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Structural comparison of human and Plasmodium proteasome β5 subunits: informing selective inhibitor design for anti-malaria agents

Malaria Journal volume 24, Article number: 21 (2025) Cite this article

Abstract

Background

The Plasmodium proteasome emerges as a promising target for anti-malarial drug development due to its potential activity against multiple life cycle stages.

Methods

In this investigation, a comparative analysis was conducted on the structural features of the β5 subunit in the 20S proteasomes of both Plasmodium and humans.

Results

The findings underscore the structural diversity inherent in both proteasomes. The human proteasome β5 subunit reveals a composition rich in β-sheets and adopts a more compact conformation. This structural arrangement limits the ligand binding pocket's capacity to accommodate only small compounds effectively. In contrast, the Plasmodium β5 subunit exhibits a higher prevalence of loop structures, creating a more open and flexible binding pocket. This unique structural characteristic enables the binding of a larger and more diverse array of compounds.

Conclusion

The discernible structural contrast between the human and Plasmodium proteasome β5 subunits holds promise for the identification of Plasmodium-selective compounds. The ability of the Plasmodium proteasome to accommodate a broader range of compounds due to its distinctive structural features opens avenues for drug screening to intending to develop selective anti-malarial agents. This study contributes valuable insights into the structural basis for targeting the Plasmodium proteasome and paves the way for the rational design of compounds with enhanced specificity and efficacy against malaria.

Background

Malaria persists as a significant health challenge, endangering hundreds of millions of individuals and resulting in approximately 600,000 fatalities annually. Unfortunately, there has been no progress in decreasing the incidence of malaria cases over the past five years [1, 2]. The effectiveness of current anti-malarial control heavily relies on artemisinin-based combination therapy (ACT). The emergence of partial resistance to artemisinin raises serious concerns about the sustainability of this approach [3,4,5,6,7]. Diminished sensitivity to ACT prolongs the clearance of parasites from patients, causing clinical failures. In regions with entrenched resistance, the treatment failure rate reaches 50%, a stark contrast to the 2% failure rate in areas where resistance is rare [8,9,10]. There is an urgent need for replacement anti-malarials.

The proteasome, a multisubunit enzyme complex, plays a crucial role in maintaining proteostasis and regulating essential processes like the cell cycle [11,12,13]. Featuring a 20S catalytic core, the proteasome comprises two heptameric rings of β subunits. Each subunit serves a distinct enzymatic function: β1 exhibits caspase-like activity, cleaving after acidic residues; β2 displays trypsin-like activity, cleaving after basic residues; and β5 demonstrates chymotrypsin-like activity, cleaving after nonpolar residues [14,15,16]. Under conditions of oxidative stress or exposure to inflammatory cytokines, the constitutive proteasome undergoes a modification wherein three active subunits are substituted with “immune” subunits, giving rise to immunoproteasomes [14, 17].

Proteasome inhibitors hold promise for malaria treatment, displaying parasiticidal activity against asexual blood stages, particularly the young (ring stage) intraerythrocytic parasites. Additionally, they target sexual stage gametocytes and liver stage parasites, which are resistant to many other chemotherapeutic agents [18,19,20,21]. Furthermore, proteasome inhibitors exhibit activity against both artemisinin-sensitive and -resistant parasites. Notably, they strongly synergize with artemisinin, enhancing its killing effects on Plasmodium falciparum in culture and Plasmodium berghei in vivo [20, 22,23,24,25]. Research on potential anti-malarial compounds has primarily focused on proteasome inhibitors featuring epoxyketone and vinyl sulfone warheads that bind irreversibly to the active site. However, recent investigations into noncovalent asparagine ethylenediamine (AsnEDA) inhibitors have shown promising cellular selectivity. Despite their efficacy, this class of inhibitors faces limitations due to instability in vivo, with a half-life of approximately 30 min, rendering them inactive when used alone in a mouse model of malaria [26, 27]. The identification of a potent, specific, and "drug-like" proteasome inhibitor holds great promise as a standalone anti-malarial compound. Moreover, it could prove highly effective when used in combination with artemisinin. However, the major challenge for the development of proteasome inhibitors as anti-malarial agents is achieving selectivity for the parasite enzyme over its human counterpart.

