Part VI: Computational & Systems Biophysics | Chapter 1

NMR Spectroscopy in Biophysics

Larmor precession, Bloch equations, chemical shifts, NOE distance constraints, and protein dynamics from relaxation analysis

Nuclear Magnetic Resonance: A Window into Molecular Structure and Dynamics

Nuclear magnetic resonance (NMR) spectroscopy exploits the magnetic properties of atomic nuclei to determine three-dimensional structures, characterize dynamics, and probe molecular interactions in solution. Unlike X-ray crystallography, NMR does not require crystals and can study proteins under near-physiological conditions. With over 14,000 NMR-derived structures in the Protein Data Bank, NMR is a cornerstone of structural biology alongside crystallography and cryo-EM.

The key NMR-active nuclei in biomolecules are $^1$H (spin-1/2, 99.98% natural abundance),$^{13}$C (spin-1/2, 1.1%), and $^{15}$N (spin-1/2, 0.37%). Isotopic enrichment with $^{13}$C and $^{15}$N is routine for protein NMR.

1. Nuclear Spin in a Magnetic Field

A nucleus with spin quantum number $I$ possesses a magnetic moment$\boldsymbol{\mu} = \gamma \hbar \mathbf{I}$, where $\gamma$ is the gyromagnetic ratio specific to each isotope. When placed in an external magnetic field$\mathbf{B}_0 = B_0 \hat{z}$, the spin interacts with the field via the Zeeman Hamiltonian.

Derivation: Larmor Frequency and Energy Splitting

The Zeeman Hamiltonian for a spin in a magnetic field is:

$$\hat{H} = -\boldsymbol{\mu} \cdot \mathbf{B}_0 = -\gamma \hbar \hat{I}_z B_0$$

For a spin-1/2 nucleus ($I = 1/2$), the allowed magnetic quantum numbers are$m_I = +1/2$ ($\alpha$ state) and $m_I = -1/2$($\beta$ state). The eigenvalues of $\hat{I}_z$ are$m_I \hbar$, so the energy levels are:

$$E_{m_I} = -\gamma \hbar m_I B_0$$

For the two states:

$$E_\alpha = -\frac{1}{2}\gamma \hbar B_0, \quad E_\beta = +\frac{1}{2}\gamma \hbar B_0$$

(assuming $\gamma > 0$, as for $^1$H). The energy splitting is:

$$\boxed{\Delta E = E_\beta - E_\alpha = \gamma \hbar B_0 = \hbar \omega_0}$$

where we identify the Larmor frequency:

$$\boxed{\omega_0 = \gamma B_0}$$

For $^1$H with $\gamma/2\pi = 42.576$ MHz/T and$B_0 = 14.1$ T (a 600 MHz spectrometer):

$$\nu_0 = \frac{\omega_0}{2\pi} = 42.576 \times 14.1 = 600.3 \text{ MHz}$$

The Boltzmann population difference at thermal equilibrium determines the net magnetization and thus the signal strength. At temperature $T$:

$$\frac{N_\alpha}{N_\beta} = \exp\left(\frac{\Delta E}{k_B T}\right) = \exp\left(\frac{\hbar \gamma B_0}{k_B T}\right)$$

Since $\hbar \gamma B_0 \ll k_B T$ at room temperature (for $^1$H at 14.1 T, $\Delta E / k_B T \approx 10^{-4}$), we expand the exponential:

$$\frac{N_\alpha - N_\beta}{N} \approx \frac{\hbar \gamma B_0}{2 k_B T}$$

This tiny population excess ($\sim 1$ in $10^5$) is what makes NMR inherently insensitive compared to optical spectroscopies, but also what makes it exquisitely sensitive to local electronic environments.

