Protein Binding Sites Research Articles

Pharmacophore modelling based virtual screening and molecular dynamics identified the novel inhibitors and drug targets against Waddlia chondrophila

Waddlia chondrophila is a possible cause of fetal death in humans. This Chlamydia-related bacterium is an emergent pathogen that causes human miscarriages and ruminant abortions, which results in financial losses. Despite the years of efforts, the underlying mechanism behind the pathogenesis of W. chondrophila is little known which hindered the development of novel treatment options. In the framework of current study, computational approaches were used to identify novel inhibitors (phytocompounds) and drug targets against W. chondrophila. At first, RNA polymerase sigma factor SigA and 3-deoxy-d-manno-octulosonic acid transferase were identified through subtractive proteomics pipeline. Afterwards, extensive docking and simulation analyses were conducted to optimize potentially novel phytocompounds by assessing their binding affinity to target proteins. A 100ns molecular dynamics simulation well complimented the compound's binding affinity and indicated strong stability of predicted compounds at the docked site. The calculation of binding free energies with MMGBSA corroborated the significant binding affinity between phytocompounds and target protein binding sites. The proposed phytocompounds may be a viable treatment option for patients infected with W. chondrophila; however, further research is required to ensure their safety.

Machine Learning in Enhancing Protein Binding Sites Predictions - What Has Changed Since Then?

Accurate identification of protein binding sites is pivotal for understanding molecular interactions and facilitating drug discovery efforts. However, the dynamic nature of proteinligand interactions presents a formidable challenge, necessitating innovative approaches to bridge the gap between theoretical predictions and experimental realities. This review explores the challenges and recent advancements in protein binding site prediction. Specifically, we highlight the integration of molecular dynamics simulations, machine learning, and deep learning techniques to capture the dynamic and complex nature of protein-ligand interactions. Additionally, we discuss the importance of integrating experimental data, such as structural information and biochemical assays, to enhance prediction accuracy and reliability. By navigating the intersection of classical and the onset of machine learning and deep learning approaches, we aim to provide insights into current state-of-the-art techniques and chart a course for future protein binding site prediction advancements. Ultimately, these efforts could unravel the mysteries of protein-ligand interactions and accelerate drug discovery endeavors.

Prediction of drug–target binding affinity based on multi-scale feature fusion

Accurate prediction of drug–target binding affinity (DTA) plays a pivotal role in drug discovery and repositioning. Although deep learning methods are widely used in DTA prediction, two significant challenges persist: (i) how to effectively represent the complex structural information of proteins and drugs; (ii) how to precisely model the mutual interactions between protein binding sites and key drug substructures. To address these challenges, we propose a MSFFDTA (Multi-scale feature fusion for predicting drug target affinity) model, in which multi-scale encoders effectively capture multi-level structural information of drugs and proteins are designed. And then a Selective Cross Attention (SCA) mechanism is developed to filter out the trivial interactions between drug–protein substructure pairs and retain the important ones, which will make the proposed model better focusing on these key interactions and offering insights into their underlying mechanism. Experimental results on two benchmark datasets demonstrate that MSFFDTA is superior to several state-of-the-art methods across almost all comparison metrics. Finally, we provide the ablation and case studies with visualizations to verify the effectiveness and the interpretability of MSFFDTA. The source code is freely available at https://github.com/whitehat32/MSFF-DTA/.

The binding pattern of ferric iron and iron-binding protein in Botrytis cinerea

Iron-binding protein (Ibp) has protective effect on pathogen exposed to H2O2 in defense response of plants. Ibp in Botrytis cinerea (BcIbp) is related to its virulence. Bcibp mutation lead to virulence deficiencies in B. cinerea. BcIbp is involved in the Fe3+ homeostasis regulation. Recognition the binding site and binding pattern of ferric iron and iron-binding protein in B. cinerea are vital to understand its function. In this study, molecular dynamics (MD) simulations, gaussian accelerated molecular dynamics (GaMD) simulations, dynamic cross correlation analysis and quantum chemical energy calculation were used to explore binding pattern of ferric iron. MD results showed that the C-terminal region had little effect on the stability of residues in the Fe3+-binding pocket. Energy calculations suggested the most likely coordination pattern for ferric iron in iron-binding protein. These results will help to understand the binding of ferric iron to iron-binding protein and provide new ideas for regulating the virulence of B. cinerea.

B-cell immune deficiency in twin sisters expands the phenotype of MOPDI.

