Biology subjects

Guarguaglini, G.

Publications and source records attributed to Guarguaglini, G..

4 recordsLinked to original sources

bioRxiv2022

Revisiting degron motifs in human AURKA required for its targeting by APC/C-FZR1

Mitotic kinase Aurora A (AURKA) diverges from other kinases in its multiple active conformations that may explain its interphase roles and association with cancer, and the limited efficacy of drugs targeting the kinase pocket. Regulation of AURKA activity by the cell is critically dependent on destruction mediated by the Anaphase-Promoting Complex (APC/CFZR1) during mitotic exit and G1 phase and requires an atypical N-terminal degron in AURKA called the A-box in addition to a reported canonical D-box degron in the C-terminus. Here we find that the proposed C-terminal D-box of AURKA does not act as a degron and instead mediates essential structural features of the protein. In living cells, as previously reported in vitro, the N-terminal intrinsically disordered region (IDR) of AURKA containing the A-box is sufficient to confer FZR1-dependent mitotic degradation. Both in silico and in cellulo assays predict the QRVL Short Linear Interacting Motif (SLiM) of the A-box to be a phospho-regulated D-box. We propose that degradation of full-length AURKA additionally depends on an intact C-terminal domain because of critical conformational parameters permissive for both activity and mitotic degradation of AURKA. Summary blurbAURKA degron motifs are redefined to show that the so-called N-terminal A-box is in fact a D-box, and the so-called D-box in the C-terminus is not a degron but a motif critical for the active, degradable conformation of AURKA

cell biology↗

bioRxiv2021

A Focused Small-Molecule Screen Identifies PHA-680626 as an Amphosteric Inhibitor Disrupting the Interaction between Aurora-A and N-Myc

Neuroblastoma is a severe childhood disease, accounting for ~10% of all infant cancers. The amplification of the MYCN gene, coding for the N-Myc transcriptional factor, is an essential marker correlated with tumor progression and poor prognosis. In neuroblastoma cells, the mitotic kinase Aurora-A (AURKA), also frequently overexpressed in cancer, prevents N-Myc degradation, by directly binding to a highly conserved N-Myc region, i.e. Myc Box I. As a result, elevated levels of N-Myc, which are required for the growth of MYCN amplified cells, are observed. During the last years, it has been demonstrated that the ATP competitive inhibitors of AURKA CD532, MLN8054 and Alisertib also cause essential conformational changes in the structure of the activation loop of the kinase that prevent N-Myc binding, thus impairing the formation of the AURKA/N-Myc complex. In this study, starting from a screening of crystal structures of AURKA in complex with known inhibitors, we identified additional compounds affecting the conformation of the kinase activation loop. We assessed the ability of such compounds to disrupt the interaction between AURKA and N-Myc in vitro, using Surface Plasmon Resonance competition assays, and in tumor cell lines overexpressing MYCN, by performing Proximity Ligation Assays. Finally, their effects on N-Myc cellular levels and cell viability were investigated. Our results, identifying PHA-680626 as an amphosteric inhibitor both in vitro and MYCN overexpressing cell lines, expand the repertoire of known conformational disrupting inhibitors of the AURKA/N-Myc complex, and confirm that altering the conformation of the activation loop of AURKA with a small molecule is an effective strategy to destabilize the AURKA/N-Myc interaction in neuroblastoma cancer cells.

cancer biology↗

bioRxiv2019

AURKA destruction is decoupled from its activity at mitotic exit but suppresses interphase activity

Activity of AURKA is controlled through multiple mechanisms including phosphorylation, ubiquitin-mediated degradation, and allosteric interaction with TPX2. Activity peaks at mitosis before AURKA is degraded during mitotic exit in a process strictly dependent on APC/C coactivator FZR1. We used FZR1 knockout cells (FZR1KO) and a novel FRET-based AURKA biosensor to investigate how activity is regulated in absence of destruction. We found that AURKA activity in FZR1KO cells dropped at mitotic exit as rapidly as in parental cells, despite absence of destruction. Unexpectedly, TPX2 was degraded normally in FZR1KO cells. Overexpression of an N-terminal TPX2 fragment sufficient for AURKA binding, but not degraded at mitotic exit, caused delay in AURKA inactivation. We conclude that AURKA inactivation in mitotic exit is determined not by its own degradation but by degradation of TPX2 and therefore dependent on CDC20 rather than FZR1. The biosensor revealed that FZR1 instead suppresses AURKA activity in interphase and is critically required for assembly of the interphase mitochondrial network after mitosis.

cell biology↗

bioRxiv2019

Revisiting the \"satisfaction of spatial restraints\" approach of MODELLER for protein homology modeling

The most frequently used approach for protein structure prediction is currently homology modeling. The 3D model building phase of this methodology is critical for obtaining an accurate and biologically useful prediction. The most widely employed tool to perform this task is MODELLER. This program implements the \"modeling by satisfaction of spatial restraints\" strategy and its core algorithm has not been altered significantly since the early 1990s. In this work, we have explored the idea of modifying MODELLER with two effective, yet computationally light strategies to improve its 3D modeling performance. Firstly, we have investigated how the level of accuracy in the estimation of structural variability between a target protein and its templates in the form of{sigma} values profoundly influences 3D modeling. We show that the{sigma} values produced by MODELLER are on average weakly correlated to the true level of structural divergence between target-template pairs and that increasing this correlation greatly improves the programs predictions, especially in multiple-template modeling. Secondly, we have inquired into how the incorporation of statistical potential terms (such as the DOPE potential) in the MODELLERs objective function impacts positively 3D modeling quality by providing a small but consistent improvement in metrics such as GDT-HA and lDDT and a large increase in stereochemical quality. Python modules to harness this second strategy are freely available at https://github.com/pymodproject/altmod. In summary, we show that there is a large room for improving MODELLER in terms of 3D modeling quality and we propose strategies that could be pursued in order to further increase its performance.\n\nAuthor summaryProteins are fundamental biological molecules that carry out countless activities in living beings. Since the function of proteins is dictated by their three-dimensional atomic structures, acquiring structural details of proteins provides deep insights into their function. Currently, the most successful computational approach for protein structure prediction is template-based modeling. In this approach, a target protein is modeled using the experimentally-derived structural information of a template protein assumed to have a similar structure to the target. MODELLER is the most frequently used program for template-based 3D model building. Despite its success, its predictions are not always accurate enough to be useful in Biomedical Research. Here, we show that it is possible to greatly increase the performance of MODELLER by modifying two aspects of its algorithm. First, we demonstrate that providing the program with accurate estimations of local target-template structural divergence greatly increases the quality of its predictions. Additionally, we show that modifying MODELLERs scoring function with statistical potential energetic terms also helps to improve modeling quality. This work will be useful in future research, since it reports practical strategies to improve the performance of this core tool in Structural Bioinformatics.

bioinformatics↗