the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 09 Apr 2024
Analysis of chi angle distributions in isolated amino acids via multiplet fitting of proton scalar couplings
Abstract. Scalar couplings are a fundamental aspect of nuclear magnetic resonance (NMR) experiments and provide rich information about electron-mediated interactions between nuclei. 3J couplings are particularly useful for determining molecular structure through the Karplus relationship, a mathematical formula used for calculating 3J coupling constants from dihedral angles. In small molecules, scalar couplings are often determined through analysis of one-dimensional proton spectra. Larger proteins have typically required specialized multidimensional pulse programs designed to overcome spectral crowding and multiplet complexity. Here we present a generalized framework for fitting scalar couplings with arbitrarily complex multiplet patterns using a weak coupling model. The method is implemented in FitNMR and applicable to 1D, 2D, and 3D NMR spectra. To gain insight into the proton-proton coupling patterns present in protein side chains, we analyze a set of isolated amino acid 1D spectra. We show that the weak-coupling assumption is largely sufficient for fitting the majority of resonances, although there are notable exceptions. To enable structural interpretation of all couplings, we extend a self-consistent Karplus parameterization of side chain chi 1 to chi 2–4. An enhanced model of side chain motion incorporating rotamer statistics from the Protein Data Bank (PDB) is developed. Even without stereospecific assignments of the beta hydrogens, we find that two couplings are sufficient to exclude a single-rotamer model for all amino acids except proline. While most isolated amino acids show rotameric populations consistent with crystal structure statistics, beta-branched valine and isoleucine deviate substantially.
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CC1: 'Comment on mr-2024-7', Gottfried Otting, 10 Apr 2024
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The article reports 3JHH couplings for the side chains of free amino acids in D2O. In the absence of a polypeptide backbone, the agreement with the predictions based on crystal structures of proteins and peptides should be best for the nuclei furthest from the backbone. Is this so? Most crystal structures are determined at cryogenic temperatures, which favour the single lowest energy conformation. Do the current data (which were recorded at which temperature?) indicate more equal populations of different rotamers?
To compare with couplings determined in peptides: how good is the agreement with the ones reported by Bundi and Wüthrich in Biopolymers 18, 285 (1979)?
In my experience, the greatest headache with J-coupling measurements in larger proteins arises from the line broadening due to faster transverse relaxation, which collapses multiplets into unresolved fine structure. It would be very interesting to get an impression for how well the fitting algorithm can cope with significantly broader lines. Table 2 suggests that all multiplet components were narrower than 1 Hz, which is not realistic even for small proteins.
Citation: https://doi.org/10.5194/mr-2024-7-CC1 -
RC1: 'Comment on mr-2024-7', Anonymous Referee #1, 15 Apr 2024
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The manuscript reports measurements of JHH couplings in sidechains of free amino acids. The authors show that for most residues these values are incompatible with a single rotamer, even when including fluctuations of adjustable amplitudes around the average chi-angle. They show that for many, but not all, residues the JHH couplings appear in reasonable agreement with rotamer distributions taken from the Dunbrack database of sidechain conformations of high-resolution protein crystal structures. Although technically the work appears fine, its level of novelty and utility to the general community appears limited in view of prior work, that the authors are probably unaware of (just a few are listed in my comments below).
Two items that could substantially increase the value of this study:
- A Table with all the JHH values that were measured with their procedure.
- The stereospecific assignments presumably are known from Kainosho’s SAIL preparations https://doi.org/10.1017/S0033583510000016 . Not sure whether they actually published these, but I expect he will be happy to share. Alternatively, with the chemical shifts and J couplings being very similar to what they are in short peptides, it should be possible to get these assignments for at least some of the residues from a combination of NOE and JHH values, or from 3JHC and 3JHH values in the isolated amino acids
The analysis relies extensively on a Karplus equation with the simplified Perez substitution values, but it may be worth checking whether better agreement can be obtained with the original, very extensively researched substituent values of Haasnoot and Altona (see the 4 papers cited by Perez in their ref.36).
