PGRS domain structures: Doomed to sail the mycomembrane

Berisio, Rita; Delogu, Giovanni

doi:10.1371/journal.ppat.1010760

Cited by 5 publications

(11 citation statements)

References 25 publications

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“…PG II sandwiches are formed by left-handed antiparallel PG II helices, sharing a similar conformation as poly-proline II [12,13], albeit stacked in two antiparallel groups, with glycine always pointing inwards, where no other residue would fit. More recently, the availability of AlphaFold2.0 offered a unique opportunity to better understand structural and functional properties of these sibylline domains [14]. Consistent with our previous models, AlphaFold2.0 predicts the structure of PGRS as PG II sandwich domains of modular size, with a large variability in the number of constituting PG II helices.…”

Section: Introductionsupporting

confidence: 80%

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Structural Basis of PE_PGRS Polymorphism, a Tool for Functional Modulation

et al. 2023

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Background: The mycobacterial PE_PGRS protein family is present only in pathogenic strains of the genus mycobacterium, such as Mtb and members of the MTB complex, suggesting a likely important role of this family in pathogenesis. Their PGRS domains are highly polymorphic and have been suggested to cause antigenic variations and facilitate pathogen survival. The availability of AlphaFold2.0 offered us a unique opportunity to better understand structural and functional properties of these domains and a role of polymorphism in Mtb evolution and dissemination. Methods: We made extensive use of AlphaFold2.0 computations and coupled them with sequence distribution phylogenetic and frequency analyses, and antigenic predictions. Results: Modeling of several polymorphic forms of PE_PGRS33, the prototype of the PE_PGRS family and sequence analyses allowed us to predict the structural impact of mutations/deletions/insertions present in the most frequent variants. These analyses well correlate with the observed frequency and with the phenotypic features of the described variants. Conclusions: Here, we provide a thorough description of structural impacts of the observed polymorphism of PE_PGRS33 protein and we correlate predicted structures to the known fitness of strains containing specific variants. Finally, we also identify protein variants associated with bacterial evolution, showing sophisticated modifications likely endowed with a gain-of-function role during bacterial evolution.

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Section: Introductionsupporting

confidence: 80%

“…Consistent with previous data, all modelled structures present a PE domain with an αhelical conformation, followed by the PGRS domain. Between the two domains, and conserved in the entire family, is the GRPLI motif (Figure 1) [5,14].…”

Section: Main Distinctive Features Of Pe_pgrs Structuresmentioning

confidence: 99%

Structural Basis of PE_PGRS Polymorphism, a Tool for Functional Modulation

et al. 2023

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“…Indeed, PE_PGRS33 interaction with Toll-like receptor 2 (TLR2) promotes the secretion of inflammatory chemokines and cytokines, which are key in the immunopathogenesis of tuberculosis [ 4 ]. This study, corroborated by successive studies [ 5 ], suggested that the PGRS domain of PE_PGRS33 exposes PGII sandwich domains on the outer surface, which are involved in the interactions with the host receptors [ 4 ]. As such, they are promising targets for a vaccination strategy aimed at inducing a humoral response.…”

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confidence: 74%

Molecular Immunology in Bacterial Vaccine Discovery

Berisio

2022

Cells

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“…Many of these belong to the 'Tetratricopeptide-like helical domain superfamily' where the median PDB structure length of structures with resolution < 3Å is only 370. Another example of repetitive structural outliers which are thought to be novel folds include the unusual "PGRS domains", found widely in mycobacteria (Berisio and Delogu, 2022).…”

Section: Fragments Repeats and Obligate Complexesmentioning

confidence: 99%

What is hidden in the darkness? Deep-learning assisted large-scale protein family curation uncovers novel protein families and folds

Durairaj

Waterhouse

Mets

et al. 2023

Preprint

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Driven by the development and upscaling of fast genome sequencing and assembly pipelines, the number of protein-coding sequences deposited in public protein sequence databases is increasing exponentially. Recently, the dramatic success of deep learning-based approaches applied to protein structure prediction has done the same for protein structures. We are now entering a new era in protein sequence and structure annotation, with hundreds of millions of predicted protein structures made available through the AlphaFold database. These models cover most of the catalogued natural proteins, including those difficult to annotate for function or putative biological role based on standard, homology-based approaches. In this work, we quantified how much of such "dark matter" of the natural protein universe was structurally illuminated by AlphaFold2 and modelled this diversity as an interactive sequence similarity network that can be navigated at https://uniprot3d.org/atlas/AFDB90v4. In the process, we discovered multiple novel protein families by searching for novelties from sequence, structure, and semantic perspectives. We added a number of them to Pfam, and experimentally demonstrate that one of these belongs to a novel superfamily of toxin-antitoxin systems, TumE-TumA. This work highlights the role of large-scale, evolution-driven protein comparison efforts in combination with structural similarities, genomic context conservation, and deep-learning based function prediction tools for the identification of novel protein families, aiding not only annotation and classification efforts but also the curation and prioritisation of target proteins for experimental characterisation.

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PGRS domain structures: Doomed to sail the mycomembrane

Cited by 5 publications

References 25 publications

Structural Basis of PE_PGRS Polymorphism, a Tool for Functional Modulation

Structural Basis of PE_PGRS Polymorphism, a Tool for Functional Modulation

Molecular Immunology in Bacterial Vaccine Discovery

What is hidden in the darkness? Deep-learning assisted large-scale protein family curation uncovers novel protein families and folds

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