Virtual screening of small molecules for targeting DYRK1A kinase: Identifying novel inhibitors through computational approaches

Down syndrome (trisomy 21) is the most common genetic cause of neurological disorders. The DYRK1A gene is located in the Down Syndrome Critical Region (DSCR) on human chromosome 21, a region that plays a crucial role in the symptoms of Down syndrome and is mainly responsible for its development. Here, we screened approximately 75,000 natural product compounds to inhibit DYRK1A kinase enzymatic activity, offering a potential therapeutic approach to alleviate the pathological effects linked to its overexpression in Down syndrome (DS). First, we selected a hundred compounds based on docking scores. After further screening based on ADMET properties, we narrowed the selection down to five compounds. The apo system and complexes with the five lead compounds were subjected to 3 × 200 ns molecular dynamics simulations. Abemaciclib was used as a control molecule, as it has been shown to potentially inhibit DYRK1A enzymatic activity. Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) calculations demonstrated that Lead1 (ΔG bind = -25.10 kcal/mol) and Lead2 (ΔG bind = -22.24 kcal/mol) exhibited higher binding affinities towards DYRK1A kinase compared to the control molecule (ΔGbind = -17.52 kcal/mol). Analysis of Protein Structure Networks highlighted conformational and network shifts triggered by ligand binding. Furthermore, using a deep learning approach (DeLA Drug), we identified an abemaciclib analogue exhibiting enhanced binding affinity compared to the control, revealing key interacting residues. Overall, our study provides important insights for developing new and effective DYRK1A inhibitors, with some compounds showing potential as drug candidates, pending confirmation through laboratory testing.

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Publication Details

Journal
In Silico Research in Biomedicine
Published
2025-01-01
DOI
https://doi.org/10.1016/j.insi.2025.100038
Citations
1
Primary Topic
Bioinformatics and Genomic Networks
Type
article
Field-Weighted Citation Impact
0.81

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article

Virtual screening of small molecules for targeting DYRK1A kinase: Identifying novel inhibitors through computational approaches

Kapil Dattatray Ursal, Parimal Kar
1 citations
In Silico Research in Biomedicine
Bioinformatics and Genomic Networks
0.81
article

Virtual screening of small molecules for targeting DYRK1A kinase: Identifying novel inhibitors through computational approaches

Kapil Dattatray Ursal, Parimal Kar
article en
1 citations

Abstract

Down syndrome (trisomy 21) is the most common genetic cause of neurological disorders. The DYRK1A gene is located in the Down Syndrome Critical Region (DSCR) on human chromosome 21, a region that plays a crucial role in the symptoms of Down syndrome and is mainly responsible for its development. Here, we screened approximately 75,000 natural product compounds to inhibit DYRK1A kinase enzymatic activity, offering a potential therapeutic approach to alleviate the pathological effects linked to its overexpression in Down syndrome (DS). First, we selected a hundred compounds based on docking scores. After further screening based on ADMET properties, we narrowed the selection down to five compounds. The apo system and complexes with the five lead compounds were subjected to 3 × 200 ns molecular dynamics simulations. Abemaciclib was used as a control molecule, as it has been shown to potentially inhibit DYRK1A enzymatic activity. Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) calculations demonstrated that Lead1 (ΔG bind = -25.10 kcal/mol) and Lead2 (ΔG bind = -22.24 kcal/mol) exhibited higher binding affinities towards DYRK1A kinase compared to the control molecule (ΔGbind = -17.52 kcal/mol). Analysis of Protein Structure Networks highlighted conformational and network shifts triggered by ligand binding. Furthermore, using a deep learning approach (DeLA Drug), we identified an abemaciclib analogue exhibiting enhanced binding affinity compared to the control, revealing key interacting residues. Overall, our study provides important insights for developing new and effective DYRK1A inhibitors, with some compounds showing potential as drug candidates, pending confirmation through laboratory testing.

In Silico Research in BiomedicineVol. 1
Indian Institute of Technology Indore (IN)
Inspire Foundation, Department of Science and Technology, Ministry of Science and Technology, India
Openalex Percentile: Top 25%
Bioinformatics and Genomic Networks
0.81
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Virtual screening of small molecules for targeting DYRK1A kinase: Identifying novel inhibitors through computational approaches — Kapil Dattatray Ursal, Parimal Kar · In Silico Research in Biomedicine (2025) | TGRS Research Map | TGRS