Biology subjects

Eriksson, L. A.

Publications and source records attributed to Eriksson, L. A..

9 recordsLinked to original sources

bioRxiv2025

FMO4 drives lung adenocarcinoma by stabilizing the MAT2A/MAT2B complex and hindering ferroptosis

Lung cancer is the leading cause of death by cancer in the world and finding new targets is a major medical need to tackle this disease. Here, upon proteomic analysis to identify common players in oncogenic EGFR- and KRAS-driven lung adenocarcinoma mouse models, we uncovered a largely unknown protein in cancer, flavin-containing monooxygenase 4 (FMO4), whose expression was increased in lung tumors compared with adjacent lung tissue. FMO4 expression was strongly increased also in lung cancer samples from patients compared with healthy lung, and its expression level was inversely correlated with overall survival. Remarkably, in vivo deletion of FMO4 greatly decreased tumor burden and increased survival in oncogenic KRAS-driven lung adenocarcinoma mice unveiling its crucial role in tumor biology. Mechanistically, we found that FMO4 loss of function promotes ferroptosis and cooperates with ferroptosis inducers in vitro and in vivo. Moreover, FMO4 facilitates the interaction between MAT2A and MAT2B, promoting the generation of cysteine from methionine, which in turn boosts the generation of glutathione, thus protecting lung adenocarcinoma against ferroptosis. In summary we identified a new target in lung adenocarcinoma with important implications in cancer biology.

cancer biology↗

bioRxiv2025

MolAI: A Deep Learning Framework for Data-driven Molecular Descriptor Generation and Advanced Drug Discovery Applications

This study introduces MolAI, a robust deep learning model designed for data-driven molecular descriptor generation. Utilizing a vast training dataset of 221 million unique compounds, MolAI employs an autoencoder neural machine translation (NMT) model to generate latent space representations of molecules. The model demonstrated exceptional performance through extensive validation, achieving a 99.99% accuracy in regenerating input molecules from their corresponding latent space. This study showcases the effectiveness of MolAI-driven molecular descriptors by developing an ML-based model (iLP) that accurately predicts the predominant protonation state of molecules at neutral pH. These descriptors also significantly enhance ligand-based virtual screening and are successfully applied in a framework (iADMET) for predicting ADMET features with high accuracy. This capability of encoding and decoding molecules to and from latent space opens unique opportunities in drug discovery, structure-activity relationship analysis, hit optimization, de novo molecular generation, and the training infinite machine learning models. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=88 SRC="FIGDIR/small/644888v1_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@aa4cdforg.highwire.dtl.DTLVardef@9cedd8org.highwire.dtl.DTLVardef@c32f68org.highwire.dtl.DTLVardef@5d7716_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2024

Proximity Interactome analyses unveil novel regulators of IRE1a canonical signaling

The unfolded protein response (UPR) is a key adaptive pathway that controls endoplasmic reticulum (ER) homeostasis. The UPR is transduced by three ER-resident sensors of ER homeostasis disruption in the lumen of this compartment. They trigger select downstream signaling pathways in the cytosol and nucleus. Among them, IRE1 (referred to as IRE1 hereafter), a type I transmembrane protein, senses accumulation of improperly folded proteins in the ER lumen and transduces signals through both kinase and endoribonuclease (RNase) activities in the cytosol. IRE1 catalyzes XBP1 mRNA unconventional splicing and RNA degradation (Regulated IRE1 Dependent Decay, termed RIDD). Recent studies have reported that IRE1-dependent protein-protein interactions (PPi) drive additional non-canonical IRE1 functions. Herein, we define the IRE1 signalosome as a list of IRE1 binding partners (direct or not) which alter IRE1 signaling towards XBP1 mRNA splicing and RIDD. Here we determined the IRE1 in situ interactome using BioID, putatively connecting IRE1 to previously unrecognized cellular functions. In addition, we link the binding of several IRE1 partners to the regulation of its RNase. Furthermore, we identify HNRNPL as an IRE1-interacting partner, previously unrecognized, which stabilizes IRE1 under basal conditions by counteracting ERAD-mediated degradation. Overall, the characterization of the IRE1 signalosome not only reveals the multi-faceted control of IRE1 RNase activity and stability by its interacting partners and allow us to discuss putative additional IRE1 regulators and cellular functions based on the nature of its interactome and its localization.

