Dataset Information

Autoregulation of the LIM kinases by their PDZ domain.

ABSTRACT: LIM domain kinases (LIMK) are important regulators of actin cytoskeletal remodeling. These protein kinases phosphorylate the actin depolymerizing factor cofilin to suppress filament severing, and are key nodes between Rho GTPase cascades and actin. The two mammalian LIMKs, LIMK1 and LIMK2, contain consecutive LIM domains and a PDZ domain upstream of the C-terminal kinase domain. The roles of the N-terminal regions are not fully understood, and the function of the PDZ domain remains elusive. Here, we determine the 2.0 Å crystal structure of the PDZ domain of LIMK2 and reveal features not previously observed in PDZ domains including a core-facing arginine residue located at the second position of the 'x-Φ-G-Φ' motif, and that the expected peptide binding cleft is shallow and poorly conserved. We find a distal extended surface to be highly conserved, and when LIMK1 was ectopically expressed in yeast we find targeted mutagenesis of this surface decreases growth, implying increased LIMK activity. PDZ domain LIMK1 mutants expressed in yeast are hyperphosphorylated and show elevated activity in vitro. This surface in both LIMK1 and LIMK2 is critical for autoregulation independent of activation loop phosphorylation. Overall, our study demonstrates the functional importance of the PDZ domain to autoregulation of LIMKs.

SUBMITTER: Casanova-Sepulveda G

PROVIDER: S-EPMC10730565 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature

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Autoregulation of the LIM kinases by their PDZ domain.

Casanova-Sepúlveda Gabriela G Sexton Joel A JA Turk Benjamin E BE Boggon Titus J TJ

Nature communications 20231219 1

LIM domain kinases (LIMK) are important regulators of actin cytoskeletal remodeling. These protein kinases phosphorylate the actin depolymerizing factor cofilin to suppress filament severing, and are key nodes between Rho GTPase cascades and actin. The two mammalian LIMKs, LIMK1 and LIMK2, contain consecutive LIM domains and a PDZ domain upstream of the C-terminal kinase domain. The roles of the N-terminal regions are not fully understood, and the function of the PDZ domain remains elusive. Here ...[more]

PMID: 38114480

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Project description:Predictive approaches such as virtual screening have been used in drug discovery with the objective of reducing developmental time and costs. Current machine learning and network-based approaches have issues related to generalization, usability, or model interpretability, especially due to the complexity of target proteins' structure/function, and bias in system training datasets. Here, we propose a new method "DRUIDom" (DRUg Interacting Domain prediction) to identify bio-interactions between drug candidate compounds and targets by utilizing the domain modularity of proteins, to overcome problems associated with current approaches. DRUIDom is composed of two methodological steps. First, ligands/compounds are statistically mapped to structural domains of their target proteins, with the aim of identifying their interactions. As such, other proteins containing the same mapped domain or domain pair become new candidate targets for the corresponding compounds. Next, a million-scale dataset of small molecule compounds, including those mapped to domains in the previous step, are clustered based on their molecular similarities, and their domain associations are propagated to other compounds within the same clusters. Experimentally verified bioactivity data points, obtained from public databases, are meticulously filtered to construct datasets of active/interacting and inactive/non-interacting drug/compound-target pairs (~2.9M data points), and used as training data for calculating parameters of compound-domain mappings, which led to 27,032 high-confidence associations between 250 domains and 8,165 compounds, and a finalized output of ~5 million new compound-protein interactions. DRUIDom is experimentally validated by syntheses and bioactivity analyses of compounds predicted to target LIM-kinase proteins, which play critical roles in the regulation of cell motility, cell cycle progression, and differentiation through actin filament dynamics. We showed that LIMK-inhibitor-2 and its derivatives significantly block the cancer cell migration through inhibition of LIMK phosphorylation and the downstream protein cofilin. One of the derivative compounds (LIMKi-2d) was identified as a promising candidate due to its action on resistant Mahlavu liver cancer cells. The results demonstrated that DRUIDom can be exploited to identify drug candidate compounds for intended targets and to predict new target proteins based on the defined compound-domain relationships. Datasets, results, and the source code of DRUIDom are fully-available at: https://github.com/cansyl/DRUIDom.

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Autoregulation of the LIM kinases by their PDZ domain.

Publications

Autoregulation of the LIM kinases by their PDZ domain.

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