Structure-based design of DYRK1A inhibitors for Alzheimer’s disease

Introduction

Alzheimer's disease (AD) is the most common neurodegenerative disorder and accounts for 60-70% of all dementia cases worldwide, producing progressive decline in memory, cognition, and the capacity for independent living [1,2] . Despite decades of research, treatment remains largely symptomatic, and a mechanistic understanding of the pathways driving neurodegeneration is essential for developing disease-modifying therapies [1,2,3] . AD pathology is defined by extracellular amyloid-β (Aβ) plaques, intracellular neurofibrillary tangles composed of hyperphosphorylated tau, synaptic dysfunction, chronic neuroinflammation, and progressive neuronal loss [2,4,5] . Abnormal tau phosphorylation in particular drives tau misfolding and tangle formation, which has focused considerable research attention on the kinases responsible for this hyperphosphorylation [4,5,6] . Among these kinases, dual-specificity tyrosine phosphorylation-regulated kinase 1A (DYRK1A) has emerged as one of the most promising targets for AD therapy [7,8] . Encoded on chromosome 21q22. 13 and belonging to the CMGC family of protein kinases, DYRK1A normally supports neuronal differentiation, synaptic plasticity, and brain development, but its dysregulation is implicated in Alzheimer's disease, Down syndrome, and Parkinson's disease [7, 9, 10] . Experimentally, DYRK1A phosphorylates tau at several pathological residues and separately promotes amyloid precursor protein processing and Aβ production, placing it upstream of both major pathological arms of AD and making it an attractive target for disease-modifying, rather than purely symptomatic, intervention [6,7,10] . Structure-based drug design (SBDD) has become central to modern kinase-inhibitor discovery, using high-resolution three-dimensional protein structures to predict proteinligand interactions computationally prior to experimental testing [11,12] . The present study uses the crystal structure of the human DYRK1A kinase domain (PDB ID: 7O7K), solved at 1.82 Å resolution in complex with the FDAapproved CDK4/6 inhibitor abemaciclib, which also inhibits DYRK1A [8] . This co-crystal structure defines the ATPbinding pocket and the residues governing ligand recognition, providing an experimentally validated template for docking, virtual screening, and inhibitor optimization [8,11,12] . Reported DYRK1A inhibitors, including harmine derivatives, leucettines, INDY-class compounds, and repurposed kinase inhibitors such as abemaciclib, continue to face limitations in selectivity, pharmacokinetics, bloodbrain barrier permeability, and off-target toxicity [13] , and recent computational screening studies have continued to identify new candidate chemotypes with improved properties [13,14] . In parallel, next-generation sequencing (NGS) has transformed the genetic characterization of complex diseases such as AD, enabling rapid, massively parallel identification of causal and risk-associated variants. NGS-based studies have identified causal genes (APP, PSEN1, PSEN2) and risk loci (APOE, TREM2, SORL1, BIN1, CLU, PICALM) through genome-wide association studies, and transcriptomic profiling has clarified dysregulated pathways in neuroinflammation, synaptic dysfunction, and oxidative stress [15][16][17][18][19][20] . Integrating this genomic evidence with structural biology allows diseaserelevant targets to be prioritized on the basis of both genetic and structural evidence, a systems-level strategy that improves on treating sequence and structure as independent lines of investigation [17,18,11,21] .Most published DYRK1A studies, however, have applied computational screening or genomic analysis separately rather than in combination [17,11] . The present study therefore integrates NGS-informed sequence analysis with structure-based drug design targeting human DYRK1A (PDB ID: 7O7K), combining protein sequence validation, structural quality assessment, proteinprotein interaction network analysis, and molecular docking of candidate ligands, with the goal of identifying and structurally justifying candidate inhibitors for further development against Alzheimer's disease [11,17,21] .

Materials and Methods

This study followed an integrated computational workflow comprising protein structure retrieval and validation, sequence similarity and phylogenetic analysis, proteinprotein interaction network mapping, and structure-based molecular docking, summarized in the sub-sections below [22][23][24][25] .

Retrieval of the DYRK1A Protein Structure and Sequence

The three-dimensional crystal structure of human DYRK1A was retrieved from the Protein Data Bank (PDB ID: 7O7K), corresponding to the DYRK1A kinase domain cocrystallized with abemaciclib [22,23,26] , and downloaded in .pdb format. The corresponding amino-acid sequence was obtained in FASTA format from the NCBI Molecular Modelling Database (MMDB), which links structural, sequence, and conserved-domain annotations to each PDB entry [24,27] .