biochemistry↗

bioRxiv2024

iScore: A ML-Based Scoring Function for de novo Drug Discovery

In the quest for accelerating de novo drug discovery, the development of efficient and accurate scoring functions represents a fundamental challenge. This study introduces iScore, a novel machine learning (ML)-based scoring function designed to predict the binding affinity of protein-ligand complexes with remarkable speed and precision. Uniquely, iScore circumvents the conventional reliance on explicit knowledge of protein-ligand interactions and full picture of atomic contacts, instead leveraging a set of ligand and binding pocket descriptors to evaluate binding affinity. This approach avoids the inefficient and slow conformational sampling stage, thereby enabling the rapid screening of ultra-huge molecular libraries, a crucial advancement given the practically infinite dimensions of chemical space. iScore was rigorously trained and validated using the PDBbind 2020 refined set, CASF 2016, and CSAR NRC-HiQ Set1/2, employing three distinct ML methodologies: Deep Neural Network (iScore-DNN), Random Forest (iScore-RF), and eXtreme Gradient Boosting (iScore-XGB). A hybrid model, iScore-Hybrid, was subsequently developed to incorporate the strengths of these individual base learners. The hybrid model demonstrated a Pearson correlation coefficient (R) of 0.78 and a root mean square error (RMSE) of 1.23 in cross-validation, outperforming the individual base learners and establishing new benchmarks for scoring power (R = 0.814, RMSE=1.34), ranking power ({rho} = 0.705), and screening power (success rate at top 10% = 73.7%).

bioinformatics↗

bioRxiv2022

Gene editing is suitable to treat GM1 Gangliosidosis: a proof-of-concept study

Ganglioside-monosialic acid (GM1) gangliosidosis, a rare autosomal recessive disorder, is frequently caused by deleterious single nucleotide variants (SNVs) in GLB1 gene. These variants result in reduced {beta}-galactosidase ({beta}-gal) activity, leading to neurodegeneration associated with premature death. Currently, no effective therapy for GM1 gangliosidosis is available. Three ongoing clinical trials aim to deliver a functional copy of the GLB1 gene to stop disease progression. Here, we show that 41% of GLB1 pathogenic SNVs might be cured by adenine base editors (ABEs). Our results demonstrate that ABE efficiently corrects the pathogenic allele in patient-derived fibroblasts, restoring a therapeutic level of {beta}-gal activity. Unbiased off-target DNA analysis did not detect off-target editing activity in treated patients cells except a bystander edit without consequences on {beta}-gal activity. Altogether our results suggest that gene editing is an alternative strategy to cure GM1 gangliosidosis, by correcting the root cause of disease and avoiding repetitive adeno-associated virus injections.

genetics↗

bioRxiv2022

Mechanical strain stimulates COPII-dependent trafficking via Rac1

Secretory trafficking from the endoplasmic reticulum (ER) is subject to regulation by extrinsic and intrinsic factors. While much of the focus has been on biochemical triggers, little is known whether and how the ER is subject to regulation by mechanical signals. Here, we show that COPII-dependent ER-export is regulated by mechanical strain. Mechanotransduction to the ER was mediated via a previously unappreciated ER-localized pool of the small GTPase Rac1. Mechanistically, we show that Rac1 interacts with the small GTPase Sar1 to drive budding of COPII carriers and stimulate ER-to-Golgi transport. Altogether, we establish an unprecedented link between mechanical strain and export from the ER.

cell biology↗

bioRxiv2021

SARS-CoV2 envelop proteins reshape the serological responses of COVID-19 patients

The SARS-CoV-2 pandemic has elicited a unique international mobilization of the scientific community to better understand this coronavirus and its associated disease and to develop efficient tools to combat infection. Similar to other coronavirae, SARS-CoV-2 hijacks the host cell complex secretory machinery to produce properly folded viral proteins that will compose the nascent virions; including Spike, Envelope and Membrane proteins, the most exposed membrane viral proteins to the host immune system. Antibody response is part of the anti-viral immune arsenal that infected patients develop to fight viral particles in the body. Herein, we investigate the immunogenic potential of Spike (S), Envelope (E) and Membrane (M) proteins using a human cell-based system to mimic membrane insertion and N-glycosylation. We show that both S and M proteins elicit the production of specific IgG, IgM and IgA in SARS-CoV-2 infected patients. Elevated Ig responses were observed in COVID+ patients with moderate and severe forms of the disease. Finally, when SARS-CoV-2 Spike D614 and G614 variants were compared, reduced Ig binding was observed with the Spike G614 variant. Altogether, this study underlines the needs for including topological features in envelop proteins to better characterize the serological status of COVID+ patients, points towards an unexpected immune response against the M protein and shows that our assay could represent a powerful tool to test humoral responses against actively evolving SARS-CoV-2 variants and vaccine effectiveness.

cell biology↗

bioRxiv2020

Stress-induced tyrosine phosphorylation of RtcB modulates IRE1 activity and signaling outputs.

