---
title: "Intrinsically Disordered Regions in NLRP Receptors as Regulatory Hubs for Inflammasome Activation"
id: "frontiers-in-immunology-18-intrinsically-disordered-regions-in-the-nlrp-family-of-receptors-act-as"
canonical_url: "https://medichelpline.com/clinical-feed/frontiers-in-immunology-18-intrinsically-disordered-regions-in-the-nlrp-family-of-receptors-act-as"
content_type: "clinical_feed_article"
specialty: "Infectious Disease"
source_name: "Frontiers in Immunology"
source_url: "https://www.frontiersin.org/articles/10.3389/fimmu.2026.1793320"
published_at: "2026-09-01T00:00:00.000Z"
evidence_level: "Journal Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# Intrinsically Disordered Regions in NLRP Receptors as Regulatory Hubs for Inflammasome Activation
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/frontiers-in-immunology-18-intrinsically-disordered-regions-in-the-nlrp-family-of-receptors-act-as
- **Specialty:** [Infectious Disease](https://medichelpline.com/clinical-feed/infectious-disease.md)
- **Primary Source:** Frontiers in Immunology
- **Source URL:** [Original Journal Publication](https://www.frontiersin.org/articles/10.3389/fimmu.2026.1793320)
- **Published At:** 2026-09-01T00:00:00.000Z
- **Evidence Rating:** Journal Feed
## Executive GIST (TL;DR)
- Source material supplied to the editor contained only site navigation and metadata; the full article text was not included. The only substantive content available is the article title: "Intrinsically disordered regions in the NLRP family of receptors act as regulatory hubs for inflammasome condensation and activation." - From the title, the article addresses **intrinsically disordered regions** (IDRs) within the **NLRP** family of pattern-recognition receptors and their role as regulatory hubs in facilitating or controlling **inflammasome** condensation and activation. - No experimental data, methods, results, figures, or author- and institution-level details were present in the provided source content. - No specifics on which NLRP family members were studied, which IDR sequences or domains were implicated, or what molecular mechanisms were proposed were available in the source. - The source did not report experimental systems (in vitro, cellular, or in vivo), techniques used (biochemistry, imaging, structural biology), or quantitative endpoints (e.g., condensation metrics, activation readouts such as cytokine release or caspase activation). - Information on clinical relevance, translational implications, or therapeutic strategies that might stem from the findings was not present in the provided material. - Author names, affiliations, funding, conflict of interest statements, and references were not included in the supplied content. - Because the supplied content was incomplete, readers should consult the original Frontiers in Immunology article for full details; those specifics were not reported in the provided source.
## Clinical Analysis & Structured Key Points
Frontiers | Intrinsically disordered regions in the NLRP family of receptors act as regulatory hubs for inflammasome condensation and activation HYPOTHESIS AND THEORY article Front. Immunol. , 01 September 2026 Sec. Systems Immunology Volume 17 - 2026 | https://doi.org/10.3389/fimmu.2026.1793320 Published in Frontiers in Immunology Systems Immunology 7 impact factor 11.3 citescore Part of a Research Topic Computational Modeling and Applications of Systems Immunology in Hispanic America Submission open 12k views 3 articles Editor & Reviewers Edited by J E Jesús Espinal-Enríquez Reviewed by L Y Ling Yin M C Marcelo Cardoso Dos Reis Melo Outline Figures and Tables Figure 1 View in article Figure 2 View in article Figure 3 View in article Figure 4 View in article Figure 5 View in article Figure 6 View in article Figure 7 View in article Table 1 Intrinsically disordered regions in human NLRPs. View in article Table 2 Disease-associated mutations within intrinsically disordered regions of NLRP1, NLRP3, and NLRP14. View in article HYPOTHESIS AND THEORY article Front. Immunol. , 01 September 2026 Sec. Systems Immunology Volume 17 - 2026 | https://doi.org/10.3389/fimmu.2026.1793320 Intrinsically disordered regions in the NLRP family of receptors act as regulatory hubs for inflammasome condensation and activation T B Teresa B. Nava-Ramírez 1 C L Cesar L. Cuevas-Velazquez 2 A A Alejandra A. Covarrubias 1 E R Enrique Rudiño-Piñera 3 L P Leonor Pérez-Martínez 4 G P Gustavo Pedraza-Alva 4 * 1. Departamento de Biología Molecular de Plantas, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Morelos, Mexico 