Biology subjects

Kurt, H.

Publications and source records attributed to Kurt, H..

4 recordsLinked to original sources

bioRxiv2024

A small molecule enhances arrestin-3 binding to the β2-adrenergic receptor

G protein-coupled receptor (GPCR) signaling is terminated by arrestin binding to a phosphorylated receptor. Binding propensity has been shown to be modulated by stabilizing the pre-activated state of arrestin through point mutations or C-tail truncation. Here, we hypothesize that pre-activated rotated states can be stabilized by small molecules, and this can promote binding to phosphorylation-deficient receptors, which underly a variety of human disorders. We performed virtual screening on druggable pockets identified on pre-activated conformations in Molecular Dynamics trajectories of arrestin-3, and found a compound targeting an activation switch, the back loop at the inter-domain interface. According to our model, consistent with available biochemical and structural data, the compound destabilized the ionic lock between the finger and the back loop, and enabled transition of the gate loop towards the pre-activated state, which stabilizes pre-activated inter-domain rotation. The predicted binding pocket is consistent with saturation-transfer difference NMR data indicating close contact between the piperazine moiety of the compound and C/finger loops. The compound increases in-cell arrestin-3 binding to phosphorylation-deficient and wild-type {beta}2-adrenergic receptor, but not to muscarinic M2 receptor, as verified by FRET and NanoBiT. This study demonstrates that the back loop can be targeted to modulate interaction of arrestin with phosphorylation-deficient GPCRs in a receptor-specific manner.

cell biology↗

bioRxiv2024

Predicting binding events in very flexible, allosteric, multi-domain proteins

Knowledge of the structures formed by proteins and small molecules is key to understand the molecular principles of chemotherapy and for designing new and more effective drugs. During the early stage of a drug discovery program, it is customary to predict ligand-protein complexes in silico, particularly when screening large compound databases. While virtual screening based on molecular docking is widely used for this purpose, it generally fails in mimicking binding events associated with large conformational changes in the protein, particularly when the latter involve multiple domains. In this work, we describe a new methodology to generate bound-like conformations of very flexible and allosteric proteins bearing multiple binding sites by exploiting only information on the unbound structure and the putative binding sites. The protocol is validated on the paradigm enzyme adenylate kinase, for which we generated a significant fraction of bound-like structures. A fraction of these conformations, employed in ensemble-docking calculations, allowed to find native-like poses of substrates and inhibitors (binding to the active form of the enzyme), as well as catalytically incompetent analogs (binding the inactive form). Our protocol provides a general framework for the generation of bound-like conformations of challenging drug targets that are suitable to host different ligands, demonstrating high sensitivity to the fine chemical details that regulate proteins activity. We foresee applications in virtual screening, in the prediction of the impact of amino acid mutations on structure and dynamics, and in protein engineering.

biophysics↗

bioRxiv2023

Parallel, Continuous Monitoring and Quantification of Programmed Cell Death in Plant Tissue

The accurate quantification of hypersensitive response (HR) programmed cell death is imperative for understanding plant defense mechanisms and developing disease-resistant crop varieties. In this study, we report an accelerated phenotyping platform for the continuous-time, rapid and quantitative assessment of HR: Parallel Automated Spectroscopy Tool for Electrolyte Leakage (PASTEL). Compared to traditional HR assays, PASTEL significantly improves temporal resolution and has high sensitivity, facilitating the detection of microscopic levels of cell death. We validated PASTEL by transiently expressing the effector protein AVRblb2 in transgenic lines of the model plant Nicotiana benthamiana (expressing the corresponding resistance protein Rpi-blb2) to reliably induce HR. We were able to detect cell death at microscopic intensities, where leaf tissue appeared healthy to the naked eye one week after infiltration. PASTEL produces large amounts of frequency domain impedance data captured continuously (sub-seconds to minutes). Using this data, we developed a supervised machine learning models for classification of HR. We were able to classify input data (inclusive of our entire tested concentration range) as HR-positive or negative with 84.1% mean accuracy (F1 score = 0.75) at 1 hour and with 87.8% mean accuracy (F1 score = 0.81) at 22 hours. With PASTEL and the ML models produced in this work, it is possible to phenotype disease resistance in plants in hours instead of days to weeks.

plant biology↗

bioRxiv2022

Tracking the circulating SARS-CoV-2 variants in Turkey: Complete genome sequencing and molecular characterization of 1000 SARS-CoV-2 samples

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmissible coronavirus and has caused a pandemic of acute respiratory disease, named coronavirus disease 2019 (COVID-19). COVID-19 has a deep impact on public health as one of the most serious pandemics in the last century. Tracking SARS-CoV-2 is important for monitoring and assessing its evolution. This is only possible by detecting all mutations in the viral genome through genomic sequencing. Moreover, accurate detection of SARS-CoV-2 and tracking its mutations is also required for its correct diagnosis. Potential effects of mutations on the prognosis of the disease can be observed. Assignment of epidemiological lineages in an emerging pandemic requires efforts. To address this, we collected 1000 SARS-CoV-2 samples from different geographical regions in Turkey and analyze their genome comprehensively. To track the virus across Turkey we focus on 10 distinct cities in different geographic regions. Each SARS-CoV-2 genome was analyzed and named according to the nomenclature system of Nextclade and Pangolin Lineage. Furthermore, the frequency of the variations observed in 10 months was also determined by region. In this way, we have observed how the virus mutations and what kind of transmission mechanism it has. The effects of age and disease severity on lineage distribution were other considered parameters. The temporal rates of SARS-CoV-2 variants by time in Turkey were close to the global trend. This study is one of the most comprehensive whole genome analyses of SARS-CoV-2 that represents a general picture of the distribution of SARS-CoV-2 variations in Turkey in 2021. Author SummarySince the outbreak of the COVID-19 pandemic in 2019, the viral genome of SARS-CoV-2 was analysed intensively all over the world both to detect its zoonotic origin and the emerging variants worldwide together with the variants effect on the prognosis and treatment, respectively, of the infection. Remarkable COVID-19 studies were also made in Turkey as it was in the rest of the world. To date, indeed, almost all studies on COVID-19 in Turkey either sequenced only a small number of the viral genome or analysed the viral genome which was obtained from online databases. In respect thereof, our study constitutes a milestone regarding both the huge sample size consisting of 1000 viral genomes and the widespread geographic origin of the viral genome samples. Our study provides new insights both into the SARS-CoV-2 landscape of Turkey and the transmission of the emerging viral pathogen and its interaction with its vertebrate host.

genomics↗