Methods

Human and malarial proteasome structure retrieval

The 3D structures of human and malarial proteasomes were assessed from RCSB PDB by PDBID 7LXV and 7LXT, respectively [28]. The energy minimization and loop refinement of both protein models were carried out by using the UCSF chimera and BOVIA discovery studio. Therefore, the target protein model’s energy minimization was carried out using UCSF Chimera and Discovery Studio [29, 30]. Moreover, the Ramachandran graph of both models was analysed by Discovery Studio. The architecture and statistical percentage values of helices, beta-sheets, coils, and turns of both models were accessed by using the online webserver VADAR (http://vadar.wishartlab.com/) [31].

Binding pocket analysis

The binding pocket of proteins is most likely the active region where chemical compounds bind and perform their competitive and noncompetitive activity. The binding pocket residues were assessed from already available data by Xie et al. [28]. Moreover, the selected residues and the position of the binding pocket of both proteasomes were analysed by visualizing in UCSF Chimera and Discovery Studio.

Molecular dynamics simulation of proteasome

For the structural comparison, both of the proteasome peptides were subjected to 500 ns Molecular Dynamic (MD) simulation for stability comparison and activity difference validation. Therefore, an online server CHARMM-GUI was utilized for GROMACS software input generation.

The CHARMM36 force field was created using the solution builder protocol provided by the CHARMM-GUI server (www.charmm-gui.org/?doc=input/solution). Input files for the MD simulations in GROMACS were generated using the default parameters [32, 33]. To create the MD input file, a five-step process was followed. First, the predicted 3D structure of proteasomes in complex with the docked compound was uploaded. Second, the system was solvated using the TIP3P solution in a periodic box extending 10 Å beyond each atom. Monte-Carlo ion placement with KCL ions was used for neutralization. In the third step, box dimensions were set to 94 Å along each axis, resulting in a system size of approximately 830,584 cubic Angstroms. The Verlet cutoff technique with a 10 Å cutoff was applied for electrostatic and Van der Waals interactions, and the LINCS algorithm constrained bond lengths. The fourth step involved NVT and NPT equilibration phases at 30 °C. In the fifth step, GROMACS topology and parameter files were generated using a Python script from CHARMM-GUI, and GROMACS 2021.2 was used for MD simulations on a Linux operating system to explore receptor’s structural behaviour.

Principal component analysis

Principal Component Analysis (PCA) is a multivariate method that decomposes protein dynamics, and extracts the dominant modes to reduce the number of motions required to describe the protein dynamics [34]. In the Cartesian coordinate space, elements of the covariance matrix (C) are defined as:

$$\text{Cij }= < (\text{xi}- <\text{ xi }>) (\text{xj}- <\text{ xj }>) >$$
(1)

where the brackets show an average of all structures sampled across the MD trajectory. The covariance matrix eigenvalues are decomposed to eigenvectors each with a corresponding variance or eigenvalue that describes a part of the protein dynamics with the large eigenvectors describing the dominant motions of the protein. The principal components (PCs) are then obtained through the diagonalization of the covariance matrix. The PCs were calculated using Gromacs commands ‘gmx covar’ and ‘gmx anaeig’, and PC1 and PC2 were used to describe the protein motions af all atom MD simulation over the 500 ns trajectory and plots generated using a Python script.