Endoplasmic Reticulum (ER) stress is a hallmark of various diseases, which is dealt with through the activation of an adaptive signaling pathway named the Unfolded Protein Response (UPR). This response is mediated by three ER-resident sensors and the most evolutionary conserved, IRE1 signals through its cytosolic kinase and endoribonuclease (RNase) activities. IRE1 RNase activity can either catalyze the initial step of XBP1 mRNA unconventional splicing or degrade a number of RNAs through Regulated IRE1- Dependent Decay (RIDD). The balance between these two activities plays an instrumental role in cells life and death decisions upon ER stress. Until now, the biochemical and biological outputs of IRE1 RNase activity have been well documented, however, the precise mechanisms controlling whether IRE1 signaling is adaptive or pro-death (terminal) remain unclear. This prompted us to further investigate those mechanisms and we hypothesized that XBP1 mRNA splicing and RIDD activity could be co-regulated by the IRE1 RNase regulatory network. We showed that a key nexus in this pathway is the tRNA ligase RtcB which, together with IRE1, is responsible for XBP1 mRNA splicing. We demonstrated that RtcB is tyrosine phosphorylated by c-Abl and dephosphorylated by PTP1B. Moreover, we identified RtcB Y306 as a key residue which, when phosphorylated, perturbs RtcB interaction with IRE1, thereby attenuating XBP1 mRNA splicing and favoring RIDD. Our results demonstrate that the IRE1 RNase regulatory network is dynamically fine-tuned by tyrosine kinases and phosphatases upon various stresses and that the nature of the stress determines cell adaptive or death outputs.

biochemistry↗

bioRxiv2019

Structural distortions induced by Kinase Inhibiting RNase Attenuator (KIRA) compounds prevent the formation of face-to-face dimers of Inositol Requiring Enzyme 1α

Inositol-Requiring Enzyme 1 (IRE1) is a transmembrane dual kinase/ribonuclease protein involved in propagation of the unfolded protein response (UPR). IRE1 is currently explored as a potential drug target due to growing evidence of its role in variety of disease conditions. Upon activation, IRE1 cleaves X-box Binding Protein 1 (XBP1) mRNA through its RNase domain. Small molecules targeting the kinase site are known to either increase or decrease RNase activity, but the allosteric relationship between the kinase and RNase domains of IRE1 is poorly understood. Subsets of IRE1 kinase inhibitors (known as \"KIRA\" compounds) bind to the ATP-binding site and allosterically impede the RNase activity. KIRA compounds are able to regulate the RNase activity by stabilizing monomeric form of IRE1.\n\nIn the present work, computational analysis, protein-protein and protein-ligand docking studies, and molecular dynamics simulations were applied to different IRE1 dimer systems to provide structural insights into the perturbation of IRE1 dimers by small molecules kinase inhibitors that regulate the RNase activity. By analyzing structural deviations, energetic components and number of hydrogen bonds in the interface region, we propose that the KIRA inhibitors act at an early stage of IRE1 activation by interfering with IRE1 face-to-face dimer formation, thus disabling the activation of the RNase domain. The work sheds light on the mechanism of action of KIRA compounds and may assist in development of further compounds in e.g. cancer therapeutics. The work also provides information on the sequence of events and protein-protein interactions initiating the unfolded protein response.\n\nNon-technical SummaryThe unfolded protein response is a protective feedback mechanism whereby cells regulate high levels of misfolded proteins in the endoplasmic reticulum. Due to its significance in cell survival, the UPR has become an interesting target in cancer therapy. A key pathway of the UPR is initiated by the activation of inositol requiring enzyme 1 (IRE1), which must first dimerise in order to mediate the stress signal. Different inhibitors have been proposed in order to block the UPR at the level of IRE1. We here unveil, through detailed computational studies, the mode of action of a set of IRE1 inhibitors targeting the kinase domain, which in turn helps us to further understand the mechanism of activation and progression of the UPR.

biochemistry↗