<scp>DomainMapper</scp>: Accurate domain structure annotation including those with non‐contiguous topologies

Manriquez-Sandoval, Edgar; Fried, Stephen D.

doi:10.1002/pro.4465

Cited by 8 publications

(12 citation statements)

References 39 publications

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“…First, sequences were annotated with InterProscan 31 and InterPro 32 (interproscan‐5.59‐91.0). In addition, domainMapper 33 (version 3.0.2) and the Evolutionary Classification of Protein Domains (ECOD) were used to complete the sequence annotation. This HMM parsing algorithm provides the detection of non‐contiguous, insertional, and circularly permuted domains as well.…”

Section: Methodsmentioning

confidence: 99%

AlphaFold2‐guided description of CoBaHMA, a novel family of bacterial domains within the heavy‐metal‐associated superfamily

Gaschignard,

Millet,

Bruley

et al. 2024

Proteins

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Three‐dimensional (3D) structure information, now available at the proteome scale, may facilitate the detection of remote evolutionary relationships in protein superfamilies. Here, we illustrate this with the identification of a novel family of protein domains related to the ferredoxin‐like superfold, by combining (i) transitive sequence similarity searches, (ii) clustering approaches, and (iii) the use of AlphaFold2 3D structure models. Domains of this family were initially identified in relation with the intracellular biomineralization of calcium carbonates by Cyanobacteria. They are part of the large heavy‐metal‐associated (HMA) superfamily, departing from the latter by specific sequence and structural features. In particular, most of them share conserved basic amino acids (hence their name CoBaHMA for Conserved Basic residues HMA), forming a positively charged surface, which is likely to interact with anionic partners. CoBaHMA domains are found in diverse modular organizations in bacteria, existing in the form of monodomain proteins or as part of larger proteins, some of which are membrane proteins involved in transport or lipid metabolism. This suggests that the CoBaHMA domains may exert a regulatory function, involving interactions with anionic lipids. This hypothesis might have a particular resonance in the context of the compartmentalization observed for cyanobacterial intracellular calcium carbonates.

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Section: Methodsmentioning

confidence: 99%

AlphaFold2‐guided description of CoBaHMA, a novel family of bacterial domains within the heavy‐metal‐associated superfamily

Gaschignard,

Millet,

Bruley

et al. 2024

Proteins

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“…34 Protein disorder is predicted using Metapredict 35 with the default disorder score thresholds. Optionally, protein domain information can be supplemented from DomainMapper, 36 though this requires that a user provide a DomainMapper output. Moreover, when provided with DomainMapper outputs, FLiPPR can perform advanced structural analyses by mapping cut-sites to regions within domains or linkers.…”

Section: Metadata Integrationmentioning

confidence: 99%

FLiPPR: A Processor for Limited Proteolysis (LiP) Mass Spectrometry Data Sets Built on FragPipe

Manriquez-Sandoval,

Brewer,

Lule

et al. 2024

J. Proteome Res.

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Here, we present FLiPPR, or FragPipe LiP (limited proteolysis) Processor, a tool that facilitates the analysis of data from limited proteolysis mass spectrometry (LiP-MS) experiments following primary search and quantification in FragPipe. LiP-MS has emerged as a method that can provide proteome-wide information on protein structure and has been applied to a range of biological and biophysical questions. Although LiP-MS can be carried out with standard laboratory reagents and mass spectrometers, analyzing the data can be slow and poses unique challenges compared to typical quantitative proteomics workflows. To address this, we leverage FragPipe and then process its output in FLiPPR. FLiPPR formalizes a specific data imputation heuristic that carefully uses missing data in LiP-MS experiments to report on the most significant structural changes. Moreover, FLiPPR introduces a data merging scheme and a protein-centric multiple hypothesis correction scheme, enabling processed LiP-MS data sets to be more robust and less redundant. These improvements strengthen statistical trends when previously published data are reanalyzed with the FragPipe/FLiPPR workflow. We hope that FLiPPR will lower the barrier for more users to adopt LiP-MS, standardize statistical procedures for LiP-MS data analysis, and systematize output to facilitate eventual larger-scale integration of LiP-MS data.

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“…31 Protein disorder is predicted using Metapredict 32 with the default disorder score thresholds. Optionally, protein domain information can be supplemented from DomainMapper, 33 though this requires that a user provide a DomainMapper output.…”

Section: Computational Sectionmentioning

confidence: 99%

“…(D) Fraction of proteins nonrefolding as a function of number of domains, based on cut-sites with FDR correction for E. coli and B. cereus. Domain assignment is determined in DomainMapper 37.…”

mentioning

confidence: 99%

FLiPPR: A Processor for Limited Proteolysis (LiP) Mass Spectrometry Datasets Built on FragPipe

Manriquez-Sandoval,

Brewer,

Lule

et al. 2023

Preprint

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Here, we present FLiPPR, or FragPipe LiP (limited proteolysis) Processor, a tool that facilitates the analysis of data from limited proteolysis mass spectrometry (LiP-MS) experiments following primary search and quantification in FragPipe. LiP-MS has emerged as a method that can provide proteome-wide information on protein structure and has been applied to a range of biological and biophysical questions. Although LiP- MS can be carried out with standard laboratory reagents and mass spectrometers, analyzing the data can be slow and poses unique challenges compared to typical quantitative proteomics workflows. To address this, we leverage the fast, sensitive, and accurate search and label-free quantification algorithms in FragPipe and then process its output in FLiPPR. FLiPPR formalizes a specific data imputation heuristic that carefully uses missing data in LiP-MS experiments to report on the most significant structural changes. Moreover, FLiPPR introduces a new data merging scheme (from ions to cut-sites) and a protein-centric multiple hypothesis correction scheme, collectively enabling processed LiP-MS datasets to be more robust and less redundant. These improvements substantially strengthen statistical trends when previously published data are reanalyzed with the FragPipe/FLiPPR workflow. As a final feature, FLiPPR facilitates the collection of structural metadata to identify correlations between experiments and structural features. We hope that FLiPPR will lower the barrier for more users to adopt LiP-MS, standardize statistical procedures for LiP-MS data analysis, and systematize output to facilitate eventual larger-scale integration of LiP-MS data.

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DomainMapper: Accurate domain structure annotation including those with non‐contiguous topologies

Cited by 8 publications

References 39 publications

AlphaFold2‐guided description of CoBaHMA, a novel family of bacterial domains within the heavy‐metal‐associated superfamily

AlphaFold2‐guided description of CoBaHMA, a novel family of bacterial domains within the heavy‐metal‐associated superfamily

FLiPPR: A Processor for Limited Proteolysis (LiP) Mass Spectrometry Data Sets Built on FragPipe

FLiPPR: A Processor for Limited Proteolysis (LiP) Mass Spectrometry Datasets Built on FragPipe

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