2. Centro de Investigación en Biotecnología, Universidad Autónoma del Estado de Morelos, Cuernavaca, Morelos, Mexico 3. Laboratorio de Bioquímica Estructural, Departamento de Medicina Molecular y Bioprocesos, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Morelos, Mexico 4. Laboratorio de Neuroinmunobiologia, Departamento de Medicina Molecular y Bioprocesos, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Morelos, Mexico See more Article metrics View details Abstract Inflammasomes are multiprotein complexes that orchestrate immune responses to pathogenic and sterile insults by regulating the maturation of inflammatory cytokines and pyroptotic cell death. While inflammasome activation is well-characterized at the biochemical level, the mechanisms governing the spatial and temporal assembly of these complexes remain poorly understood. Here, we uncover a critical role for intrinsically disordered regions (IDRs) in activating NLRP1, NLRP3, and NLRP14 inflammasomes. Through structural prediction analyses, we identify IDRs within these receptors that harbor post-translational modification sites essential for inflammasome assembly and function. Notably, disease-associated mutations in NLRP1 and NLRP3 occur within these IDRs, underscoring their functional relevance in inflammatory disorders. Our computational analysis suggests that IDR-mediated phase separation may drive inflammasome condensation at the perinuclear membrane, serving as a sensor for cellular stress, as stress signals may change their conformation, through post-translational modifications, and thus their interaction capacity. Furthermore, inflammasomes lacking IDRs in their NLRPs may rely on interactions with chaperone or adapter proteins containing IDRs for proper assembly. These insights provide a new framework for understanding the regulation of inflammasomes, suggesting that targeting the dynamics of phase transitions could open novel therapeutic avenues for treating inflammatory and autoimmune diseases. Introduction Inflammation plays a pivotal role as a biological response mechanism restoring homeostasis following various detrimental insults, ranging from pathogenic invasions to physical injuries. This intricate response involves the recognition of pathogens and damage-associated molecular patterns by a class of receptors known as pattern recognition receptors (PRRs), which include toll-like receptors (TLRs) and NOD-like receptors (NLRs), among others. Upon engagement with their respective ligands, these receptors initiate a cascade of events leading to the expression of genes encoding inflammatory cytokines such as TNF, IL-6, IFNγ, IL-18, and IL-1β. While TNF, IL-6, and IFNγ are rapidly secreted upon synthesis, IL-1β and IL-18 require proteolytic cleavage by inflammatory caspases such as caspase-1 and caspase-11 to attain their mature and active cytokine forms. This cleavage event requires a secondary signal, triggered by various factors, including cell membrane damage, endosomal injury, oxidative stress, or cytosolic DNA, whether of foreign (from bacterial or viral sources) or endogenous (genomic or mitochondrial) origin (Reviewed in ( 1 )). The detection of this secondary signal is mediated by a class of receptors known as NLRP receptors (Nucleotide-binding Oligomerization Domain, Leucine-rich Repeat, and Pyrin domain-containing). Upon activation, these receptors undergo a conformational change that promotes their oligomerization and interaction with caspase-1, either directly or via the adapter molecule ASC. This interaction leads to the formation of a multiprotein complex known as the inflammasome. The formation of this complex facilitates the self-activation of caspase-1 to its active form, thereby initiating the production of inflammatory cytokines or triggering a form of inflammatory cell death known as pyroptosis (Reviewed in ( 1 )). Activation of the inflammasome by various stimuli, including excess energy, β-amyloid peptide, cholesterol, and uric acid, contributes to the perpetuation of chronic inflammation. This sustained inflammatory state can give rise to the development of various pathologies, including type 2 diabetes, neurodegenerative disorders such as Alzheimer’s disease, gout, and even cancer (Reviewed in ( 2 )). Despite our ever-evolving understanding of these processes, the exact mechanisms governing inflammasome assembly and activation remain incompletely understood. Recent studies have revealed a common factor in the activation of the NLRP3 inflammasome in response to diverse insults: the