Backbone-independent NMR resonance assignments of methyl probes in large proteins
| Autor: | Viviane S. De Paula, Nikolaos G. Sgourakis, Santrupti Nerli, Andrew C. McShan |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Models
Molecular Streptococcus pyogenes Science General Physics and Astronomy Nuclear Overhauser effect Tritium 010402 general chemistry 01 natural sciences Article General Biochemistry Genetics and Molecular Biology 03 medical and health sciences Protein Domains CRISPR-Associated Protein 9 Nuclear Magnetic Resonance Biomolecular 030304 developmental biology Physics Carbon Isotopes 0303 health sciences Multidisciplinary Resonance General Chemistry Recombinant Proteins 0104 chemical sciences Isotope Labeling Interleukin-2 Structural biology Biological system Solution-state NMR Software Algorithms |
| Zdroj: | Nature Communications, Vol 12, Iss 1, Pp 1-13 (2021) Nature Communications |
| ISSN: | 2041-1723 |
| Popis: | Methyl-specific isotope labeling is a powerful tool to study the structure, dynamics and interactions of large proteins and protein complexes by solution-state NMR. However, widespread applications of this methodology have been limited by challenges in obtaining confident resonance assignments. Here, we present Methyl Assignments Using Satisfiability (MAUS), leveraging Nuclear Overhauser Effect cross-peak data, peak residue type classification and a known 3D structure or structural model to provide robust resonance assignments consistent with all the experimental inputs. Using data recorded for targets with known assignments in the 10–45 kDa size range, MAUS outperforms existing methods by up to 25,000 times in speed while maintaining 100% accuracy. We derive de novo assignments for multiple Cas9 nuclease domains, demonstrating that the methyl resonances of multi-domain proteins can be assigned accurately in a matter of days, while reducing biases introduced by manual pre-processing of the raw NOE data. MAUS is available through an online web-server. Here, the authors present Methyl Assignments Using Satisfiability (MAUS), a method for the assignment of methyl groups using raw NOE data. They use eight proteins in the 10–45 kDa size range as test cases and show that MAUS yields 100% accurate assignments at high completeness levels. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|