Sequence Similarity and Phylogenetic Analysis

The retrieved FASTA sequence was submitted as a query to BLASTP (Basic Local Alignment Search Tool for Proteins) against the PDB protein database using default parameters [28, 29] . Homologous sequences were evaluated by maximum score, query coverage, E-value, and percentage identity [29,30] . Evolutionary relationships among the resulting homologues were then visualized using the BLAST Distance Tree Viewer, which applies the Fast Minimum Evolution algorithm to cluster sequences by evolutionary distance [31] .

Protein Structure Validation

Structural quality was assessed using the SAVES v6.0 server [32] . ERRAT was used to evaluate overall model quality from the statistics of non-bonded atomic interactions, with structures classified as excellent (≥95%), acceptable (80-90%), or requiring refinement (<80%) [33,34] . Stereochemical quality was separately assessed using PROCHECK, which generates a Ramachandran plot showing the distribution of backbone dihedral (φ/ψ) angles across the most favoured, additionally allowed, generously allowed, and disallowed regions [34] .

Structure Visualization, Ligand Contacts, and B-Factor Analysis

The validated DYRK1A structure was visualized in PyMOL (Version 3.0, Schrödinger, LLC) [35,36] with a white background and water molecules removed. The cocrystallized ligand was highlighted and its surrounding pocket rendered as a molecular surface, with contact residues labelled using PyMOL's residue annotation tools. Hydrogen bonds and interatomic distances were measured using PyMOL's built-in distance tools. Per-residue B-factors were extracted and mapped onto the structure to identify conformationally flexible, solvent-exposed regions relative to the stable protein core [35,37] .

Molecular Docking

Molecular docking was performed using a curvature-based blind-docking server that automatically detects candidate binding cavities on the protein surface using its CurPocket algorithm and docks ligands into each predicted cavity with AutoDock Vina (version 1.1.2), without requiring a predefined grid box [42,43,44] . The validated receptor (PDB ID: 7O7K) was uploaded in PDB format. Structure data files (SDF) for five candidate ligands, pazopanib (PubChem CID 10113978), kaempferol (PubChem CID 5280863), emodin (PubChem CID 3220), sunitinib (PubChem CID 5329102), and abemaciclib (PubChem CID 46220502), were retrieved from PubChem [45] and docked individually. For each ligand, CB-Dock ranked the predicted cavities by AutoDock Vina score (kcal/mol), with more negative scores indicating more favourable predicted binding, alongside cavity volume (ų) and docking-box dimensions. The top-ranked cavity for each ligand was carried forward for detailed contact-residue analysis in PyMOL [35,36] . Abemaciclib, the ligand cocrystallized with PDB ID: 7O7K, was re-docked using the same protocol as an internal positive control.

Protein-Protein Interaction and Pathway Analysis

A protein-protein interaction (PPI) network for DYRK1A was constructed using STRING (Search Tool for the Retrieval of Interacting Genes/Proteins, version 12.0) [38] , querying the DYRK1A gene symbol against the Homo sapiens genome at the default medium-confidence threshold. Predicted partners were ranked by the STRING combined confidence score, which integrates experimental, curateddatabase, co-expression, genomic-context, and text-mining evidence. To place this network in a disease context, the DYRK1A interaction partners identified by STRING were cross-referenced against the KEGG Alzheimer's disease pathway (map hsa05010) [50,51] , which curates the amyloidogenic, tau-hyperphosphorylation, and neuroinflammatory processes underlying AD pathology.

Results

Retrieval and Overview of the DYRK1A Structure

The crystal structure of human DYRK1A (PDB ID: 7O7K) was successfully retrieved from the Protein Data Bank. The deposited structure represents the kinase domain cocrystallized with abemaciclib and belongs to the transferase class, with Chain A containing the complete kinase domain used as the query for downstream sequence and structural analyses (Figure 1). [52,53] Fig 1: Crystal structure of the human DYRK1A kinase domain (PDB ID: 7O7K) retrieved from the Protein Data Bank.

Sequence Similarity Analysis

BLASTP analysis confidently identified the query sequence as human DYRK1A. All significant alignments returned an E-value of 0.0, query coverage of 99-100%, and sequence identity of 99.72-100% against previously deposited human and mouse DYRK1A structures (Figure 2), confirming the identity of the retrieved protein and its suitability for downstream structural analysis [54,55] .

Phylogenetic Analysis

The BLAST Distance Tree Viewer placed the query protein within the CDC-like kinase (CLK)/DYRK kinase family, clustering closely with other human DYRK and CLK isoforms (Figure 3). This pattern is consistent with the established classification of DYRK1A within the CMGC group of the human kinome and confirms strong evolutionary conservation of the kinase domain used as the docking template [56] .

