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Identification of a short Spir interaction sequence at the C-terminal end of formin subgroup proteins.

ABSTRACT: The actin nucleation factors Spire and Cappuccino interact with each other and regulate essential cellular events during Drosophila oogenesis in a cooperative fashion. The interaction blocks formin actin nucleation activity and enhances the Spire activity. Analogous to Spire and Cappuccino, the mammalian homologs Spir-1 and formin-2 show a regulatory interaction. To get an understanding of the nature of the Spir-formin cooperation, we have analyzed the interaction biochemically and biophysically. Our data shows that the association of Spir-1 and formin-2 is not significantly mediated by binding of the Spir-1-KIND domain to the formin FH2 core domain. Instead, a short sequence motif C-terminal adjacent to the formin-2-FH2 domain could be characterized that mediates the interaction and is conserved among the members of the Fmn subgroup of formins. In line with this, we found that both mammalian Spir proteins, Spir-1 and Spir-2, interact with mammalian Fmn subgroup proteins formin-1 and formin-2.

SUBMITTER: Pechlivanis M

PROVIDER: S-EPMC2757234 | biostudies-literature | 2009 Sep

REPOSITORIES: biostudies-literature

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Identification of a short Spir interaction sequence at the C-terminal end of formin subgroup proteins.

Pechlivanis Markos M Samol Annette A Kerkhoff Eugen E

The Journal of biological chemistry 20090715 37

The actin nucleation factors Spire and Cappuccino interact with each other and regulate essential cellular events during Drosophila oogenesis in a cooperative fashion. The interaction blocks formin actin nucleation activity and enhances the Spire activity. Analogous to Spire and Cappuccino, the mammalian homologs Spir-1 and formin-2 show a regulatory interaction. To get an understanding of the nature of the Spir-formin cooperation, we have analyzed the interaction biochemically and biophysically ...[more]

PMID: 19605360

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Project description:BackgroundThe prognosis of glioblastoma remains poor, related to its diffuse spread within the brain. There is an ongoing search for molecular regulators of this particularly invasive behavior. One approach is to look for actin regulating proteins that might be targeted by future anti-cancer therapy. The formin family of proteins orchestrates rearrangement of the actin cytoskeleton in multiple cellular processes. Recently, the formin proteins mDia1 and mDia2 were shown to be expressed in glioblastoma in vitro, and their function could be modified by small molecule agonists. This finding implies that the formins could be future therapeutic targets in glioblastoma.MethodsIn cell studies, we investigated the changes in expression of the 15 human formins in primary glioblastoma cells and commercially available glioblastoma cell lines during differentiation from spheroids to migrating cells using transcriptomic analysis and qRT-PCR. siRNA mediated knockdown of selected formins was performed to investigate whether their expression affects glioblastoma migration. Using immunohistochemistry, we studied the expression of two formins, FHOD1 and INF2, in tissue samples from 93 IDH-wildtype glioblastomas. Associated clinicopathological parameters and follow-up data were utilized to test whether formin expression correlates with survival or has prognostic value.ResultsWe found that multiple formins were upregulated during migration. Knockdown of individual formins mDia1, mDia2, FHOD1 and INF2 significantly reduced migration in most studied cell lines. Among the studied formins, knockdown of INF2 generated the greatest reduction in motility in vitro. Using immunohistochemistry, we demonstrated expression of formin proteins FHOD1 and INF2 in glioblastoma tissues. Importantly, we found that moderate/high expression of INF2 was associated with significantly impaired prognosis.ConclusionsFormins FHOD1 and INF2 participate in glioblastoma cell migration. Moderate/high expression of INF2 in glioblastoma tissue is associated with worse outcome. Taken together, our in vitro and tissue studies suggest a pivotal role for INF2 in glioblastoma. When specific inhibiting compounds become available, INF2 could be a target in the search for novel glioblastoma therapies.

Project description:Systematically discovering protein-ligand interactions across the entire human and pathogen genomes is critical in chemical genomics, protein function prediction, drug discovery, and many other areas. However, more than 90% of gene families remain "dark"-i.e., their small-molecule ligands are undiscovered due to experimental limitations or human/historical biases. Existing computational approaches typically fail when the dark protein differs from those with known ligands. To address this challenge, we have developed a deep learning framework, called PortalCG, which consists of four novel components: (i) a 3-dimensional ligand binding site enhanced sequence pre-training strategy to encode the evolutionary links between ligand-binding sites across gene families; (ii) an end-to-end pretraining-fine-tuning strategy to reduce the impact of inaccuracy of predicted structures on function predictions by recognizing the sequence-structure-function paradigm; (iii) a new out-of-cluster meta-learning algorithm that extracts and accumulates information learned from predicting ligands of distinct gene families (meta-data) and applies the meta-data to a dark gene family; and (iv) a stress model selection step, using different gene families in the test data from those in the training and development data sets to facilitate model deployment in a real-world scenario. In extensive and rigorous benchmark experiments, PortalCG considerably outperformed state-of-the-art techniques of machine learning and protein-ligand docking when applied to dark gene families, and demonstrated its generalization power for target identifications and compound screenings under out-of-distribution (OOD) scenarios. Furthermore, in an external validation for the multi-target compound screening, the performance of PortalCG surpassed the rational design from medicinal chemists. Our results also suggest that a differentiable sequence-structure-function deep learning framework, where protein structural information serves as an intermediate layer, could be superior to conventional methodology where predicted protein structures were used for the compound screening. We applied PortalCG to two case studies to exemplify its potential in drug discovery: designing selective dual-antagonists of dopamine receptors for the treatment of opioid use disorder (OUD), and illuminating the understudied human genome for target diseases that do not yet have effective and safe therapeutics. Our results suggested that PortalCG is a viable solution to the OOD problem in exploring understudied regions of protein functional space.

Dataset Information

Identification of a short Spir interaction sequence at the C-terminal end of formin subgroup proteins.

Publications

Identification of a short Spir interaction sequence at the C-terminal end of formin subgroup proteins.

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