Classical Picture: Precession

Classically, the torque on the magnetic moment is $\boldsymbol{\tau} = \boldsymbol{\mu} \times \mathbf{B}_0$. Since $\boldsymbol{\tau} = d\mathbf{J}/dt = d(\hbar \mathbf{I})/dt$ and$\boldsymbol{\mu} = \gamma \hbar \mathbf{I}$:

$$\frac{d\boldsymbol{\mu}}{dt} = \gamma \boldsymbol{\mu} \times \mathbf{B}_0$$

This describes precession of $\boldsymbol{\mu}$ about $\mathbf{B}_0$at the Larmor frequency $\omega_0 = \gamma B_0$. The bulk magnetization$\mathbf{M} = \sum_i \boldsymbol{\mu}_i$ obeys the same equation, forming the basis for the Bloch equations.

2. Bloch Equations and Relaxation

Felix Bloch introduced phenomenological equations describing the time evolution of the bulk magnetization $\mathbf{M}$ in a magnetic field, incorporating relaxation processes that return the system to thermal equilibrium.

Derivation: The Bloch Equations

Starting from the equation of motion for the magnetization in a field $\mathbf{B}$:

$$\frac{d\mathbf{M}}{dt} = \gamma \mathbf{M} \times \mathbf{B}$$

Bloch added relaxation terms to account for the return to equilibrium. The longitudinal magnetization $M_z$ recovers toward the equilibrium value $M_0$with time constant $T_1$ (spin-lattice relaxation), while the transverse components $M_x, M_y$ decay to zero with time constant $T_2$(spin-spin relaxation):

$$\frac{dM_x}{dt} = \gamma(\mathbf{M} \times \mathbf{B})_x - \frac{M_x}{T_2}$$

$$\frac{dM_y}{dt} = \gamma(\mathbf{M} \times \mathbf{B})_y - \frac{M_y}{T_2}$$

$$\frac{dM_z}{dt} = \gamma(\mathbf{M} \times \mathbf{B})_z - \frac{M_z - M_0}{T_1}$$

$T_1$ relaxation (spin-lattice): Energy exchange between nuclear spins and the surrounding "lattice" (molecular tumbling, vibrations). After a perturbation (e.g., 180° pulse), $M_z$ recovers exponentially:

$$M_z(t) = M_0\left(1 - 2e^{-t/T_1}\right)$$

$T_2$ relaxation (spin-spin): Loss of phase coherence among precessing spins due to local field inhomogeneities. After a 90° pulse creating transverse magnetization:

$$M_{xy}(t) = M_0 e^{-t/T_2}$$

The relationship $T_2 \leq T_1$ always holds. For small molecules in solution,$T_1 \approx T_2 \sim 1\text{--}10$ s, while for large proteins,$T_2$ can be much shorter ($\sim 10\text{--}100$ ms) than $T_1$.

Derivation: Free Induction Decay and Fourier Transform

After a 90° pulse tips $M_z$ into the transverse plane, the precessing magnetization induces a signal in the receiver coil. In the rotating frame at the carrier frequency $\omega_{rf}$, the complex transverse magnetization for a single resonance at offset $\Omega = \omega_0 - \omega_{rf}$ is:

$$M^+(t) = M_x(t) + iM_y(t) = M_0 e^{i\Omega t} e^{-t/T_2}, \quad t \geq 0$$

This is the free induction decay (FID). The NMR spectrum is obtained by Fourier transformation:

$$S(\omega) = \int_0^\infty M^+(t) e^{-i\omega t}\, dt = \int_0^\infty M_0 e^{i(\Omega - \omega)t} e^{-t/T_2}\, dt$$

Evaluating the integral:

$$S(\omega) = M_0 \left[\frac{-1}{i(\Omega - \omega) - 1/T_2}\right]_0^\infty = \frac{M_0}{1/T_2 - i(\Omega - \omega)}$$

Separating real and imaginary parts:

$$\text{Re}[S(\omega)] = \frac{M_0 / T_2}{(1/T_2)^2 + (\Omega - \omega)^2} \quad \text{(absorption Lorentzian)}$$

$$\text{Im}[S(\omega)] = \frac{M_0 (\Omega - \omega)}{(1/T_2)^2 + (\Omega - \omega)^2} \quad \text{(dispersion Lorentzian)}$$

The absorption lineshape is a Lorentzian centered at $\omega = \Omega$ with full width at half maximum $\Delta\omega_{1/2} = 2/T_2$, or in Hz,$\Delta\nu_{1/2} = 1/(\pi T_2)$. Longer $T_2$ gives narrower lines.