Structural Quality Validation

ERRAT analysis of the DYRK1A structure returned an overall quality factor of 96.37%. Ramachandran plot analysis using PROCHECK showed that 88.7% (539 residues) of the structure fell within the most favoured regions, 10.9% (66 residues) in additionally allowed regions, 0.1% (1 residue) in generously allowed regions, and 0.2% (2 residues) in disallowed regions. [32,33,34]

B-Factor Analysis

B-factor mapping showed that the majority of the DYRK1A structure exhibited low atomic mobility, consistent with a stable, well-ordered kinase core. Elevated B-factors were largely confined to solvent-exposed loop regions, suggesting localized flexibility that may accommodate conformational adjustment during ligand binding without compromising the overall fold [57] .

Protein-Protein Interaction Network Analysis

STRING analysis identified DYRK1A as the hub of a tenpartner interaction network comprising DCAF7, RNF169, RAD54L2, LIN52, FAM53C, FAM117B, RCAN1, WDR26, MED13L, and NFATC1. DCAF7 (also known as WDR68), an established binding partner that stabilizes and regulates DYRK1A, showed the highest combined confidence score (0.997). RNF169, RAD54L2, LIN52, FAM53C, and FAM117B, associated with DNA-damage repair, genome stability, and cell-cycle regulation, showed high confidence scores (0.88-0.93), while RCAN1, WDR26, MED13L, and NFATC1, linked to calcineurin-NFAT signalling and transcriptional regulation, showed moderate confidence scores (0.82-0.88) [58,59] .

KEGG Pathway Analysis

Mapping the DYRK1A-centred interaction network onto the KEGG Alzheimer's disease pathway (map hsa05010) placed DYRK1A and its functional partners, including NFATC1, RCAN1, MED13L, WDR26, and DCAF7, within the pathway's amyloidogenic processing, tauhyperphosphorylation, mitochondrial-dysfunction, oxidative-stress, and neuroinflammatory branches (Figure 10). This convergence between the STRING-derived interaction network and the curated KEGG pathway provides disease-level support for DYRK1A as a therapeutically relevant target and establishes the rationale for the structure-based docking analysis that follows [60,61] .

Molecular Docking

Five candidate ligands, pazopanib, kaempferol, emodin, sunitinib, and the co-crystallized reference inhibitor abemaciclib, were docked against the validated DYRK1A kinase domain using CB-Dock. For each ligand, CB-Dock [62, 63] evaluated five candidate cavities detected by its CurPocket algorithm; the top-ranked cavity for each ligand, identified by its most negative AutoDock Vina score, is summarized in Table 1. Taken together, all five ligands converged on the same ATP-binding cleft of the DYRK1A kinase domain, sharing a substantially overlapping contact-residue footprint that spans the glycine-rich loop, hinge region, and catalytic loop. Pazopanib and abemaciclib produced the strongest predicted affinities of the panel, while kaempferol, emodin, and sunitinib each showed consistent, favourable engagement of the same pocket.

Conclusion

This study retrieved, validated, and structurally characterized the human DYRK1A kinase domain (PDB ID: 7O7K) as a computational template for structure-based drug discovery against Alzheimer's disease. BLASTP and phylogenetic analyses confirmed the identity and evolutionary conservation of the retrieved sequence, [64,65] while ERRAT and Ramachandran plot analyses confirmed excellent stereochemical quality, and B-factor analysis identified flexible, solvent-exposed loop regions relevant to ligand binding. STRING-based protein-protein interaction analysis placed DYRK1A within a biologically coherent signalling hub linked to DNA-damage repair, calcineurin-NFAT signalling, and transcriptional regulation, and mapping this network onto the KEGG Alzheimer's disease pathway confirmed its involvement in amyloidogenic, tauhyperphosphorylation, and neuroinflammatory processes central to AD pathology. Building on this validated foundation, CB-Dock-based molecular docking of five candidate ligands identified abemaciclib (-10.7 kcal/mol) and pazopanib (-10.3 kcal/mol) as the strongest predicted binders of the DYRK1A ATP-binding cleft, with kaempferol, emodin, and sunitinib each showing consistent, favourable engagement of the same pocket. Collectively, these findings establish a structurally validated and biologically contextualized basis for advancing this compound panel, particularly pazopanib, toward ADMET profiling and molecular dynamics simulation as part of a drug-repurposing strategy against Alzheimer's disease [66,67,68] .

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