Targeting LIMK1 in Alzheimer's Disease: A Multifaceted Computational Investigation Involving ADMET, Virtual Screening, Molecular Docking, and Molecular Dynamics

LIM domain kinases (LIMKs), which include LIMK1 and LIMK2, are key proteins in actin dynamics. On this basis, the inhibition of LIMK1 enhances dendritic spine density and size in dementia, reducing Alzheimer's disease (AD) effects. Therefore, several small molecules were discovered as potential therapeutic targets for AD. Herein, a pharmacophore-based virtual screening was employed to identify novel potential LIMK1 inhibitors. The pharmacophore model derived from the co-crystallized receptor structure of PubChem-329823760: LIMK1 (PDB ID: 5NXC) was then used for virtual screening. After applying Lipinski's rules and pharmacophore filters, 29 potential hits were identified. Molecular docking simulations were performed to determine the binding affinities of these candidates against LIMK1, with results ranging from -5.20 to -10.60 kcal/mol. Notably, PubChem-136621040 showed the highest binding affinity against the target protein, with a docking score of -10.60 kcal/mol, slightly surpassing the native ligand, PubChem-329823760, possessing a lower docking score of -9.80 kcal/mol. The drug-likeness and toxicity properties of target compounds were assessed through ADMET evaluations. A series of 75 nanosecond molecular dynamics (MD) simulations were conducted on the complexes generated by the best-docked molecule and the native ligand. RMSD, RMSF, SASA, and Rg calculations of their trajectories were also calculated. PubChem-136621040 possessed an average RMSD value of 0.23 nm, lower than the native ligand's 0.31 nm, indicating a greater binding stability. The RMSF results also revealed that the best-docked compound had a lower value (0.10 nm), while the native ligand possessed a value of 0.12 nm. The SASA values for both the native ligand and the best-docked compound were nearly identical, at 150.20 nm2 and 150.80 nm2, respectively. The Rg results demonstrated that both complexes maintained their rigidity throughout the simulation, with similar average values of 2.04 nm for the native ligand and 2.06 nm for the best-docked compound.

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Journal
Journal of the Turkish Chemical Society Section A Chemistry
Published
2024-09-23
DOI
https://doi.org/10.18596/jotcsa.1465547
Primary Topic
Computational Drug Discovery Methods
Type
article
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0.00

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article

Targeting LIMK1 in Alzheimer's Disease: A Multifaceted Computational Investigation Involving ADMET, Virtual Screening, Molecular Docking, and Molecular Dynamics

Mazlum Türk, Gülbin Kurtay, Harun Nalçakan, Defne Eşkin et al.
Journal of the Turkish Chemical Society Section A Chemistry
Computational Drug Discovery Methods
article

Targeting LIMK1 in Alzheimer's Disease: A Multifaceted Computational Investigation Involving ADMET, Virtual Screening, Molecular Docking, and Molecular Dynamics

Mazlum Türk, Gülbin Kurtay, Harun Nalçakan, Defne Eşkin, Beril Uras, Yiğit Akkan
article en

Abstract

LIM domain kinases (LIMKs), which include LIMK1 and LIMK2, are key proteins in actin dynamics. On this basis, the inhibition of LIMK1 enhances dendritic spine density and size in dementia, reducing Alzheimer's disease (AD) effects. Therefore, several small molecules were discovered as potential therapeutic targets for AD. Herein, a pharmacophore-based virtual screening was employed to identify novel potential LIMK1 inhibitors. The pharmacophore model derived from the co-crystallized receptor structure of PubChem-329823760: LIMK1 (PDB ID: 5NXC) was then used for virtual screening. After applying Lipinski's rules and pharmacophore filters, 29 potential hits were identified. Molecular docking simulations were performed to determine the binding affinities of these candidates against LIMK1, with results ranging from -5.20 to -10.60 kcal/mol. Notably, PubChem-136621040 showed the highest binding affinity against the target protein, with a docking score of -10.60 kcal/mol, slightly surpassing the native ligand, PubChem-329823760, possessing a lower docking score of -9.80 kcal/mol. The drug-likeness and toxicity properties of target compounds were assessed through ADMET evaluations. A series of 75 nanosecond molecular dynamics (MD) simulations were conducted on the complexes generated by the best-docked molecule and the native ligand. RMSD, RMSF, SASA, and Rg calculations of their trajectories were also calculated. PubChem-136621040 possessed an average RMSD value of 0.23 nm, lower than the native ligand's 0.31 nm, indicating a greater binding stability. The RMSF results also revealed that the best-docked compound had a lower value (0.10 nm), while the native ligand possessed a value of 0.12 nm. The SASA values for both the native ligand and the best-docked compound were nearly identical, at 150.20 nm2 and 150.80 nm2, respectively. The Rg results demonstrated that both complexes maintained their rigidity throughout the simulation, with similar average values of 2.04 nm for the native ligand and 2.06 nm for the best-docked compound.

Journal of the Turkish Chemical Society Section A ChemistryVol. 11(4)
Ankara University (TR), Hacettepe University (TR)
Türkiye Bilimsel ve Teknolojik Araştırma Kurumu
Good health and well-being
Openalex Percentile: Top 81%
Computational Drug Discovery Methods
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