Microcephalic osteodysplastic primordial dwarfism type I (MOPDI) is a very rare and severe autosomal recessive disorder characterized by marked intrauterine growth retardation, skeletal dysplasia, microcephaly and brain malformations. MOPDI is caused by biallelic mutations in RNU4ATAC, a non-coding gene involved in U12-type splicing of 1% of the introns in the genome, which are recognized by their specific splicing consensus sequences. Here, we describe a unique observation of immunodeficiency in twin sisters with mild MOPDI, who harbor a novel n.108_126del mutation, encompassing part of the U4atac snRNA 3' stem-loop and Sm protein binding site, and the previously reported n.111G>A mutation. Interestingly, both twin sisters show mild B-cell anomalies, including low naive B-cell counts and increased memory B-cell and plasmablasts counts, suggesting partial and transitory blockage of B-cell maturation and/or excessive activation of naive B-cells. Hence, the localization of a mutation in stem II of U4atac snRNA, as observed in another RNU4ATAC-opathy with immunodeficiency, that is, Roifman syndrome (RFMN), is not required for the occurrence of an immune deficiency. Finally, we emphasize the importance of considering immunodeficiency in MOPDI management to reduce the risk of serious infectious episodes.

SOFB is a comprehensive ensemble deep learning approach for elucidating and characterizing protein-nucleic-acid-binding residues

Proteins and nucleic-acids are essential components of living organisms that interact in critical cellular processes. Accurate prediction of nucleic acid-binding residues in proteins can contribute to a better understanding of protein function. However, the discrepancy between protein sequence information and obtained structural and functional data renders most current computational models ineffective. Therefore, it is vital to design computational models based on protein sequence information to identify nucleic acid binding sites in proteins. Here, we implement an ensemble deep learning model-based nucleic-acid-binding residues on proteins identification method, called SOFB, which characterizes protein sequences by learning the semantics of biological dynamics contexts, and then develop an ensemble deep learning-based sequence network to learn feature representation and classification by explicitly modeling dynamic semantic information. Among them, the language learning model, which is constructed from natural language to biological language, captures the underlying relationships of protein sequences, and the ensemble deep learning-based sequence network consisting of different convolutional layers together with Bi-LSTM refines various features for optimal performance. Meanwhile, to address the imbalanced issue, we adopt ensemble learning to train multiple models and then incorporate them. Our experimental results on several DNA/RNA nucleic-acid-binding residue datasets demonstrate that our proposed model outperforms other state-of-the-art methods. In addition, we conduct an interpretability analysis of the identified nucleic acid binding residue sequences based on the attention weights of the language learning model, revealing novel insights into the dynamic semantic information that supports the identified nucleic acid binding residues. SOFB is available at https://github.com/Encryptional/SOFB and https://figshare.com/articles/online_resource/SOFB_figshare_rar/25499452.

Asymmetric allostery in estrogen receptor-α homodimers drives responses to the ensemble of estrogens in the hormonal milieu

The estrogen receptor-α (ER) is thought to function only as a homodimer but responds to a variety of environmental, metazoan, and therapeutic estrogens at subsaturating doses, supporting binding mixtures of ligands as well as dimers that are only partially occupied. Here, we present a series of flexible ER ligands that bind to receptor dimers with individual ligand poses favoring distinct receptor conformations-receptor conformational heterodimers-mimicking the binding of two different ligands. Molecular dynamics simulations showed that the pairs of different ligand poses changed the correlated motion across the dimer interface to generate asymmetric communication between the dimer interface, the ligands, and the surface binding sites for epigenetic regulatory proteins. By examining the binding of the same ligand in crystal structures of ER in the agonist vs. antagonist conformers, we also showed that these allosteric signals are bidirectional. The receptor conformer can drive different ligand binding modes to support agonist vs. antagonist activity profiles, a revision of ligand binding theory that has focused on unidirectional signaling from the ligand to the coregulator binding site. We also observed differences in the allosteric signals between ligand and coregulator binding sites in the monomeric vs. dimeric receptor, and when bound by two different ligands, states that are physiologically relevant. Thus, ER conformational heterodimers integrate two different ligand-regulated activity profiles, representing different modes for ligand-dependent regulation of ER activity.