Preliminary molecular docking

Initially, investigational proteasome inhibitors from MedChemExpress (MCE, https://www.medchemexpress.com)were selected for the preliminary molecular docking analysis. Furthermore, 12 investigational compounds also subjected to preliminary molecular docking against both malarial and human proteasomes to assess the response of investigational drug candidates and MCE known proteasome inhibitors. Prior to the docking analysis, ligand molecules were prepared and subjected to energy minimization. Similarly, energy minimization and receptor preparation were conducted. The molecular docking was performed using the Discovery studio's CDocker approach, with a binding site sphere size extended to 9.5045 Å. Parameters such as Top hits, Random conformations, and orientation to refines were set at 10 for each.

Results and discussion

Structural analysis of the human and Plasmodium β5 subunits

The human and Plasmodium 20S proteasomes are composed of four stacked rings. Two outer rings, each consisting of seven α-subunits (alpha subunits), form the regulatory particle. Two inner rings, each composed of seven β subunits (beta subunits), form the catalytic core. The α and β rings alternate, resulting in the overall structure [35]. Some of the previous reports suggest that proteasome β5 subunit was mostly involved in malarial diseases [36, 37].

Therefore, the electron microscopic structures of 20S human and Plasmodium proteasomes were retrieved from online webserver RCSB PDB with (PDBID 7LXV and 7LXT, respectively) 3.40 Å resolution [28]. Furthermore, the Ramachandran plots indicate that a substantial 98.5% of amino acids are situated within the favoured region for human proteasome β5 subunit, while 83.3% of residues falling into the favoured zone for Plasmodium β5 subunit, in terms of dihedral angles phi (φ) and psi (ψ) (Fig. 1).

Fig. 1
figure 1

A, B The 3D structure of the Human proteasome β5 subunit (A) and Plasmodium β subunit are visualized using UCSF Chimera, and the Ramachandran plots for both peptides are generated by Discovery Studio

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VADAR analysis revealed that the overall structure of human and Plasmodium β5 subunit comprises of α-Helix, β-Sheets and coils. Moreover, ProtParam, physiochemical properties analysis manifested notable distinctions in their characteristics. Firstly, the theoretical isoelectric point (pI) indicates a slightly acidic nature for the human protein (pI = 6.91) compared to the more acidic nature of the malarial protein (pI = 5.40). This suggests differences in the overall charge distribution of the proteins. Considering additional information on extinction coefficients, half-life, and instability index, provides a comprehensive perspective. Notably, the malarial protein exhibits lower extinction coefficients at 280 nm (21,360 and 20,860) compared to the human protein (31,985 and 31,860), which implies variations in their absorption characteristics. Additionally, the estimated half-life of the malarial protein, ranging from 10 to 30 h across different organisms, suggests potential susceptibility to degradation, as indicated by its higher instability index (51.82) in comparison to the human protein (43.78).

Lastly, the grand average of hydropathicity (GRAVY) values indicate higher hydrophilicity for the malarial protein (−0.298) in contrast to the human protein (−0.186), suggesting potential variations in solubility and interactions with aqueous environments (Table 1). These findings collectively suggest that the malarial protein may have structural and biochemical features that make it more prone to degradation or rapid turnover compared to the relatively more stable human protein. Furthermore, the sequence similarity of both proteins was depicted as 51.76% while the structural RMSD was 0.683 Å (Fig. 2).

Table 1 The statistical and physiochemical properties of both proteasome β5 subunit
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Fig. 2
figure 2

The sequence comparison of both proteasome β5 subunits (A), The structural comparison of both β5 subunits (B). The sequence comparison demonstrates the sequence similarity of 51.76% while the structural comparison revealed a structural RMSD of 0.683 Å

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The binding pocket analysis

The role of a binding pocket in a protein is shaped not only by its structural attributes and position but also by the particular set of surrounding amino acid residues [38]. The Binding pocket residues were retrieved from already published data [28, 39] and visualized by UCSF Chimera and Discovery Studio. Interestingly, The Mutated amino acid residues in human (Thr21, Ala22, and Tyr169) and Plasmodium (Ser21, Met22, and Gly169) proteasome β5 subunits were taking part and exhibiting the interactions in both proteasomes. Accompanying that, 17 amino acid residues were selected in both receptors (Fig. 3).

