Thiazole/Thiadiazole/Benzothiazole Based Thiazolidin-4-One Derivatives as Potential Inhibitors of Main Protease of SARS-CoV-2

Since the time of its appearance until present, COVID-19 has spread worldwide, with over 71 million confirmed cases and over 1.6 million deaths reported by the World Health Organization (WHO). In addition to the fact that cases of COVID-19 are increasing worldwide, the Delta and Omicron variants have also made the situation more challenging. Herein, we report the evaluation of several thiazole/thiadiazole/benzothiazole based thiazolidinone derivatives which were chosen from 112 designed derivatives by docking as potential molecules to inhibit the main protease of SARS-CoV-2. The contained experimental data revealed that among the fifteen compounds chosen, five compounds (k3, c1, n2, A2, A1) showed inhibitory activity with IC50 within the range of 0.01-34.4 μΜ. By assessing the cellular effects of these molecules, we observed that they also had the capacity to affect the cellular viability of human normal MRC-5 cells, albeit with a degree of variation. More specifically, k3 which is the most promising compound with the higher inhibitory capacity to SARS-CoV-2 protease (0.01 μΜ) affects in vitro cellular viability only by 57% at the concentration of 0.01 μM after 48 h in culture. Overall, these data provide evidence on the potential antiviral activity of these molecules to inhibit the main protease of SARS-CoV-2, a fact that sheds light on the chemical structure of the thiazole/thiadiazole/benzothiazole based thiazolidin-4-one derivatives as potential candidates for COVID-19 therapeutics.

Dissecting miRNA–Gene Networks to Map Clinical Utility Roads of Pharmacogenomics-Guided Therapeutic Decisions in Cardiovascular Precision Medicine

MicroRNAs (miRNAs) create systems networks and gene-expression circuits through molecular signaling and cell interactions that contribute to health imbalance and the emergence of cardiovascular disorders (CVDs). Because the clinical phenotypes of CVD patients present a diversity in their pathophysiology and heterogeneity at the molecular level, it is essential to establish genomic signatures to delineate multifactorial correlations, and to unveil the variability seen in therapeutic intervention outcomes. The clinically validated miRNA biomarkers, along with the relevant SNPs identified, have to be suitably implemented in the clinical setting in order to enhance patient stratification capacity, to contribute to a better understanding of the underlying pathophysiological mechanisms, to guide the selection of innovative therapeutic schemes, and to identify innovative drugs and delivery systems. In this article, the miRNA–gene networks and the genomic signatures resulting from the SNPs will be analyzed as a method of highlighting specific gene-signaling circuits as sources of molecular knowledge which is relevant to CVDs. In concordance with this concept, and as a case study, the design of the clinical trial GESS (NCT03150680) is referenced. The latter is presented in a manner to provide a direction for the improvement of the implementation of pharmacogenomics and precision cardiovascular medicine trials.

A Risk-Stratification Machine Learning Framework for the Prediction of Coronary Artery Disease Severity: Insights From the GESS Trial

Our study aims to develop a data-driven framework utilizing heterogenous electronic medical and clinical records and advanced Machine Learning (ML) approaches for: (i) the identification of critical risk factors affecting the complexity of Coronary Artery Disease (CAD), as assessed via the SYNTAX score; and (ii) the development of ML prediction models for accurate estimation of the expected SYNTAX score. We propose a two-part modeling technique separating the process into two distinct phases: (a) a binary classification task for predicting, whether a patient is more likely to present with a non-zero SYNTAX score; and (b) a regression task to predict the expected SYNTAX score accountable to individual patients with a non-zero SYNTAX score. The framework is based on data collected from the GESS trial (NCT03150680) comprising electronic medical and clinical records for 303 adult patients with suspected CAD, having undergone invasive coronary angiography in AHEPA University Hospital of Thessaloniki, Greece. The deployment of the proposed approach demonstrated that atherogenic index of plasma levels, diabetes mellitus and hypertension can be considered as important risk factors for discriminating patients into zero- and non-zero SYNTAX score groups, whereas diastolic and systolic arterial blood pressure, peripheral vascular disease and body mass index can be considered as significant risk factors for providing an accurate estimation of the expected SYNTAX score, given that a patient belongs to the non-zero SYNTAX score group. The experimental findings utilizing the identified set of important risk factors indicate a sufficient prediction performance for the Support Vector Machine model (classification task) with an F-measure score of ~0.71 and the Support Vector Regression model (regression task) with a median absolute error value of ~6.5. The proposed data-driven framework described herein present evidence of the prediction capacity and the potential clinical usefulness of the developed risk-stratification models. However, further experimentation in a larger clinical setting is needed to ensure the practical utility of the presented models in a way to contribute to a more personalized management and counseling of CAD patients.