A New Perspective on the Biomineralization of Radicular Dentin

The biomineralization of radicular dentin involves complex molecular signaling. The exact mechanism of action remains elusive. However, the literature showed that protein binding sites for calcium ions and mineral precipitation are essential to promote the remineralization process. Dentin organic matrix possesses non-collagenous proteins, such as dentin matrix protein 1 (DMP1), that can initiate and regulate crystal nucleation. Recombinant DMP1 molecules have been thought to perform specific molecular recognition with the apatite surface, guiding calcium phosphate clusters during recruitment through the type I collagen matrix, which serves as a template for controlled biomineralization. The biological basis for the clinical benefits of this process has yet to be completely elucidated. From a clinical perspective, caries, acid erosion, or disinfection protocol treatments can cause dentin demineralization. Given this fact, dentin biomimetic remineralization strategies and treatment strategies aimed at preserving the dentin matrix have been proposed.

Long-lasting, biochemically modified mRNA, and its frameshifted recombinant spike proteins in human tissues and circulation after COVID-19 vaccination.

According to the CDC, both Pfizer and Moderna COVID-19 vaccines contain nucleoside-modified messenger RNA (mRNA) encoding the viral spike glycoprotein of severe acute respiratory syndrome caused by corona virus (SARS-CoV-2), administered via intramuscular injections. Despite their worldwide use, very little is known about how nucleoside modifications in mRNA sequences affect their breakdown, transcription and protein synthesis. It was hoped that resident and circulating immune cells attracted to the injection site make copies of the spike protein while the injected mRNA degrades within a few days. It was also originally estimated that recombinant spike proteins generated by mRNA vaccines would persist in the body for a few weeks. In reality, clinical studies now report that modified SARS-CoV-2 mRNA routinely persist up to a month from injection and can be detected in cardiac and skeletal muscle at sites of inflammation and fibrosis, while the recombinant spike protein may persist a little over half a year in blood. Vaccination with 1-methylΨ (pseudouridine enriched) mRNA can elicit cellular immunity to peptide antigens produced by +1 ribosomal frameshifting in major histocompatibility complex-diverse people. The translation of 1-methylΨ mRNA using liquid chromatography tandem mass spectrometry identified nine peptides derived from the mRNA +1 frame. These products impact on off-target host T cell immunity that include increased production of new B cell antigens with far reaching clinical consequences. As an example, a highly significant increase in heart muscle 18-flourodeoxyglucose uptake was detected in vaccinated patients up to half a year (180 days). This review article focuses on medical biochemistry, proteomics and deutenomics principles that explain the persisting spike phenomenon in circulation with organ-related functional damage even in asymptomatic individuals. Proline and hydroxyproline residues emerge as prominent deuterium (heavy hydrogen) binding sites in structural proteins with robust isotopic stability that resists not only enzymatic breakdown, but virtually all (non)-enzymatic cleavage mechanisms known in chemistry.

Genomic analysis of Salmonella bacteriophages revealed multiple endolysin ORFs and importance of ligand binding site of receptor binding protein.

Salmonella is a prevalent foodborne pathogen causing millions of global cases annually. Antimicrobial resistance is a growing public health concern, leading to search for alternatives like bacteriophages. 97 bacteriophages, isolated from cattle farms (n= 48), poultry farms (n=37), and wastewater (n=5) samples in Türkiye, were subjected to host range analysis using 36 Salmonella isolates with 18 different serotypes. The broadest host range belonged to an Infantis phage (MET P1-091), lysing 28 hosts. Ten phages with the widest host range underwent further analysis, revealing 7 unique genomes (32 to 243kb), including a jumbophage (>200kb). Except for one with lysogenic properties, none of them harbored virulence or antibiotic resistance genes, making them potential Salmonella reducers in different environments. Examining ORFs of endolysin enzymes revealed surprising findings: 5 of 7 unique genomes contained multiple endolysin ORFs. Despite sharing same endolysin sequences, phages exhibited significant differences in host range. Detailed analysis unveiled diverse receptor binding protein sequences, with similar structures but distinct ligand binding sites. These findings emphasize the importance of ligand binding sites of receptor binding proteins. Additionally, bacterial reduction curve and virulence index revealed that Enteritidis phages inhibit bacterial growth even at low concentrations, unlike Infantis and Kentucky phages.

Role of the CTCF Binding Site in Human T-Cell Leukemia Virus-1 Pathogenesis.

