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      GSTP alleviates acute lung injury by S-glutathionylation of KEAP1 and subsequent activation of NRF2 pathway

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          Abstract

          Oxidative stress plays an important role in the pathogenesis of acute lung injury (ALI). As a typical post-translational modification triggered by oxidative stress, protein S-glutathionylation (PSSG) is regulated by redox signaling pathways and plays diverse roles in oxidative stress conditions. In this study, we found that GSTP downregulation exacerbated LPS-induced injury in human lung epithelial cells and in mice ALI models, confirming the protective effect of GSTP against ALI both in vitro and in vivo. Additionally, a positive correlation was observed between total PSSG level and GSTP expression level in cells and mice lung tissues. Further results demonstrated that GSTP inhibited KEAP1-NRF2 interaction by promoting PSSG process of KEAP1. By the integration of protein mass spectrometry, molecular docking, and site-mutation validation assays, we identified C434 in KEAP1 as the key PSSG site catalyzed by GSTP, which promoted the dissociation of KEAP1-NRF2 complex and activated the subsequent anti-oxidant genes. In vivo experiments with AAV-GSTP mice confirmed that GSTP inhibited LPS-induced lung inflammation by promoting PSSG of KEAP1 and activating the NRF2 downstream antioxidant pathways. Collectively, this study revealed the novel regulatory mechanism of GSTP in the anti-inflammatory function of lungs by modulating PSSG of KEAP1 and the subsequent KEAP1/NRF2 pathway. Targeting at manipulation of GSTP level or activity might be a promising therapeutic strategy for oxidative stress-induced ALI progression.

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          Highlights

          • GSTP promotes S-glutathionylation (PSSG) of KEAP1 in acute lung injury (ALI).

          • GSTP-catalyzed PSSG of KEAP1 activates NRF2 pathway and alleviates ALI.

          • C434 in KEAP1 is the key PSSG site in this process.

          • Targeting at GSTP might be a promising therapeutic strategy for ALI.

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          Most cited references78

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          Highly accurate protein structure prediction with AlphaFold

          Proteins are essential to life, and understanding their structure can facilitate a mechanistic understanding of their function. Through an enormous experimental effort 1 – 4 , the structures of around 100,000 unique proteins have been determined 5 , but this represents a small fraction of the billions of known protein sequences 6 , 7 . Structural coverage is bottlenecked by the months to years of painstaking effort required to determine a single protein structure. Accurate computational approaches are needed to address this gap and to enable large-scale structural bioinformatics. Predicting the three-dimensional structure that a protein will adopt based solely on its amino acid sequence—the structure prediction component of the ‘protein folding problem’ 8 —has been an important open research problem for more than 50 years 9 . Despite recent progress 10 – 14 , existing methods fall far short of atomic accuracy, especially when no homologous structure is available. Here we provide the first computational method that can regularly predict protein structures with atomic accuracy even in cases in which no similar structure is known. We validated an entirely redesigned version of our neural network-based model, AlphaFold, in the challenging 14th Critical Assessment of protein Structure Prediction (CASP14) 15 , demonstrating accuracy competitive with experimental structures in a majority of cases and greatly outperforming other methods. Underpinning the latest version of AlphaFold is a novel machine learning approach that incorporates physical and biological knowledge about protein structure, leveraging multi-sequence alignments, into the design of the deep learning algorithm. AlphaFold predicts protein structures with an accuracy competitive with experimental structures in the majority of cases using a novel deep learning architecture.
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            OPLS3: A Force Field Providing Broad Coverage of Drug-like Small Molecules and Proteins.

            The parametrization and validation of the OPLS3 force field for small molecules and proteins are reported. Enhancements with respect to the previous version (OPLS2.1) include the addition of off-atom charge sites to represent halogen bonding and aryl nitrogen lone pairs as well as a complete refit of peptide dihedral parameters to better model the native structure of proteins. To adequately cover medicinal chemical space, OPLS3 employs over an order of magnitude more reference data and associated parameter types relative to other commonly used small molecule force fields (e.g., MMFF and OPLS_2005). As a consequence, OPLS3 achieves a high level of accuracy across performance benchmarks that assess small molecule conformational propensities and solvation. The newly fitted peptide dihedrals lead to significant improvements in the representation of secondary structure elements in simulated peptides and native structure stability over a number of proteins. Together, the improvements made to both the small molecule and protein force field lead to a high level of accuracy in predicting protein-ligand binding measured over a wide range of targets and ligands (less than 1 kcal/mol RMS error) representing a 30% improvement over earlier variants of the OPLS force field.
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              Therapeutic targeting of the NRF2 and KEAP1 partnership in chronic diseases

              The transcription factor NF-E2 p45-related factor 2 (NRF2; encoded by NFE2L2) and its principal negative regulator, the E3 ligase adaptor Kelch-like ECH-associated protein 1 (KEAP1), are critical in the maintenance of redox, metabolic and protein homeostasis, as well as the regulation of inflammation. Thus, NRF2 activation provides cytoprotection against numerous pathologies including chronic diseases of the lung and liver; autoimmune, neurodegenerative and metabolic disorders; and cancer initiation. One NRF2 activator has received clinical approval and several electrophilic modifiers of the cysteine-based sensor KEAP1 and inhibitors of its interaction with NRF2 are now in clinical development. However, challenges regarding target specificity, pharmacodynamic properties, efficacy and safety remain.
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                Author and article information

                Contributors
                Journal
                Redox Biol
                Redox Biol
                Redox Biology
                Elsevier
                2213-2317
                06 March 2024
                May 2024
                06 March 2024
                : 71
                : 103116
                Affiliations
                [a ]Clinical Pharmacology Research Center, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, 211198, PR China
                [b ]Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, 32827, United States
                [c ]National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Nanjing University of Chinese Medicine, 138 Xianlin Road, Nanjing, 210023, PR China
                [d ]School of Pharmacy, Key Laboratory of Molecular Pharmacology and Drug Evaluation (Yantai University), Ministry of Education, Collaborative Innovation Center of Advanced Drug Delivery System and Biotech Drugs in Universities of Shandong, Yantai University, Yantai, 264005, PR China
                Author notes
                [* ]Corresponding author. zhangyongjie@ 123456cpu.edu.cn
                [** ]Corresponding author. tianjingwei618@ 123456163.com
                [*** ]Corresponding author. chenxj-lab@ 123456hotmail.com
                [1]

                These authors contributed equally to the work.

                Article
                S2213-2317(24)00092-2 103116
                10.1016/j.redox.2024.103116
                10945259
                38479222
                e563d44e-8e0f-494b-b228-dfa7eabbf65f
                © 2024 The Authors

                This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

                History
                : 21 December 2023
                : 17 February 2024
                : 6 March 2024
                Categories
                Research Paper

                gstp,s-glutathionylation,acute lung injury,oxidative stress,keap1,nrf2

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