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Biomolecules
Special Issues
Structural Proteomics–Structural Biology Led by Advancements in Mass Spectrometry Techniques
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Structural Proteomics–Structural Biology Led by Advancements in Mass Spectrometry Techniques

A special issue of Biomolecules (ISSN 2218-273X). This special issue belongs to the section "Bioinformatics and Systems Biology".

Deadline for manuscript submissions: 20 November 2025 | Viewed by 3862

Special Issue Editors

Dr. Rohit Jain

E-Mail Website
Guest Editor
School of Medicine, Case Western Reserve University, Cleveland, OH, USA
Interests: structural biology; protein folding; mass spectrometry; biosensors; protein footprinting
Special Issues, Collections and Topics in MDPI journals
Dr. Corie Ralston

E-Mail Website
Guest Editor
Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
Interests: X-ray; structural characterization
Special Issues, Collections and Topics in MDPI journals
Dr. Gang (Gary) Ren

E-Mail Website
Guest Editor
The Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
Interests: single-molecule 3D structure; cryo-electron tomography; macromolecular dynamics and folding
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Structural proteomics, driven by advancements in mass spectrometry (MS), focuses on deriving structural information from MS-based data. These structural MS methods are pivotal for characterizing protein structures, determining protein–protein interactions, and identifying protein motions. They can also be used to study proteins that are inaccessible to techniques such as NMR or X-ray crystallography. These insights are invaluable to the biopharmaceutical industry for drug development, target identification, biomarker discovery, and understanding mechanisms of drug action.

We can broadly categorize structural MS methods into two groups: peptide-based techniques and intact protein analyses.

Peptide-Centric MS Techniques

Peptide-centric MS techniques perform orthogonal three-dimensional structural analyses to complement classical biophysical methods used in structural biology. These techniques include the following:

  • Hydroxyl radical protein footprinting MS (XFP, FPOP);
  • Hydrogen/deuterium exchange MS (HDX-MS);
  • Cross-linking MS (XL-MS);
  • Covalent labeling MS.

Intact Protein Analyses

For intact protein analyses, top-down MS is used to sequence intact proteins and complement bottom-up MS by providing detailed information, such as post-translational modifications. Native MS accurately measures the mass of intact non-covalent assemblies and provides information on homogeneity, stoichiometry, and the oligomeric state of native protein complexes. Combined with ion mobility, native MS can be used to capture a snapshot of protein conformation diversity, providing global information on shapes through collision cross-section (CCS) or collision-induced unfolding (CIU) measurements.

Special Issue Call for Papers

This Special Issue aims to highlight recent innovative approaches and significant progress in structural proteomics methods. We welcome contributions on a wide range of topics, including protein-labeling approaches (XFP, FPOP, and HDX), cross-linking MS, protein interactome mapping, and intact and top-down MS. Scholars are invited to submit both original research articles and reviews.

This Special Issue promises to be a significant resource for those in the field of structural biology and mass spectrometry, offering insights into the latest methodologies and their applications.

Dr. Rohit Jain
Dr. Corie Ralston
Dr. Gang (Gary) Ren
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biomolecules is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • hydroxyl radical protein footprinting MS (XFP, FPOP)
  • hydrogen/deuterium exchange MS (HDX-MS)
  • cross-linking MS (XL-MS)
  • covalent labeling MS
  • top-down MS
  • native MS

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Published Papers (2 papers)

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11 pages, 1793 KiB  
Article
Installation of an Indole on the BRCA1 Disordered Domain Using Triazine Chemistry
by Liam E. Claton, Chrissy Baker, Hayes Martin, Sergei V. Dzyuba, Khadiza Zaman, Laszlo Prokai, Mikaela D. Stewart and Eric E. Simanek
Biomolecules 2024, 14(12), 1625; https://doi.org/10.3390/biom14121625 - 18 Dec 2024
Viewed by 915
Abstract
The functionalization of protein sidechains with highly water-soluble chlorotriazines (or derivatives thereof) using nucleophilic aromatic substitution reactions has been commonly employed to install various functional groups, including poly(ethylene glycol) tags or fluorogenic labels. Here, a poorly soluble dichlorotriazine with an appended indole is [...] Read more.
The functionalization of protein sidechains with highly water-soluble chlorotriazines (or derivatives thereof) using nucleophilic aromatic substitution reactions has been commonly employed to install various functional groups, including poly(ethylene glycol) tags or fluorogenic labels. Here, a poorly soluble dichlorotriazine with an appended indole is shown to react with a construct containing the disordered domain of BRCA1. Subsequently, this construct can undergo proteolytic cleavage to remove the SUMO-tag: the N-terminal poly(His) tag is still effective for purification. Steady-state fluorescence, circular dichroism spectroscopy, and isothermal titration calorimetry with the binding partner of BRCA1, PALB2, are used to characterize the indole-labeled BRCA1. Neither the reaction conditions nor the indole-tag appreciably alter the structure of the BRCA1. Mass spectrometry confirms that the target is modified once, although the location of modification cannot be determined by tandem mass spectrometry with collision-induced dissociation due to disadvantageous fragmentation patterns. Full article
(This article belongs to the Special Issue Structural Proteomics–Structural Biology Led by Advancements in Mass Spectrometry Techniques)
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Review

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23 pages, 845 KiB  
Review
Structure-Based Approaches for Protein–Protein Interaction Prediction Using Machine Learning and Deep Learning
by Despoina P. Kiouri, Georgios C. Batsis and Christos T. Chasapis
Biomolecules 2025, 15(1), 141; https://doi.org/10.3390/biom15010141 - 17 Jan 2025
Cited by 1 | Viewed by 2518
Abstract
Protein–Protein Interaction (PPI) prediction plays a pivotal role in understanding cellular processes and uncovering molecular mechanisms underlying health and disease. Structure-based PPI prediction has emerged as a robust alternative to sequence-based methods, offering greater biological accuracy by integrating three-dimensional spatial and biochemical features. [...] Read more.
Protein–Protein Interaction (PPI) prediction plays a pivotal role in understanding cellular processes and uncovering molecular mechanisms underlying health and disease. Structure-based PPI prediction has emerged as a robust alternative to sequence-based methods, offering greater biological accuracy by integrating three-dimensional spatial and biochemical features. This work summarizes the recent advances in computational approaches leveraging protein structure information for PPI prediction, focusing on machine learning (ML) and deep learning (DL) techniques. These methods not only improve predictive accuracy but also provide insights into functional sites, such as binding and catalytic residues. However, challenges such as limited high-resolution structural data and the need for effective negative sampling persist. Through the integration of experimental and computational tools, structure-based prediction paves the way for comprehensive proteomic network analysis, holding promise for advancements in drug discovery, biomarker identification, and personalized medicine. Future directions include enhancing scalability and dataset reliability to expand these approaches across diverse proteomes. Full article
(This article belongs to the Special Issue Structural Proteomics–Structural Biology Led by Advancements in Mass Spectrometry Techniques)
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