During HTLV-1 infection, the virus integrates into the host cell genome as a provirus with a single CCCTC binding protein (CTCF) binding site (vCTCF-BS), which acts as an insulator between transcriptionally active and inactive regions. Previous studies have shown that the vCTCF-BS is important for maintenance of chromatin structure, regulation of viral expression, and DNA and histone methylation. Here, we show that the vCTCF-BS also regulates viral infection and pathogenesis in vivo in a humanized (Hu) mouse model of adult T-cell leukemia/lymphoma. Three cell lines were used to initiate infection of the Hu-mice, i) HTLV-1-WT which carries an intact HTLV-1 provirus genome, ii) HTLV-1-CTCF, which contains a provirus with a mutated vCTCF-BS which abolishes CTCF binding, and a stop codon immediate upstream of the mutated vCTCF-BS which deletes the last 23 amino acids of p12, and iii) HTLV-1-p12stop that contains the intact vCTCF-BS, but retains the same stop codon in p12 as in the HTLV-1-CTCF cell line. Hu-mice were infected with mitomycin treated or irradiated HTLV-1 producing cell lines. There was a delay in pathogenicity when Hu-mice were infected with the CTCF virus compared to mice infected with either p12 stop or WT virus. Proviral load (PVL), spleen weights, and CD4 T cell counts were significantly lower in HTLV-1-CTCF infected mice compared to HTLV-1-p12stop infected mice. Furthermore, we found a direct correlation between the PVL in peripheral blood and death of HTLV-1-CTCF infected mice. In cell lines, we found that the vCTCF-BS regulates Tax expression in a time-dependent manner. The scRNAseq analysis of splenocytes from infected mice suggests that the vCTCF-BS plays an important role in activation and expansion of T lymphocytes in vivo. Overall, these findings indicate that the vCTCF-BS regulates Tax expression, proviral load, and HTLV pathogenicity in vivo.

Chromones and biflavonoids from Garcinia pedunculata and Garcinia nujiangensis and their anti-inflammatory activity

Plants of the Garcinia genus were rich in structurally diverse and naturally bioactive components, while limited studies have been reported for Garcinia pedunculata Roxb. and G. nujiangensis C. Y. Wu & Y. H. Li. Four previously undescribed compounds including three chromones, garpedunchromones A-C (1–3), and one biflavonoid, nujiangbiflavone A (14), along with fifteen known analogs (4–13, 15–19) were isolated from G. pedunculata and G. nujiangensis. The structures of the isolated compounds were determined based on their HRESIMS data, extensive NMR spectroscopic analyses, and ECD calculations. The chromone derivatives were isolated from Garcinia for the first time. Compound 14 was a rare biflavonoid with C-3─C-6″ linkage. The biological evaluation of these isolates against NO production was conducted in the LPS-induced RAW 264.7 cells, resulting in the identification of a series of potent NO inhibitors, of which garpedunchromone B (2) was the most active with an IC50 value of 18.11 ± 0.96 μM. In the network pharmacology studies, the potential targets of compounds and inflammation were obtained from PharmMapper and GeneCards database. GO and KEGG enrichment analysis revealed that the overlapped targets were closely related to the major pathogenic processes linked to inflammation. Garpedunchromone B and proteins binding sites were being predicted.

The FXR1 network acts as signaling scaffold for actomyosin remodeling.

It is currently not known whether mRNAs fulfill structural roles in the cytoplasm. Here, we report the FXR1 network, an mRNA-protein (mRNP) network present throughout the cytoplasm, formed by FXR1-mediated packaging of exceptionally long mRNAs. These mRNAs serve as underlying condensate scaffold and concentrate FXR1 molecules. The FXR1 network contains multiple protein binding sites and functions as a signaling scaffold for interacting proteins. We show that it is necessary for RhoA signaling-induced actomyosin reorganization to provide spatial proximity between kinases and their substrates. Point mutations in FXR1, found in its homolog FMR1, where they cause Fragile X syndrome, disrupt the network. FXR1 network disruption prevents actomyosin remodeling-an essential and ubiquitous process for the regulation of cell shape, migration, and synaptic function. These findings uncover a structural role for cytoplasmic mRNA and show how the FXR1 RNA-binding protein as part of the FXR1 network acts as organizer of signaling reactions.

Hybrid Caffeic Acid-Based DHFR Inhibitors as Novel Antimicrobial and Anticancer Agents.