efflux of potassium ions (K + ) ( 3 ). Additionally, variations in cell volume and exposure to hyper-osmotic signals, such as high salt concentrations, can trigger inflammasome assembly and activation ( 4 ). The mechanism by which a decrease in cytosolic K + concentrations or changes in cellular volume cause inflammasome components to relocate to a specific area of the perinuclear membrane, leading to the formation of a macromolecular protein complex that promotes inflammation, remains a mystery. Biomolecular condensates, dynamic and membrane-less subcellular compartments formed through phase separation or phase transition, have emerged as crucial players in key cellular processes (Reviewed in ( 5 )). These condensates arise from weak yet multivalent interactions between proteins and/or nucleic acids, favoring compartmentalization. This segregation of specific molecules and reactions within the crowded cellular milieu plays a pivotal role in various cellular processes, including gene expression, signal transduction, and stress responses, by enhancing reaction rates and enabling localized functions that promote cell survival (Reviewed in ( 6 )). Consequently, the dysregulation of phase transitions and condensate formation has been linked to various diseases, notably neurodegenerative disorders such as amyotrophic lateral sclerosis and frontotemporal dementia ( 7 ). In recent years, the study of biomolecular phase transitions and the role of proteins containing intrinsically disordered regions (IDRs) have attracted considerable attention (Reviewed in ( 8 )). These IDRs, which lack a stable tertiary structure under physiological conditions, exhibit high conformational flexibility and can interact with various molecular partners. This dynamic nature enables them to contribute to the formation of biomolecular condensates (reviewed in ( 5 )). Proteins that contain IDRs are often found in condensates due to their ability to undergo liquid-liquid phase separation ( 8 ). The interactions these proteins engage in can range from weak and transitory to strong and specific, creating a diverse spectrum of molecular compositions within these structures ( 9 ). Given the multi-protein nature of the inflammasome and its specific perinuclear assembly within the cell, we hypothesized that phase-transition processes and IDRs in the NLRP family members, ASC, and inflammatory caspases might play pivotal roles in sensing cellular physicochemical changes triggered by noxious stimuli, thereby leading to inflammasome activation and inflammation. Nonetheless, this intriguing possibility has received limited attention. Here, we explore the role of IDRs in inflammasome formation and activation through an in-depth analysis of predicted protein structures using AlphaFold. Our findings revealed the presence of IDRs in several members of the NLRP family of receptors. Specifically, we focus our attention and discuss the potential roles of these IDRs in the function of NLRP1, NLRP3, and NLRP14. Our data demonstrate that the IDR within the NLRP1 and NLRP3 inflammasome encompasses sequences containing amino acid residues that undergo post-translational modifications crucial for inflammasome formation and activation. Additionally, we observed mutations in the NLRP1 receptor correlated with Vitiligo-associated multiple autoimmune disease susceptibility 1, and in the NLRP3 receptor correlated with inflammatory diseases, such as familial fever syndrome, occurring within the identified IDRs. In the case of NLRP14, the IDR we uncovered may regulate its interaction with other proteins, facilitating oocyte fertilization. Our findings suggest that the assembly of inflammasomes lacking IDRs in their NLRPs may be governed by interactions between NLRPs and chaperone or adapter proteins containing IDRs. Methodology Prediction of IDRs in the NLRP protein family To ascertain the presence of intrinsically disordered regions (IDRs) within the NLRPs protein family, we analyzed the amino acid sequences of human NLRPs family proteins obtained from Uniprot (NLRP1- Q9C000, NLRP2-Q9NX02, NLRP3- Q96P20, NLRP4-Q96MN2, NLRP5-P59047, NLRP6-P59044, NLRP7 Q8WX94, NLRP8-Q86W28, NLRP9- Q288C4, NLRP10-Q86W26, NLRP11- P59045, NLRP12-P59046, NLRP13-Q86W25, NLRP14- Q86W24). An in silico analysis was performed employing three disorder prediction tools: the DisEMBL server, IUPRED, and MobiDB ( 10 – 12 ). We employed MobiDB to corroborate the results, as it calculates a disorder consensus score by considering the outcomes of various predictors and their variants (such as