NGIWY-Amide: A Bioinspired Ultrashort Self-Assembled Peptide Gelator for Local Drug Delivery Applications

Fibrillar structures derived from plant or animal origin have long been a source of inspiration for the design of new biomaterials. The Asn-Gly-Ile-Trp-Tyr-NH2 (NGIWY-amide) pentapeptide, isolated from the sea cucumber Apostichopus japonicus, which spontaneously self-assembles in water to form hydrogel, pertains to this category. In this study, we evaluated this ultra-short cosmetic bioinspired peptide as vector for local drug delivery applications. Combining nuclear magnetic resonance, circular dichroism, infrared spectroscopy, X-ray diffraction, and rheological studies, the synthesized pentapeptide formed a stiff hydrogel with a high β-sheet content. Molecular dynamic simulations aligned well with scanning electron and atomic-force microscopy studies, revealing a highly filamentous structure with the fibers adopting a helical-twisted morphology. Model dye localization within the supramolecular hydrogel provided insights on the preferential distribution of hydrophobic and hydrophilic compounds in the hydrogel network. That was further depicted in the diffusion kinetics of drugs differing in their aqueous solubility and molecular weight, namely, doxorubicin hydrochloride, curcumin, and octreotide acetate, highlighting its versatility as a delivery vector of both hydrophobic and hydrophilic compounds of different molecular weight. Along with the observed cytocompatibility of the hydrogel, the NGIWY-amide pentapeptide may offer new approaches for cell growth, drug delivery, and 3D bioprinting tissue-engineering applications.

The GEnetic Syntax Score: a genetic risk assessment implementation tool grading the complexity of coronary artery disease-rationale and design of the GESS study

Background

Coronary artery disease (CAD) remains one of the leading causes of mortality worldwide and is associated with multiple inherited and environmental risk factors. This study is designed to identify, design, and develop a panel of genetic markers that combined with clinical and angiographic information, will facilitate the creation of a personalized risk prediction algorithm (GEnetic Syntax Score—GESS). GESS score could be a reliable tool for predicting cardiovascular risk for future adverse events and for guiding therapeutic strategies.

Methods

GESS (ClinicalTrials.gov Identifier: NCT03150680) is a prospective, non-interventional clinical study designed to enroll 1080 consecutive patients with no prior history of coronary revascularization procedure, who undergo scheduled or emergency coronary angiography in AHEPA, University General Hospital of Thessaloniki. Next generation sequencing (NGS) technology will be used to genotype specific single-nucleotide polymorphisms (SNPs) across the genome of study participants, which were identified as clinically relevant to CAD after extensive bioinformatic analysis of literature-based SNPs. Enrichment analyses of Gene Ontology-Molecular Function, Reactome Pathways and Disease Ontology terms were also performed to identify the top 15 statistically significant terms and pathways. Furthermore, the SYNTAX score will be calculated for the assessment of CAD severity of all patients based on their angiographic findings. All patients will be followed-up for one-year, in order to record any major adverse cardiovascular events.

Discussion

A group of 228 SNPs was identified through bioinformatic and pharmacogenomic analysis to be involved in CAD through a wide range of pathways and was correlated with various laboratory and clinical parameters, along with the patients' response to clopidogrel and statin therapy. The annotation of these SNPs revealed 127 genes being affected by the presence of one or more SNPs. The first patient was enrolled in the study in February 2019 and enrollment is expected to be completed until June 2021. Hence, GESS is the first trial to date aspiring to develop a novel risk prediction algorithm, the GEnetic Syntax Score, able to identify patients at high risk for complex CAD based on their molecular signature profile and ultimately promote pharmacogenomics and precision medicine in routine clinical settings.

Trial registration GESS trial registration: ClinicalTrials.gov Number: NCT03150680. Registered 12 May 2017- Prospectively registered, https://clinicaltrials.gov/ct2/show/NCT03150680.

Uncovering the pharmacological response of novel sesquiterpene derivatives that differentially alter gene expression and modulate the cell cycle in cancer cells

The present study aimed to assess the pharmacological anticancer profile of three natural and five synthetic sesquiterpenes developed by total chemical synthesis. To this end, their properties at the cellular and molecular level were evaluated in a panel of normal and cancer cell lines. The results obtained by performing cytotoxicity assays and gene expression analysis by reverse transcription-quantitative polymerase chain reaction showed that: i) Among the sesquiterpene derivatives analyzed, VDS58 exhibited a notable anticancer profile within attached (U-87 MG and MCF-7) and suspension (K562 and MEL-745) cancer cell cultures; however, U-87 MG cells were able to recover their proliferation capacity rapidly after 48 h of exposure; ii) gene expression profiling of U-87 MG cells, in contrast to K562 cells, showed a transient induction of cyclin-dependent kinase inhibitor 1A (CDKN1) expression; iii) the expression levels of transforming growth factor β1 (TGFB1) increased after 12 h of exposure of U-87 MG cells to VDS58 and were maintained at this level throughout the treatment period; iv) in K562 cells exposed to VDS58, TGFB1 expression levels were upregulated for 48 h and decrease afterwards; and v) the re-addition of VDS58 in U-87 MG cultures pretreated with VDS58 resulted in a notable increase in the expression of caspases (CASP3 and CASP9), BCL2‑associated agonist of cell death (BAD), cyclin D1, CDK6, CDKN1, MYC proto-oncogene bHLH transcription factor (MYC), TGFB1 and tumor suppressor protein p53. This upregulation persisted only for 24 h for the majority of genes, as afterwards, only the expression of TGFB1 and MYC was maintained at high levels. Through bioinformatic pathway analysis of RNA-Seq data of parental U-87 MG and K562 cells, substantial variation was reported in the expression profiles of the genes involved in the regulation of the cell cycle. This was associated with the differential pharmacological profiles observed in the same cells exposed to VDS58. Overall, the data presented in this study provide novel insights into the molecular mechanisms of action of sesquiterpene derivatives by dysregulating the expression levels of genes associated with the cell cycle of cancer cells.