Fig. 3
figure 3

Binding pocket residues of human β5 subunits exhibited by UCSF Chimera and demonstrated in violet red (Human) and Salmon (Plasmodium). The binding pocket residues are mentioned on their position in the active region of the receptor

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Molecular dynamics simulation

Both Proteasome’s β5 subunits were further subjected to 500 ns MD simulations to analyse the residual flexibility and stability difference of both models.

Root mean square deviation

By calculating the Root Mean Square Deviation (RMSD) using MD trajectories, it was possible to identify the fluctuations of the backbone residues of the proteasome β5 subunit of Plasmodium protein in comparison with human β5 subunit. The human β5 subunit manifests quite stable behaviour throughout 500 ns MD simulation. In the starting frames the bar exhibits the increasing pattern starting from σ = 0.05 to σ = 0.2 and then it keeps fluctuating between σ = 0.20 to σ = 0.22 till 500 ns endpoint (Fig. 4). However, the Plasmodium β5 subunit depicted a highly fluctuating bar line. The graph initially showed σ = 0.35, remaining stable up to 160 ns. After this point, the RMS deviation began to increase, eventually reaching σ = 0.7. Therefore the Plasmodium β5 subunit graph remained fluctuating from 200 to 500 ns between σ = 0.60 to σ = 0.85.

Fig. 4
figure 4

The calculated RMSD of Both proteasome β5 subunits in 500 ns molecular dynamic simulation

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The stability of the human β5 subunit throughout the 500 ns simulation suggests a robust and well-maintained structure, potentially indicating a more conserved and tightly regulated function in comparison to the Plasmodium. On the other hand, the heightened fluctuations in the Plasmodium β5 subunit may stem from structural instabilities or conformational changes, possibly related to its specific role in the life cycle of the parasite. The initial stability observed followed by a sudden increase in RMS deviation values in the Plasmodium β5 subunit might indicate a structural transition or functional alteration, possibly reflecting the protein's adaptability to dynamic environmental conditions.

Root mean square fluctuations

Root Mean Square Fluctuations (RMSF) serve as a key metric for understanding the dynamic behaviour and flexibility of proteins over time. A comparative analysis of RMSF derived from 500 ns molecular dynamics simulations of the human and Plasmodium proteins was carried out (Fig. 5).

Fig. 5
figure 5

The graphical representation of RMSF of Both proteasome β5 subunits in 500 ns molecular dynamic simulation

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In this extensive comparative analysis, the intricacies of RMSF observed in 500 ns molecular dynamics simulations of both human and Plasmodium proteins were explored. The human protein reveals a narrative of nuanced dynamism, featuring moderated fluctuations across the majority of residues. Notably, peaks in flexibility emerge around residues 20–30 and 60–70, suggesting localized conformational changes. In contrast, the Plasmodium protein displays an elevated overall RMSF profile, particularly pronounced in the expansive N-terminal region spanning residues 20–30 and C-terminal 170–205. Thus, indicating a more extensive and pronounced flexibility pattern. While both proteins share flexible regions, variations in dynamic behaviours underscore distinctive structural dynamics. The inclusion of a carefully crafted comparative RMSF plot visually encapsulates these nuanced distinctions, serving as a tangible reference for further in-depth analyses. This exploration establishes a robust foundation for future investigations, inviting the scientific community to unravel the functional ramifications within these specific flexible regions.