Espritz, IUPred, DisEMBL, GlobPlot, etc.) ( 12 ). For the DDX3X family disorder prediction, we employed the database D2P2. These predictors assess the disorder status of each amino acid residue within a protein, providing a disorder probability value ranging from 0.0 to 1.0. Regions with a value ≥0.5 are typically classified as IDRs. Prediction of protein structures by AlphaFold Since there are no available crystallographic structures of the NLRPs monomers in the Protein Data Bank, we obtained predicted structures of the NLRPs monomers, including their disordered regions, using the AlphaFold2 platform. These models are used for all the figures except the Supplementary Figures 2 , 3 , and 10 . Structural models of NLRP1, NLRP3, and NLRP14 in both their phosphorylated and non-phosphorylated states were generated using the AlphaFold 3 server. The predicted structures were subsequently aligned and compared with the corresponding AlphaFold 2 models using PyMOL (The PyMOL Molecular Graphics System, Version 3.0, Schrödinger, LLC). Phosphorylation sites incorporated into the models were retrieved from the GlyGen and PeptideAtlas databases. Determination of liquid-liquid phase separation propensity index To assess the potential for liquid-liquid phase separation and the likelihood of protein condensate formation within the NLRPs, we employed FuzDrop ( 13 ). This computational tool calculates the probability of an amino acid sequence to undergo liquid-liquid phase separation (pLLPS). Proteins with pLLPS values greater than or equal to 0.60 are considered capable of spontaneously undergoing liquid-liquid phase separation. Additionally, the program predicts the probability of each amino acid residue participating in interactions that promote condensate formation, enabling the identification of specific regions within the protein sequence with the highest likelihood of undergoing liquid-liquid phase separation ( 13 ). Sequence and structure alignments of NLRPs with IDRs To assess the conservation of IDRs within the NLRPs, we conducted two types of alignments: one for amino acid sequences and another for protein structures. For the amino acid sequence alignment, we utilized the sequences of human NLRP1, NLRP3, and NLRP14 as references. To compile a diverse set of sequences, we conducted a BLAST search on the NCBI BLAST server and obtained 250 different Chordata sequences. These sequences were aligned using the ClustalW algorithm implemented in MEGA software ( 14 ). Manual curation was performed to refine the alignment. The previously obtained monomer 3D structures of human NLRPs were used for the structural alignments against the 3D models generated by AlphaFold2. Additionally, we selected two or three proteins from different animal species for which the monomeric structure was predicted using AlphaFold2. To superpose these 3D structures, we employed the POSA server, a tool designed for multiple alignments of protein coordinates ( 15 ). Determination of NLRPs interaction zones with other proteins To identify amino acid sequences of NLRP1, NLRP3, and NLRP14 with a high probability of interaction with other proteins, we utilized the InterProSurf server. This server predicts the likelihood that the surfaces of a protein structure can engage in various types of interactions with other proteins ( 16 ). The protein 3D models of NLRP1, NLRP3, and NLRP14 obtained through AlphaFold2 were employed for this analysis. Amino acids with the highest probability of interaction were highlighted in red, while those with a medium likelihood of being involved in protein-protein interactions were marked in green. To identify potential interaction partners, protein association networks were generated using the STRING server ( 17 ). We obtained interaction networks for human NLRP1, NLRP3, and NLRP14. For subsequent molecular docking experiments, we selected the proteins ASC, TxNIP, and TBK1 as their interactions with NLRP1, NLRP3, and NLRP14, respectively, have been experimentally demonstrated. Molecular docking We conducted molecular docking analyses to assess potential interactions between the IDRs of NLRP1, NLRP3, and NLRP14 with ASC, TxNIP, and TBK1, respectively. For this purpose, we utilized the HDock server. We chose this server because it predicts binding complexes between molecules, such as proteins, using a hybrid docking strategy. This strategy enables the seamless integration of experimental data, such as protein–protein interface information and SAXS data, to refine docking poses and enhance the reliability of the results. Only interaction