Biology subjects

Durrant, J.

Publications and source records attributed to Durrant, J..

7 recordsLinked to original sources

bioRxiv2026

Cardiomyocyte-specific loss of Smyd5 leads to a robust activation of inflammatory signaling and heart failure in mice.

Background: Cardiomyocytes respond to stress by undergoing hypertrophic growth driven by dynamic changes in gene expression. Epigenetic mechanisms, including histone methylation, play critical roles in regulating these transcriptional programs, yet the enzymes controlling these modifications during cardiac disease remain largely unknown. The SMYD family of histone methyltransferases regulates gene expression in multiple biological contexts, but the function of SMYD5 in the mammalian heart has never been investigated. Methods: SMYD5 expression was assessed in human heart failure samples and in a mouse model of cardiac hypertrophy. To define its functional role in vivo, we generated inducible cardiomyocyte-specific Smyd5 knockout mice and characterized their cardiac phenotype using molecular, histological, and functional analyses. Chromatin immunoprecipitation-quantitative PCR (ChIP-qPCR) was performed to examine histone H4 lysine 20 trimethylation (H4K20me3) at the Il-6 promoter. Results: SMYD5 expression was altered in diseased human and mouse hearts. Under basal conditions, cardiomyocyte-specific deletion of Smyd5 resulted in baseline structural cardiac remodeling and transcriptional signatures characteristic of pathological stress. Smyd5-deficient hearts exhibited marked inflammatory activation resembling a cytokine storm with immune cell infiltration and heart failure. Notably, Smyd5 knockout mice displayed a 100-fold increase in Il-6 expression, accompanied by a global reduction in H4K20me3. ChIP-qPCR analysis of the Il-6 promoter, together with loss- and gain-of-function analysis of SMYD5, supports a direct epigenetic role of SMYD5 in regulating Il-6 expression through H4K20me3 in cardiomyocytes. Conclusions: SMYD5 is a previously unrecognized epigenetic regulator of cardiac homeostasis that restrains inflammatory signaling in cardiomyocytes under normal conditions. Loss of Smyd5 disrupts H4K20me3, leading to derepression of Il-6 in cardiomyocytes and a robust inflammatory response characterized by immune cell recruitment and fibrosis, accompanied by rapid progression of cardiac remodeling and heart failure. These findings identify SMYD5 as a critical regulator of intrinsic cardiomyocyte inflammatory signaling and reveal a novel chromatin-based mechanism contributing to inflammatory cardiomyopathies.

molecular biology↗

bioRxiv2023

Worth the weight: Sub-Pocket EXplorer (SubPEx), a weighted-ensemble method to enhance binding-pocket conformational sampling

1.Structure-based virtual screening (VS) is an effective method for identifying potential small-molecule ligands, but traditional VS approaches consider only a single binding-pocket conformation. Consequently, they struggle to identify ligands that bind to alternate conformations. Ensemble docking helps address this issue by incorporating multiple conformations into the docking process, but it depends on methods that can thoroughly explore pocket flexibility. We here introduce Sub-Pocket EXplorer (SubPEx), an approach that uses weighted ensemble (WE) path sampling to accelerate binding-pocket sampling. As proof of principle, we apply SubPEx to three proteins relevant to drug discovery: heat shock protein 90, influenza neuraminidase, and yeast hexokinase 2. SubPEx is available free of charge without registration under the terms of the open-source MIT license: http://durrantlab.com/subpex/

bioinformatics↗

bioRxiv2022

Hexokinase 2 localizes to the nucleus in response to glucose limitation but does not regulate gene expression

Glucose is the preferred carbon source for most eukaryotes, and the first step in its metabolism is phosphorylation to glucose-6-phosphate. This reaction is catalyzed by a family of enzymes called either hexokinases or glucokinases depending on their substrate specificity. The yeast Saccharomyces cerevisiae encodes three such enzymes, Hxk1, Hxk2 and Glk1. In yeast and mammals, some isoforms of this enzyme are found in the nucleus, suggesting a possible moonlighting function beyond glucose phosphorylation. In contrast to mammalian hexokinases, the yeast Hxk2 enzyme has been proposed to shuttle into the nucleus in glucose replete conditions where it reportedly moonlights as part of a glucose-repressive transcriptional complex. To achieve this role in glucose repression, Hxk2 reportedly binds the Mig1 transcriptional repressor, is dephosphorylated at serine 15 in its N-terminus, and requires an N-terminal nuclear localization sequence (NLS). In this study, we use high-resolution, quantitative, fluorescent microscopy of live cells to determine the conditions, residues, and regulatory proteins required for Hxk2 nuclear localization. In direct contradiction to previous yeast studies, our quantitative imaging demonstrates that Hxk2 is largely excluded from the nucleus under glucose replete conditions but is retained in the nucleus under glucose limiting conditions. Our data show that the Hxk2 N-terminus does not contain an NLS but instead comprises sequences necessary for nuclear exclusion and multimerization regulation. Amino acid substitutions of the phosphorylated residue, serine 15, disrupt Hxk2 dimerization but have no effect on its glucose-regulated nuclear localization. Substitution of alanine at the nearby residue, lysine 13, affects both dimerization and maintenance of nuclear exclusion under glucose replete conditions. Modeling and simulation provide insight into the molecular mechanisms of this regulation. In marked contrast to earlier studies, we find that the transcriptional repressor Mig1 and the protein kinase Snf1 have little effect on Hxk2 localization. Instead, the protein kinase Tda1 is a key regulator of Hxk2 localization. Finally, RNAseq analyses of the yeast transcriptome further dispel the idea that Hxk2 moonlights as a transcriptional repressor, demonstrating that Hxk2 has a negligible role in transcriptional regulation in both glucose replete and limiting conditions. Taken together, our studies provide a paradigm shift for the conditions, residues, and regulators controlling Hxk2 dimerization and nuclear localization. Based on our data, the nuclear translocation of Hxk2 in yeast occurs in glucose starvation conditions, a finding that aligns well with the nuclear regulation of mammalian orthologs of this enzyme. Our findings lay the foundation for future studies of Hxk2 nuclear activity.