NMR: FID, Fourier Transform, and Relaxation Simulations

Python
script.py96 lines

Click Run to execute the Python code

Code will be executed with Python 3 on the server

3. Chemical Shift and Multidimensional NMR

The resonance frequency of a nucleus depends on its local electronic environment. Electrons surrounding the nucleus generate small magnetic fields that partially shield it from$B_0$, causing nuclei in different chemical environments to resonate at slightly different frequencies.

Derivation: Chemical Shift from Electron Shielding

The local field experienced by a nucleus is modified by the shielding tensor $\boldsymbol{\sigma}$:

$$\mathbf{B}_{\text{local}} = (1 - \sigma)\mathbf{B}_0$$

where $\sigma$ is the isotropic shielding constant (typically $10^{-6}$ to$10^{-4}$ for $^1$H). The resonance frequency becomes:

$$\boxed{\omega = \gamma B_0(1 - \sigma)}$$

Rather than reporting absolute frequencies, chemists use the chemical shift$\delta$ relative to a reference compound (TMS for $^1$H and $^{13}$C):

$$\delta = \frac{\omega - \omega_{\text{ref}}}{\omega_{\text{ref}}} \times 10^6 = \frac{\sigma_{\text{ref}} - \sigma}{1 - \sigma_{\text{ref}}} \times 10^6 \approx (\sigma_{\text{ref}} - \sigma) \times 10^6 \text{ (ppm)}$$

Sources of shielding in proteins:

  • Diamagnetic shielding: Circulation of electrons in the ground state around the nucleus, proportional to electron density
  • Paramagnetic shielding: Involves excited electronic states; dominant for $^{13}$C and $^{15}$N
  • Ring current effects: The delocalized $\pi$electrons in aromatic rings (Phe, Tyr, Trp, His) create a ring current that generates an induced magnetic field. Nuclei above/below the ring are shielded (upfield shift), while those in the plane are deshielded (downfield shift). The ring current shift is:$$\Delta\delta \propto \frac{1 - 3\cos^2\theta}{r^3}$$where $r$ and $\theta$ are the distance and angle from the ring center
  • Hydrogen bonding: Deshields the bonded proton; the amide$^1$H chemical shift correlates with H-bond length in proteins

Typical protein chemical shift ranges: Backbone amide $^1$H: 6–10 ppm; $^1$H$\alpha$: 3–5 ppm; methyl $^1$H: 0–1 ppm; $^{13}$C$\alpha$: 45–65 ppm;$^{15}$N amide: 100–135 ppm.

Multidimensional NMR Pulse Sequences

COSY (COrrelation SpectroscopY): Detects through-bond (J-coupling) correlations between nuclei. A simple two-pulse sequence (90°–$t_1$–90°–$t_2$) produces cross-peaks connecting J-coupled nuclei. The cross-peak intensity depends on$\sin(\pi J t_1)$, where $J$ is the coupling constant.

NOESY (Nuclear Overhauser Effect SpectroscopY): Detects through-space correlations via dipolar cross-relaxation. The mixing time $\tau_m$allows magnetization transfer between nuclei close in space ($< 5$ Å). Cross-peak intensity is proportional to $1/r^6$.

HSQC (Heteronuclear Single-Quantum Coherence): Correlates$^1$H with a directly bonded heteronucleus ($^{15}$N or $^{13}$C). The $^{15}$N-HSQC spectrum serves as the "fingerprint" of a protein, with one peak per backbone amide. For a well-folded protein of $N$ residues, expect approximately $N - 1$ peaks (minus prolines, which lack amide NH).