Other than the two methods investigated by the current authors, they may also wish to consider Markley’s CUPID method https://doi.org/10.1021/ja00041a044 and consider what others have found regarding sidechain rotamer populations and rotamer skewing: https://doi.org/10.1021/ja010595d and https://doi.org/10.1021/jacs.5b10072
Interpretation of amino acid sidechain J HH couplings in terms of rotamer distributions spans work from over at least 6 decades, with some of the first analyses that I’m aware of by Pachler (Pachler: SpectrochimicaActa, 1963,Vol.19, pp. 2085 to 2092)
Minor issues:
- Table 3: clarify how you identified the negative sign of J(HG12-HG13)
- 2: Include the fitted J values as an SI table
- Line 191: clarify what you mean with “arises due to the strong coupling network”. Isn’t this simply due to the 4-bond HD1-HD2 coupling for cases where HE1 and HE2 have different spin states, and similarly for HE1-HE2 J coupling for cases where HD1 and HD2 have different spin states. 5J(HE-HD) would simply be in the weak coupling limit and yield a small symmetric splitting of each of the doublet components that appears unresolved in the spectra shown.
- The legend to Fig. 3 is a bit confusing. It says: “The dihedral angles governing 3J(HB2-HG2) and 3J(HB3-HG3) have the same Δχ” but since you don’t have stereo assignments, how do you deal with this. It’s also strange to see the bold HB-HG J values to be so different for Lys and Arg. See also line 230. Something must be amiss in the interpretation of the data when concluding a gauche chi2 angle for the free amino acid. Steric clashing is expected to lower this population.
- Can the large difference between J(HA-HB2) and J(HA-HB3) be used for stereo assignment of the two resonances?
- Line 213-215: Perhaps try the Haasnoot values?
- Line 284: list the values you found for 3J(HA-HB) for Val and Ile when discussing the issue
- Line 302: “where such 2J couplings are also involved in 3J couplings” Poor phrasing
- Line 309-311: this proposes to do what Altona&Haasnoot did successfully some 40 years ago
Typo/style errors:
Line 67: set scalar > set of scalar
Line 92: could be made linear combinations ?
Line 129: by set of ?
Line 294: amio --> amino
Line 325: that size are computationally
Citation: https://doi.org/10.5194/mr-2024-7-RC1 -
RC2: 'Comment on mr-2024-7', Anonymous Referee #2, 26 Apr 2024
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The authors use measurement of sidechain 3JHH couplings from isolated amino acids to inform the analysis of sidechain rotamers in proteins.
The authors first present a workflow for fitting 1D 1H spectra to extract 3JHH couplings using the previously described lineshape fitting program FitNMR, and apply this method to measurements of sidechain couplings in all 20 isolated amino acids, each isolated in in D2O without the context of a polypeptide. The measured coupling values are then analyzed in terms of Karplus curves for sidechain rotamers. The authors extend the previous work of Pérez et al., who proposed a model “M1” that accounts for fluctuations about a single chi angle, and a model “M2” that describes couplings in terms of populations of three canonical chi angles. The authors introduce a new model “M3” that calculates couplings in terms of empirically derived rotamer distributions, and using this model, the authors suggest that measurement of two sidechain 3JHH couplings is sufficient to decide whether a given sidechain populates more than one rotamer.
The couplings are extracted using a weak coupling model, and the authors nicely illustrate the J fitting results for all of the amino acids, highlighting the cases where strong coupling causes deviations from the model. The extracted couplings for the isolated amino acids agree well with rotamer populations from folded proteins, with some exceptions, in particular valine and isoleucine. It is not unexpected that rotamer populations of non-polar sidechains would be different for an isolated amino acid in water compared to an amino acid in the context of a hydrophobic core.
The fitting method and rotamer models are sound, and, while there is long history of coupling analysis, the combination of use of isolated amino acids, fitting approach, and models for 3JHH of rotamer populations is novel. This method will be of interest to the community, subject to the constraint that these coupling values can be hard to measure for larger proteins.
Citation: https://doi.org/10.5194/mr-2024-7-RC2
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