complexes involving the IDRs of NLRP1, NLRP3, and NLRP14, with a docking score value less than -200 and a confidence score value greater than 0.7, were selected. These criteria indicate a high likelihood of interaction, as determined by the HDock algorithm ( 18 ). To further evaluate the robustness of the predicted interaction patterns, complementary protein-protein docking analyses were performed using ClusPro ( 19 ). To investigate mutant variants located within the IDRs of NLRP1, NLRP3, and NLRP14 and associated with specific pathologies, we searched the dbSNP database from NCBI. Subsequently, the PremPs server was used to predict how these mutations might affect the structure of NLRP proteins. PremPs evaluates the effects of individual mutations on protein stability by calculating quantitative changes in the Gibbs free energy. The protein structures obtained from AlphaFold2 for NLRP1, NLRP3, and NLRP14, along with the selected mutations within the IDRs, were used to determine changes in the Gibbs free energy, while the changes in the structure were corroborated by analyzing and comparing with the regions of the structures with available experimentally determined 3D structures deposited in the PDB. To confirm the effect of these mutations, we used the available crystallographic structures in the PDB of some NLRPs (PDB entry 7ALV for NLRP3, PDB entry 4N1L for NLRP14, and PDB entry 1PN5 for NLRP1). The mutations resulting in significant changes in NLRP protein structures (considering a highly destabilizing ΔΔGexp ≥ 1.0 kcal mol-1 or highly stabilizing ΔΔGexp ≤ -1.0 kcal mol-1) were analyzed by molecular docking to assess their interaction potential. Results and discussion NLRPs contain intrinsically disordered regions predicted within their structural composition We analyzed the NLRP gene family encompassing NLRP 1–14 in humans to ascertain the presence of IDR within their sequences. We identified IDRs in 11 NLRPs (1, 3, 5, 6, 7, 8, 9, 10, 11, 13, 14) ( Table 1 ). These regions exhibited disorder scores of ≥ 0.5, as determined by the IUPRED and MobiDB predictors, supporting their computational classification as predicted IDRs; this threshold is standard in the field, but not definitive, and disorder predictions are inherently probabilistic rather than experimentally confirmed. Long IDRs were defined as those containing ≥30 residues, whereas short IDRs contained between 5 and 30 residues ( 20 ) ( Supplementary Figure 1 ). For further characterization, we focused on NLRP1, NLRP3, and NLRP14 because NLRP1 and NLRP3 play key roles in initiating inflammatory responses to diverse stimuli, whereas NLRP14 has been implicated in regulating the cellular responses to DNA. Table 1 Protein IDR Sequence Region aa Domain NLRP1 IDR1 AGHSPSFPYSPSEP 90-113 After PYD IDR2 LPSSPDHESPSQESPNAPTSTAVLGSWGSPPQPSLAPREQEAPGTQWPLDETSGIYYTEIREREREKSEKGRPPWAAVVGTPPQAHTSLQPHHHP 160-254 Polar residues/disorder IDR3 VMTPTEGLDTGEMSNSTSSLKRQRLGS 991-1017 After LRR6/disorder NLRP2 IDR1 NKRKPLSLGITRKERPPLDVDEMLERFKTEAQAFTETKGNVICLGKEVFKGKKPDK 101-156 After PYD NLRP3 IDR1 DEPKWGSDNARVSNPTVICQEDSIEEEWMGLLEYLSRISIC 90-130 After PYD IDR2 QEREQELLAIGKTKTCE 181-197 FISNA IDR3 NMPKEEEEEEKEGRHLDMVQCVLPSSSHAACSHGL 686-720 Acidic Loop NLRP5 IDR1 MKVAGGLELGAAALLSASPRALVTLSTGPTCSILPKNPLFPQNLSSQPCIKMEGD 1-56 N terminal IDR2 RDDMKRHSPEDPEATMTDQGPSKEKVPGISQAVQQDSATAAETKEQEISQAMEQEGATAAETEEQEISQAMEQEGATAAETEEQGHGGDT 142-232 After PYD/Disorder NLRP6 IDR1 APEEAMGPAEEPEPGRARRSDTHT 157-181 After PYD/Disorder IDR2 PEVTEGAKGLEDTEEPEEEEEGEE 585-614 After LRR1/Disorder NLRP7 IDR1 VQEIDNPELGDAEEDSELAKPGEKEGW 97-123 After PYD/Disorder NLRP8 IDR1 MSDVNPPSDTPIPFSSSSTHSSHIPPW 1-23 N- terminal IDR2 PTPHPPDFTGKSDCLSQINP 1029-1048 C- terminal NLRP10 IDR1 GIQMNNVSFKIKHSNEKKSQSQNLFSVKSSLSHGPKEEQKCPSVHGQKEGKDNIAGTQKEASTGKGRGTEETPKNTYI 578-655 C-terminal/Disorder NLRP12 IDR1 RDTPPGGPSSLGNQSTCLLEVSLVTPRKD 96-124 After PYD NLRP13 IDR1 MNFSVITCPNGG 1-12 N-terminal IDR2 ENVQTQELQDPTQEDLEMLEAAAGNMQTQGCQDPNQEELDELEEETGNVQAQGCQDPNQEEPEMLEE 107-173 After PYD NLRP14 IDR1 MADSSSS 1-7 Before PYD/Disorder IDR2 IGPDDAKAGETQEDQEAVLG 102-121 After PYD/Disorder Intrinsically disordered regions in human NLRPs. Nucleotide-binding oligomerization domain, Leucine rich Repeat and Pyrin domain containing from 1 to 14. AlphaFold 2 was selected for the structural prediction of the NLRPs owing to the absence of experimentally resolved full-length monomeric structures for these proteins. The comparison between structural models generated by AlphaFo
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