Triple-resonance experiments: For backbone assignment, experiments like HNCA, HN(CO)CA, HNCO, CBCA(CO)NH correlate amide $^1$H-$^{15}$N with $^{13}$C$\alpha$, $^{13}$C$\beta$, and$^{13}$CO of the same and preceding residues, enabling sequential assignment.

4. Nuclear Overhauser Effect and Distance Constraints

The Nuclear Overhauser Effect (NOE) is the change in intensity of one NMR signal when the equilibrium population of a nearby spin is perturbed. It arises from dipolar cross-relaxation between nuclear spins and provides distance information critical for structure determination.

Derivation: NOE and the Solomon Equations

Consider a two-spin system (spins I and S) with dipolar coupling. The Solomon equations describe the time evolution of the longitudinal magnetizations:

$$\frac{dI_z}{dt} = -\rho_I (I_z - I_0) - \sigma_{IS}(S_z - S_0)$$

$$\frac{dS_z}{dt} = -\sigma_{IS}(I_z - I_0) - \rho_S (S_z - S_0)$$

where $\rho_I, \rho_S$ are the auto-relaxation rates and $\sigma_{IS}$ is the cross-relaxation rate. The dipolar relaxation rates depend on the internuclear distance$r$ and the rotational correlation time $\tau_c$:

$$\sigma_{IS} = \frac{1}{10}\left(\frac{\mu_0}{4\pi}\right)^2 \frac{\gamma_I^2 \gamma_S^2 \hbar^2}{r^6} \left[6J(2\omega_0) - J(0)\right]$$

where the spectral density function for isotropic tumbling is:

$$J(\omega) = \frac{2}{5} \frac{\tau_c}{1 + \omega^2 \tau_c^2}$$

The steady-state NOE enhancement when spin S is saturated is:

$$\eta = \frac{I_z - I_0}{I_0} = \frac{\sigma_{IS}}{\rho_I} \cdot \frac{\gamma_S}{\gamma_I}$$

The critical distance dependence:

$$\boxed{\sigma_{IS} \propto \frac{1}{r^6}}$$

This steep distance dependence means that NOE is essentially a short-range effect: observable only for proton pairs within $\sim 5$ Å. The NOE changes sign depending on molecular size: positive for small molecules ($\omega_0\tau_c \ll 1$), zero at$\omega_0\tau_c \approx 1.12$, and negative for large molecules ($\omega_0\tau_c \gg 1$).

Initial rate approximation: For short mixing times$\tau_m$, the NOE buildup is linear:

$$\text{NOE}(I \leftarrow S) \approx \sigma_{IS} \tau_m \propto \frac{\tau_m}{r_{IS}^6}$$

Structure determination: In a NOESY spectrum, cross-peak volumes are proportional to $1/r^6$. By calibrating against a known distance (e.g., geminal CH$_2$ protons at 1.78 Å), distances are extracted:$r_{ij} = r_{\text{ref}}(V_{\text{ref}}/V_{ij})^{1/6}$. These serve as upper bound distance restraints for structure calculation by simulated annealing or distance geometry.

NOE Distance Dependence and Structure Determination

Python
script.py100 lines

Click Run to execute the Python code

Code will be executed with Python 3 on the server

5. Protein Dynamics from NMR Relaxation

NMR relaxation measurements ($T_1$, $T_2$, and heteronuclear NOE) provide site-specific information about molecular dynamics on timescales from picoseconds to milliseconds. The Lipari-Szabo model-free formalism provides a framework for interpreting these data.

