MTT (3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide) assay. Neither of the tested compounds shows activity against a healthy MRC-5 cell line while the MCF-7 cell line is the most sensitive to all. Compounds 3, 4 and 5 were about two times more active than cisplatin, while the antiproliferative activity of 6 was almost the same as with cisplatin. Flow cytometry analysis showed the apoptotic death of the cells with a cell cycle arrest in the subG1 phase. Show less