Thorben Maass, Lorena Rudolph, Thomas Peters, Alvaro Mallagaray
{"title":"AMIGO - Guided assignment of 13C-methyl labelled proteins","authors":"Thorben Maass, Lorena Rudolph, Thomas Peters, Alvaro Mallagaray","doi":"10.1007/s10858-026-00491-4","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>Over the last 20 years, the number of large proteins accessible to protein-NMR analysis has increased significantly due to the development of selective [<sup>1</sup>H<sub>,</sub><sup>13</sup>C]-methyl labelling techniques in combination with methyl-TROSY based NMR experiments. Structure-based strategies for the assignment of [¹H,¹³C]-methyl groups rely on comparing spatial constraints derived from methyl–methyl NOEs to a known three-dimensional structure of the protein of interest. Cross peaks in methyl-TROSY spectra are assigned to specific methyl groups by matching methyl–methyl NOEs, as observed for example in 4D HMQC-NOESY-HMQC spectra, with distances derived from a structural model. This process is commonly referred to as a “methyl walk”. Here, we present AMIGO (Automated Methyl assignment via Iterative Graph Optimization), a novel assignment algorithm that formalises the intuitive methyl walk procedure by constructing graphs with nodes representing specific methyl groups and edges reflecting methyl-methyl NOEs or short methyl-methyl distances in a model. “Building blocks” consisting of nodes and edges are then generated to reconcile structure-based and NOE-based graphs. Assignments are achieved through permutation and concatenation of individual “building blocks” in a modular fashion, enabling efficient computation even for large proteins. Additional experimental restraints, such as paramagnetic relaxation enhancements (PREs) or pseudocontact shifts (PCSs), can be integrated to validate and extend the assignments. The performance of AMIGO was validated using 11 proteins that had previously been assigned and 32 NOE networks that had been generated synthetically.</p>\n </div>","PeriodicalId":613,"journal":{"name":"Journal of Biomolecular NMR","volume":"80 1","pages":""},"PeriodicalIF":1.9000,"publicationDate":"2026-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13070982/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Biomolecular NMR","FirstCategoryId":"99","ListUrlMain":"https://link.springer.com/article/10.1007/s10858-026-00491-4","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Over the last 20 years, the number of large proteins accessible to protein-NMR analysis has increased significantly due to the development of selective [1H,13C]-methyl labelling techniques in combination with methyl-TROSY based NMR experiments. Structure-based strategies for the assignment of [¹H,¹³C]-methyl groups rely on comparing spatial constraints derived from methyl–methyl NOEs to a known three-dimensional structure of the protein of interest. Cross peaks in methyl-TROSY spectra are assigned to specific methyl groups by matching methyl–methyl NOEs, as observed for example in 4D HMQC-NOESY-HMQC spectra, with distances derived from a structural model. This process is commonly referred to as a “methyl walk”. Here, we present AMIGO (Automated Methyl assignment via Iterative Graph Optimization), a novel assignment algorithm that formalises the intuitive methyl walk procedure by constructing graphs with nodes representing specific methyl groups and edges reflecting methyl-methyl NOEs or short methyl-methyl distances in a model. “Building blocks” consisting of nodes and edges are then generated to reconcile structure-based and NOE-based graphs. Assignments are achieved through permutation and concatenation of individual “building blocks” in a modular fashion, enabling efficient computation even for large proteins. Additional experimental restraints, such as paramagnetic relaxation enhancements (PREs) or pseudocontact shifts (PCSs), can be integrated to validate and extend the assignments. The performance of AMIGO was validated using 11 proteins that had previously been assigned and 32 NOE networks that had been generated synthetically.
期刊介绍:
The Journal of Biomolecular NMR provides a forum for publishing research on technical developments and innovative applications of nuclear magnetic resonance spectroscopy for the study of structure and dynamic properties of biopolymers in solution, liquid crystals, solids and mixed environments, e.g., attached to membranes. This may include:
Three-dimensional structure determination of biological macromolecules (polypeptides/proteins, DNA, RNA, oligosaccharides) by NMR.
New NMR techniques for studies of biological macromolecules.
Novel approaches to computer-aided automated analysis of multidimensional NMR spectra.
Computational methods for the structural interpretation of NMR data, including structure refinement.
Comparisons of structures determined by NMR with those obtained by other methods, e.g. by diffraction techniques with protein single crystals.
New techniques of sample preparation for NMR experiments (biosynthetic and chemical methods for isotope labeling, preparation of nutrients for biosynthetic isotope labeling, etc.). An NMR characterization of the products must be included.