A novel series of 1,2,4-triazole analogues of caffeic acid was designed, synthesized, characterized, and assessed for their capacity to inhibit DHFR, as well as their anticancer and antimicrobial properties. A molecular docking analysis was conducted on DHFR, utilizing PDB IDs 1U72 and 2W9S, aiming to design anticancer and antimicrobial drugs, respectively. Among all the synthesized derivatives, compound CTh7 demonstrated the highest potency as a DHFR inhibitor, with an IC50 value of 0.15 μM. Additionally, it exhibited significant cytotoxic properties, with an IC50 value of 8.53 µM. The molecular docking analysis of the CTh7 compound revealed that it forms strong interactions with key residues of homo sapiens DHFR such as Glu30, Phe34, Tyr121, Ile16, Val115, and Phe31 within the target protein binding site and displayed excellent docking scores and binding energy (-9.9; -70.38 kcal/mol). Additionally, synthesized compounds were screened for antimicrobial properties, revealing significant antimicrobial potential against bacterial strains and moderate effects against fungal strains. Specifically, compound CTh3 exhibited notable antibacterial efficacy against Staphylococcus aureus (MIC = 5 µM). Similarly, compound CTh4 demonstrated significant antibacterial activity against both Escherichia coli and Pseudomonas aeruginosa, with MIC values of 5 µM for each. A docking analysis of the most active antimicrobial compound CTh3 revealed that it forms hydrogen bonds with Thr121 and Asn18, a π-cation bond with Phe92, and a salt bridge with the polar residue Asp27.

Genome-Wide Identification, Expression Analysis and Functional Study of DELLA Genes in Chinese Cabbage (Brassica rapa L. ssp. pekinensis).

DELLA protein is a crucial factor which played pivotal roles in regulating numerous intriguing biological processes in plant development and abiotic stress responses. However, little is known about the function and information of DELLA protein in Chinese cabbage. Using 5 DELLA gene sequences in Arabidopsis Thaliana as probes, 5 DELLA genes in Chinese cabbage were identified by Blast search in Chinese cabbage database (Brassica database (BRAD)). The National Center for Biotechnology Information (NCBI), ExPaSy, SWISS-MODEL, DNAMAN, MEGA 11, PlantCARE were used to identify and analyze the DELLA gene family of Chinese cabbage. Gene expression was analyzed by quantitative real-time polymerase chain reaction (qRT-PCR). The function of BraA10gRGL3 was verified by overexpression and phenotypic analysis of BraA10gRGL3 and yeast hybrid. In this study, 5 BraDELLAs homologous to Arabidopsis thaliana were identified and cloned based on the Brassica database, namely, BraA02gRGL1, BraA05gRGL2, BraA10gRGL3, BraA06gRGA and BraA09gRGA. All BraDELLAs contain the DELLA, TVHYNP, and GRAS conserved domains. Cis-element analysis revealed that the promoter regions of these 5 DELLA genes all contain light-responsive elements, TCT motif, I-box, G-box, and box 4, which are associated with GA signaling. Transcriptome analysis results proved that the expression of BraA02gRGL1, BraA05gRGL2, and BraA10gRGL3 in Y2 at different growth stages were lower than them in Y7, which is consistent with the phenotype that Y7 exhibited stronger stress tolerance than Y2. It is worth emphasizing that even through the overexpression of BraA10gRGL3-Y7 in Arabidopsis resulted in smaller leaf size and lower fresh weight compared to the wild type (WT) Arabidopsis: Columbia, a stronger response to abiotic stresses was observed in BraA10gRGL3-Y7. It indicated that BraA10gRGL3-Y7 can improve the stress resistance of plants by inhibiting their growth. Moreover, the yeast two-hybrid experiment confirmed that BraA10gRGL3-Y7 can interacted with BraA05gGID1a-Y7, BraA04gGID1b1, BraA09gGID1b3-Y2, and BraA06gGID1c, whereas BraA10gRGL3-Y2 cannot interact with any BraGID1. Collectively, BraDELLAs play important role in plant development and response to abiotic stress. The differences in amino acid sequences between BraA10gRGL3-Y2 and BraA10gRGL3-Y7 may result in variations in their protein binding sites, thus affecting their interaction with the BraGID1 family proteins. This systematic analysis lays the foundation for further study of the functional characteristics of DELLA genes of Chinese cabbage.

Thermodynamics-Guided Design Reveals a Cooperative Hydrogen Bond in DC-SIGN-targeted Glycomimetics.