Radius of gyration

The radius of gyration (Rg) is a measure of a molecule's overall compactness, providing insights into its structural stability during molecular dynamics simulations. In the context of the present study, the Rg values were analysed for both human and Plasmodium β5 subunits. The Rg profile for the human β5 subunit exhibited a stable trend, with the initial bar starting at 1.60 nm and fluctuating between 1.60 nm and 1.65 nm throughout the 500 ns simulation (Fig. 6). In contrast, the Plasmodium β5 subunit displayed a more dynamic behaviour. Initially, its Rg values decreased from 1.70 nm to 1.65 nm until 50 ns, followed by stability until 150 ns. Subsequently, a notable increase to 1.95 nm at 230 ns, a subsequent decrease to 1.65 nm at 260 ns, and a peak at 280 ns were observed. From 330 to 450 ns, stability ensued, but after 450 ns, a pronounced increase in Rg values occurred, reaching 1.83 nm, followed by a gradual decrease to 1.70 nm and a return to 1.65 nm at 500 ns. This erratic behaviour in the Plasmodium protein's Rg suggests potential structural rearrangements or conformational changes, while the consistent Rg values in the human protein underscore its stable and compact nature throughout the simulation. The distinct dynamics may be indicative of the unique functional requirements and environmental adaptations of these proteins.

Fig. 6
figure 6

The calculated Rg graph of Both proteasome β5 subunits in 500 ns molecular dynamic simulation

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Solvent-accessible surface area

The solvent-accessible surface area (SASA) provides crucial information about the exposure of a protein to its surrounding environment. In this investigation, the SASA values for the human β5 subunit initiated at 105 nm and maintained stability throughout the entire 500 ns simulation. Conversely, the Plasmodium β5 subunit exhibited a dynamic SASA profile. Starting at 110 nm, it initially decreased to 107 nm, maintaining stability from 40 to 130 ns. Subsequently, a gradual increase in SASA values commenced, reaching 115 nm by the end of the 500 ns simulation (Fig. 7). This suggests that the Plasmodium protein undergoes significant conformational changes, possibly indicative of structural adaptability in response to environmental cues during its life cycle. In contrast, the consistent SASA values in the human protein point towards a more stable and less responsive conformation, reflecting its robust and predetermined structural characteristics.

Fig. 7
figure 7

The graphical representation of SASA values of Both proteasome β5 subunits in 500 ns molecular dynamic simulation. The SASA of binding pocket residues of both proteasomes is depicted in the inset graph

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Furthermore, the SASA values of binding pocket residues were also calculated from MD trajectories, and interestingly, the solvent-accessible surface area (SASA) within the binding pocket of the human β5 subunit consistently showed lower values at 5.99 nm, in contrast to the Plasmodium β5 subunit, where the corresponding values were higher at 6.99 nm (Fig. 7 inset graph). This discrepancy in binding pocket SASA suggests potential differences in the structural dynamics of the two proteins. The elevated SASA values in the Plasmodium protein may indicate increased flexibility and exposure of its binding pocket to the surrounding environment, contributing to higher fluctuations. In contrast, the more restrained SASA values in the human protein's binding pocket imply a relatively stable and compact conformation, potentially leading to reduced fluctuations.

Principal component analysis

Principal component analysis (PCA) was employed to elucidate the dynamic behaviours of both human and Plasmodium β5 subunits, capturing their motions through a reduced set of principal modes defined by eigenvalues and eigenvectors. The essential subspace, determined by projecting the protein main chain conformations from molecular dynamics (MD) trajectories onto the first and second eigenvectors, provides insights into the dominant collective motions within biomolecules. The resulting figures (Fig. 8) reveal that the Plasmodium β5 subunit exhibits a dispersed distribution in the phase space, suggesting a higher degree of conformational variability or flexibility, possibly related to structural adaptations for diverse functions or interactions within its cellular environment. In contrast, the human β5 subunit occupies a more centralized and compact region, with residues closely grouped, implying a stable and constrained conformational space essential for its specific biological roles. The observed differential distribution patterns in the PCA analysis may reflect distinct structural and functional demands, with the scattered nature of Plasmodium residues potentially contributing to adaptability and the clustered arrangement of human residues indicating a more rigid and defined conformational landscape.

