ArticleMethods (San Diego, Calif.)2015
Protein structure prediction guided by crosslinking restraints--A systematic evaluation of the impact of the crosslinking spacer length.
Article in Methods (San Diego, Calif.), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
28 citing papers in PubMed.
- Structural proteomics defines a sequential priming mechanism for the progesterone receptor.Nature communications · 2025Article
- Fast cross-linking by DOPA2 promotes the capturing of a stereospecific protein complex over nonspecific encounter complexes.Biophysics reports · 2022Article
- pH Dependence of Succinimide-Ester-Based Protein Cross-Linking for Structural Mass Spectrometry Applications.ACS measurement science au · 2022Article
- Accounting for Neighboring Residue Hydrophobicity in Diethylpyrocarbonate Labeling Mass Spectrometry Improves Rosetta Protein Structure Prediction.Journal of the American Society for Mass Spectrometry · 2022Article
- Targeted Cross-Linking Mass Spectrometry on Single-Step Affinity Purified Molecular Complexes in the Yeast Saccharomyces cerevisiae.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Prediction of Protein Complex Structure Using Surface-Induced Dissociation and Cryo-Electron Microscopy.Analytical chemistry · 2021Article
- Article
- Hybrid methods for combined experimental and computational determination of protein structure.The Journal of chemical physics · 2020Review
- Mass Spectrometry-Based Protein Footprinting for Higher-Order Structure Analysis: Fundamentals and Applications.Chemical reviews · 2020Review
- Exploring Spacer Arm Structures for Designs of Asymmetric Sulfoxide-Containing MS-Cleavable Cross-Linkers.Analytical chemistry · 2020Article
- Article
- Federating Structural Models and Data: Outcomes from A Workshop on Archiving Integrative Structures.Structure (London, England : 1993) · 2019Article
- Bifunctional cross-linking approaches for mass spectrometry-based investigation of nucleic acids and protein-nucleic acid assemblies.Methods (San Diego, Calif.) · 2018Article
- Modeling Protein Complexes Using Restraints from Crosslinking Mass Spectrometry.Structure (London, England : 1993) · 2018Article
- Integrated Structural Biology for α-Helical Membrane Protein Structure Determination.Structure (London, England : 1993) · 2018Article
- Protein Tertiary Structure by Crosslinking/Mass Spectrometry.Trends in biochemical sciences · 2018Review
- Cross-Linking Mass Spectrometry: An Emerging Technology for Interactomics and Structural Biology.Analytical chemistry · 2018Review
- Iterative Molecular Dynamics-Rosetta Membrane Protein Structure Refinement Guided by Cryo-EM Densities.Journal of chemical theory and computation · 2017Article
- Novel Concepts of MS-Cleavable Cross-linkers for Improved Peptide Structure Analysis.Journal of the American Society for Mass Spectrometry · 2017Article
- A Novel MS-Cleavable Azo Cross-Linker for Peptide Structure Analysis by Free Radical Initiated Peptide Sequencing (FRIPS).Journal of the American Society for Mass Spectrometry · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Recent development of high-resolution mass spectrometry (MS) instruments enables chemical crosslinking (XL) to become a high-throughput method for obtaining structural information about proteins. Restraints derived from XL-MS experiments have been used successfully for structure refinement and protein-protein docking. However, one formidable question is under which circumstances XL-MS data might be sufficient to determine a protein's tertiary structure de novo? Answering this question will not only include understanding the impact of XL-MS data on sampling and scoring within a de novo protein structure prediction algorithm, it must also determine an optimal crosslinker type and length for protein structure determination. While a longer crosslinker will yield more restraints, the value of each restraint for protein structure prediction decreases as the restraint is consistent with a larger conformational space. In this study, the number of crosslinks and their discriminative power was systematically analyzed in silico on a set of 2055 non-redundant protein folds considering Lys-Lys, Lys-Asp, Lys-Glu, Cys-Cys, and Arg-Arg reactive crosslinkers between 1 and 60Å. Depending on the protein size a heuristic was developed that determines the optimal crosslinker length. Next, simulated restraints of variable length were used to de novo predict the tertiary structure of fifteen proteins using the BCL::Fold algorithm. The results demonstrate that a distinct crosslinker length exists for which information content for de novo protein structure prediction is maximized. The sampling accuracy improves on average by 1.0 Å and up to 2.2 Å in the most prominent example. XL-MS restraints enable consistently an improved selection of native-like models with an average enrichment of 2.1.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.