Due to the shallow and hydrophilic binding sites of carbohydrate-binding proteins, the design of glycomimetics is often complicated by high desolvation costs as well as competition with solvent. Therefore, a careful optimization of interaction vectors and ligand properties is required in the design and optimization of glycomimetics. Here, we employ thermodynamics-guided design to optimize mannose-based glycomimetics targeting the human C-type lectin receptor dendritic cell-specific intercellular adhesion molecule 3 grabbing nonintegrin (DC-SIGN), a pathogenic host factor in viral infections. By exploring ligand rigidification and hydrogen bond engineering, a monovalent glycomimetic with an unprecedented affinity for DC-SIGN in the low μM range was discovered. A matched molecular pair analysis based on microcalorimetric data revealed a stereospecific hydrogen bond interaction with Glu358/Ser360 as the origin of this cooperative and enthalpically dominated interaction. This detailed insight into the binding mechanism paves the way for an improvement of monovalent glycomimetics targeting DC-SIGN.

Known and potential benefits of applying herbicides with glutathione S-transferase inhibitors and inducers – a review

Abstract Weed resistance to herbicides has increased exponentially during the past 30 to 40 years, consequently reducing the number of effective products available to control certain species and populations. Future efforts should target not only the discovery of new protein binding sites and the development of new molecules, but also the revival of old molecules with reduced efficacy due to widespread herbicide resistance. The addition of herbicide synergists that inhibit metabolic pathways or enhance intrinsic plant stress is a possible solution to ameliorate the negative effects caused by the lack of new herbicide chemistries. Glutathione S-transferase (GST) enzymes are involved with numerous herbicide detoxification reactions and plant stress responses. This review approaches the potential use of natural and synthetic GST-inhibitors to enhance herbicidal activity or induce crop safety to provide effective, sustainable weed management strategies in the future.

Assessing the functional impact of protein binding site definition.

Many biomedical applications, such as classification of binding specificities or bioengineering, depend on the accurate definition of protein binding interfaces. Depending on the choice of method used, substantially different sets of residues can be classified as belonging to the interface of a protein. A typical approach used to verify these definitions is to mutate residues and measure the impact of these changes on binding. Besides the lack of exhaustive data, this approach also suffers from the fundamental problem that a mutation introduces an unknown amount of alteration into an interface, which potentially alters the binding characteristics of the interface. In this study we explore the impact of alternative binding site definitions on the ability of a protein to recognize its cognate ligand using a pharmacophore approach, which does not affect the interface. The study also shows that methods for protein binding interface predictions should perform above approximately F-score = 0.7 accuracy level to capture the biological function of a protein.

Insect Chemosensory Proteins against COVID-19

This article describes a novel strategy to fight SARS-CoV-2 infection by employing tiny soluble binding proteins called “Odorant Binding Proteins” (OBPs), “Niemann-Pick Type C2 (NPC2s)”, and “Chemosensory Proteins” (CSPs). The possible interactions between these proteins and sensory receptors are not relevant to COVID-19. We concentrate on the interaction between the protein-binding site and C18 lipids in COVID. Extended lipid chains, like palmitic acid (C18), oleic acid (C18:1), and linoleic acid (C18:2) resemble the primary components of membrane viral particles. The virus’s surface is covered in C18 lipids. In light of this, OBPs’, NPC2s’ and CSPs’ capacity to interact with C18-lipids and transfer them to Degradative Enzymes (ODEs) may provide a novel molecular strategy for combating coronavirus infection, regardless of the course of viral mutation. In order to confine COVID virus variations in a hydrophobic pocket and/or produce viral particles devoid of an outer protective envelope, proteins with the ability to bind long lipid chains on viral surfaces or peplos may show great promise.

Structural transitions enable interleukin-18 maturation and signaling

Several interleukin-1 (IL-1) family members, including IL-1β and IL-18, require processing by inflammasome-associated caspases to unleash their activities. Here, we unveil, by cryoelectron microscopy (cryo-EM), two major conformations of the complex between caspase-1 and pro-IL-18. One conformation is similar to the complex of caspase-4 and pro-IL-18, with interactions at both the active site and an exosite (closed conformation), and the other only contains interactions at the active site (open conformation). Thus, pro-IL-18 recruitment and processing by caspase-1 is less dependent on the exosite than the active site, unlike caspase-4. Structure determination by nuclear magnetic resonance uncovers a compact fold of apo pro-IL-18, which is similar to caspase-1-bound pro-IL-18 but distinct from cleaved IL-18. Binding sites for IL-18 receptor and IL-18 binding protein are only formed upon conformational changes after pro-IL-18 cleavage. These studies show how pro-IL-18 is selected as a caspase-1 substrate, and why cleavage is necessary for its inflammatory activity.