cell biology↗

bioRxiv2022

Computational and experimental analyses of alanine racemase suggest new avenues for developing allosteric small-molecule antibiotics

Given the ever-present threat of antibacterial resistance, there is an urgent need to identify new antibacterial drugs and targets. One such target is alanine racemase (Alr), an enzyme required for bacterial cell-wall biosynthesis. Alr is an attractive drug target because it is essential for bacterial survival but is absent in humans. Here, we investigate the Alr from M. tuberculosis (MT), the pathogen responsible for human tuberculosis, as a model Alr enzyme. MT-Alr functions exclusively as an obligate homodimer formed by two identical monomers. Both monomers contribute to the overall composition of their active sites. Therefore, disrupting the dimer interface could inhibit MT-Alr activity. Using computational methods, we identified seven interfacial residues predicted to be responsible for MT-Alr dimerization. Mutating one of the seven residues, Lys261, to alanine resulted in a completely inactive enzyme. Further investigation suggested a potential drug-binding site near Lys261 that might be useful for allosteric drug discovery. SummaryThe bacterial protein alanine racemase (Alr) converts L-alanine to D-alanine, a critical component of the bacterial cell wall. Cycloserine, a known antibiotic, inhibits Alr by binding to the same pocket that alanine binds. Several human proteins have similar pockets, so cycloserine has severe side effects. We identified additional Alr pockets and discovered that altering one of them abolishes Alr activity. Molecules that bind this pocket may similarly impact Alr activity, helping to address the ongoing antibiotic resistance crisis.

biochemistry↗

bioRxiv2022

FPocketWeb: Protein pocket hunting in a web browser

MotivationDetecting macromolecular (e.g., protein) cavities where small molecules bind is an early step in computer-aided drug discovery. Multiple pocket-detection algorithms have been developed over the past several decades. Among them, fpocket, created by Schmidtke and Le Guilloux, is particularly popular. Like many programs used in computational-biology research, fpocket requires users to download and install an executable file. That file must also be run via a command-line interface, further complicating use. An existing fpocket server application effectively addresses these challenges, but it requires users to upload their possibly proprietary structures to a third-party server. ResultsThe FPocketWeb web app builds on this prior work. It runs the fpocket3 executable entirely in a web browser without requiring installation. The pocket-finding calculations occur on the users computer rather than on a remote server. AvailabilityA working version of the open-source FPocketWeb app can be accessed free of charge from http://durrantlab.com/fpocketweb.

pharmacology and toxicology↗

bioRxiv2021

BINANA 2.0: Characterizing Protein/Ligand Interactions in Python and JavaScript

BINding ANAlyzer (BINANA) is an algorithm for identifying and characterizing protein/ligand interactions and other factors that contribute to binding. We recently updated BINANA to make the algorithm more accessible to a broader audience. We have also ported the Python3 codebase to JavaScript, thus enabling BINANA analysis in the web browser. As proof of principle, we created a web-browser application so students and chemical-biology researchers can quickly visualize receptor/ligand complexes and their unique binding interactions.

biochemistry↗

bioRxiv2021

DeepFrag: An Open-Source Browser App for Deep-Learning Lead Optimization

1Lead optimization, a critical step in early-stage drug discovery, involves making chemical modifications to a small-molecule ligand to improve its drug-like properties (e.g., binding affinity). We recently developed DeepFrag, a deep-learning model capable of recommending such modifications. Though a powerful hypothesis-generating tool, DeepFrag is currently implemented in Python and so requires a certain degree of computational expertise. To encourage broader adoption, we have created the DeepFrag browser app, which provides a user-friendly graphical user interface that runs the DeepFrag model in users web browsers. The browser app does not require users to upload their molecular structures to a third-party server, nor does it require the separate installation of any third-party software. We are hopeful that the app will be a useful tool for both researchers and students. It can be accessed free of charge, without requiring registration, at http://durrantlab.com/deepfrag. The source code is also available at http://git.durrantlab.com/jdurrant/deepfrag-app, released under the terms of the open-source Apache License, Version 2.0.

pharmacology and toxicology↗