Fig. 8
figure 8

Conformational sampling of human and Plasmodium β5 subunits by 2D projection of the MD trajectory on PC1 and PC2 (A). The Percentile Cumulative Sum of Eigenvalues of the whole trajectory is presented in the inset graph while the initial Percentile Cumulative Sum of Eigenvalues is presented in the main graph (B)

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Furthermore, the cumulative sum of eigenvalues for malarial beta subunits exhibited a rapid increase suggesting that a substantial proportion of the variance in the malarial beta subunit dataset is captured by a relatively small number of principal components. In contrast, the human β5 subunit showed a slower initial increase. The malarial beta subunits may have a more concentrated set of influential features, while the human β5 subunit requires a larger set of components to explain a comparable amount of variance.

Define secondary structure of proteins

DSSP (Define Secondary Structure of Proteins) is a widely used program in structural bioinformatics designed to analyse the secondary structure of proteins based on their three-dimensional (3D) structures. Developed by Wolfgang Kabsch and Chris Sander, DSSP assigns specific secondary structure classifications, such as helix (H), sheet (E), or coil (C), to each amino acid residue in a protein (Supplementary data Fig. 1). It achieves this by analysing hydrogen bonding patterns within the protein structure, identifying regions with helical or sheet-like structures. The DSSP analysis of the human β5 subunit and malarial protein indicated notable differences in their secondary structure elements. Specifically, the human β5 subunit exhibited a more compact arrangement of α-helices and β-sheets compared to the malarial protein (Fig. 9). This suggests a potentially more organized and stable secondary structure in the human protein. Additionally, the higher number of 5-helix and β-bridges observed in the human β5 subunit implies a greater prevalence of these specific structural features compared to the malarial protein. These findings from the DSSP analysis provide insights into the distinct structural characteristics between the two proteins.

Fig. 9
figure 9

The DSSP values of both human and Plasmodium β5 subunits are represented in this figure. All the variables like α-helix, β-sheets, and coils are coloured differently. While overall structure bar lines are coloured as blue which contains the cumulative values of α-helix, β-sheets and coils

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Snapshot comparison at each 100 ns

Throughout a 500 ns molecular dynamics (MD) simulation, snapshots of the 3D structures of human and Plasmodium β5 subunits were captured at 100 ns intervals to examine their structural variations. Consequently, six snapshots were obtained at 0 ns, 100 ns, 200 ns, 300 ns, 400 ns, and 500 ns for each peptide, and these were superimposed using UCSF Chimera. The analysis of structural variability in the human peptide revealed a compact formation with minimal changes. In contrast, the Plasmodium peptide exhibited more pronounced structural changes and a looser formation compared to the human peptide. The binding pocket region in the Plasmodium peptide also displayed increased flexibility (Fig. 10). The observed structural alterations in the Plasmodium peptide can be attributed to a higher number of loop regions, whereas the stability of the human peptide arises from an abundance of β-sheets, contributing to its rigidity and heightened stability.

Fig. 10
figure 10

The structural comparison of variation is provided in this figure. The six snapshots from 0 to 500 ns (at each 100 ns) are coloured in gray scale as white (0 ns), light grey (100 ns), gray (200 ns), dark gray (300 ns), dim gray (400 ns), and black (500 ns)

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Columbic surface comparison

A comparison of the Coulombic surfaces was conducted for both proteasomes. The human proteasome displayed a bridge-like conformation in its binding pocket, where the residues Ala20 and Ala49 shared the surface and formed a bridge. This structural arrangement resulted in a more confined and compact pocket for ligand binding. In contrast, the Plasmodium proteasome subunit provided a wider area for ligand binding (Fig. 11). Additionally, the binding pocket residues in both proteasomes did not exhibit significant electronegative or electropositive charges. The bridge-like conformation in the human proteasome might suggest a specific mode of ligand recognition or regulatory mechanism, emphasizing precision in binding. On the other hand, the broader binding area in the Plasmodium proteasome could be advantageous for accommodating a variety of ligands.

Fig. 11
figure 11

Comparison of the Coulombic surfaces are presented in this figure, Visualized by UCSF Chimera. The bound ligands to both receptors are coloured as spring green. While, the surface transparency for the bound ligands is increased to 80%

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Theoretical approaches to target preferentially malaria proteasome over human proteasome

Known protease inhibitors—MCE and investigational compounds

MCE known proteasome inhibitors were docked to both proteasome subunits and the results showed comparable outcomes (Fig. 12)(supplementary data Table 1). It suggests that these inhibitors may interact similarly with both proteasomes at the molecular level. The 2D representation of MCE known inhibitors was provided in supplementary data Fig. 2. Furthermore, 12 investigational compounds Bortezomib, Carfilzomib, Carmaphycin B, Carmaphycin B analogue, WLL-vs, MPI-5, TDI-8304, ONX-0914, Delanzomib, Ixazomib, Marizomib, Oprozomib were chosen from already published data [40] and were docked to the human and Plasmodium β5 subunit. Out of 12 docked compounds, Carfilzomib manifested the specific binding to malaria instead of Human proteasome (Supplementary data Table 2). The 2D structures of investigational compounds were provided in supplementary data Fig. 3.

Fig. 12
figure 12

The negative CDocker energy comparison of both human and Plasmodium proteasome. CDocker energy comparison of investigational compounds is depicted on the right while the CDocker energy comparison of reported proteasome inhibitors is provided on the left side

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Conclusion

In conclusion, the present study underscores the structural differences in the β5 subunit of the 20S proteasomes between Plasmodium and humans. The human proteasome exhibits a compact conformation, favouring small compound binding, while the Plasmodium proteasome, with its abundance of loop structures, allows for a broader range of compound interactions. This structural contrast suggests a promising avenue for developing Plasmodium-selective compounds, providing valuable insights for targeted anti-malarial drug design. Further exploration of these structural distinctions could lead to the development of more effective and specific anti-malarial therapies. These endeavors promise to enhance understanding of the intricate structural dynamics underlying the functional roles of both human and Plasmodium proteasome β5 subunit, providing fertile ground for scientific inquiry and advancing knowledge of these crucial biological entities.

Data availability

No datasets were generated or analysed during the current study.

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Funding

This work was supported by the Research Grant from Institute of Medical Sciences, Kangwon National University 2024, and by a Korea Basic Science Institute (National Research Facilities and Equipment Center) grant funded by the Ministry of Education (grant no. 2022R1A6C101A739).

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Authors and Affiliations

  1. Department of Pharmacology, Kangwon National University School of Medicine, Chuncheon, 24341, Republic of Korea

    Muhammad Yasir, Jinyoung Park & Wanjoo Chun

  2. Department of Medical Environmental Biology and Tropical Medicine, Kangwon National University School of Medicine, Chuncheon, 24341, Republic of Korea

    Eun-Taek Han & Jin-Hee Han

  3. Department of Physiology, Kangwon National University School of Medicine, Chuncheon, 24341, Republic of Korea

    Won Sun Park

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Contributions

MY and JYP were involved in the experimental operation and data analysis. ETH, WSP, and JHH were involved in data curation and in the methodology. WC was involved in the conceptualization, writing, reviewing, and editing of the manuscript. WC confirmed the authenticity of all the raw data. All authors have read and approved the final manuscript.

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Correspondence to Wanjoo Chun.

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Yasir, M., Park, J., Han, ET. et al. Structural comparison of human and Plasmodium proteasome β5 subunits: informing selective inhibitor design for anti-malaria agents. Malar J 24, 21 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12936-025-05259-z

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  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12936-025-05259-z

Keywords

Malaria Journal

ISSN: 1475-2875

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