Derivation: Lipari-Szabo Model-Free Analysis

The relaxation of a $^{15}$N nucleus is dominated by the dipolar interaction with the directly bonded $^1$H and the $^{15}$N chemical shift anisotropy (CSA). The relaxation rates are expressed in terms of spectral density functions:

$$\frac{1}{T_1} = \frac{d^2}{4}\left[J(\omega_H - \omega_N) + 3J(\omega_N) + 6J(\omega_H + \omega_N)\right] + c^2 J(\omega_N)$$

$$\frac{1}{T_2} = \frac{d^2}{8}\left[4J(0) + J(\omega_H - \omega_N) + 3J(\omega_N) + 6J(\omega_H) + 6J(\omega_H + \omega_N)\right] + \frac{c^2}{6}\left[4J(0) + 3J(\omega_N)\right]$$

$$\text{NOE} = 1 + \frac{d^2}{4T_1}\frac{\gamma_H}{\gamma_N}\left[6J(\omega_H + \omega_N) - J(\omega_H - \omega_N)\right]$$

where $d = (\mu_0/4\pi)\gamma_H\gamma_N\hbar/r_{NH}^3$ (dipolar coupling constant) and $c = \omega_N \Delta\sigma / \sqrt{3}$ (CSA contribution).

The Lipari-Szabo model-free spectral density: Rather than assuming a specific motional model, Lipari and Szabo (1982) showed that the spectral density can be approximated as:

$$\boxed{J(\omega) = \frac{2}{5}\left[\frac{S^2 \tau_m}{1 + \omega^2\tau_m^2} + \frac{(1-S^2)\tau}{1 + \omega^2\tau^2}\right]}$$

where $1/\tau = 1/\tau_m + 1/\tau_e$, and:

  • $\tau_m$ is the overall rotational correlation time of the molecule
  • $S^2$ is the generalized order parameter($0 \leq S^2 \leq 1$), measuring the spatial restriction of the internal motion.$S^2 = 1$ means completely rigid; $S^2 = 0$ means unrestricted motion
  • $\tau_e$ is the effective internal correlation time for fast motions

Physical interpretation of $S^2$: For a bond vector confined to a cone of semi-angle $\theta$:

$$S^2 = \left[\frac{\cos\theta(1 + \cos\theta)}{2}\right]^2$$

Typical values: backbone amide N-H in structured regions: $S^2 \approx 0.85\text{--}0.90$; in flexible loops: $S^2 \approx 0.5\text{--}0.7$; in disordered termini:$S^2 < 0.4$.

Extracting $\tau_m$: The overall tumbling time can be estimated from the $T_1/T_2$ ratio. For backbone amides in structured regions (where $S^2$ is similar), $T_1/T_2$ is approximately constant and depends primarily on $\tau_m$:

$$\frac{T_1}{T_2} \approx \frac{6J(\omega_N)}{4J(0) + 3J(\omega_N)} \xrightarrow{\omega_N\tau_m \gg 1} \frac{3}{2}\omega_N^2\tau_m^2$$

The Stokes-Einstein relation predicts $\tau_m = 4\pi\eta r_H^3 / (3k_BT)$, giving approximately $\tau_m \approx 0.5$ ns per kDa for globular proteins at 25°C in water.

Lipari-Szabo Model-Free Analysis of Protein Dynamics

Python
script.py118 lines

Click Run to execute the Python code

Code will be executed with Python 3 on the server

6. Applications of NMR in Biophysics

Protein Structure Determination

NMR structure determination uses NOE-derived distance restraints, dihedral angle restraints from chemical shifts (TALOS) and J-couplings, hydrogen bond restraints, and residual dipolar couplings (RDCs) for orientational information. An ensemble of 10–20 structures is calculated by simulated annealing. Over 14,000 NMR structures are deposited in the PDB, typically for proteins up to $\sim 30$ kDa, though TROSY-based methods extend this to $> 100$ kDa.

SAR by NMR (Drug Discovery)

Structure-Activity Relationships by NMR, developed by Fesik and colleagues at Abbott, uses$^{15}$N-HSQC chemical shift perturbations to identify small molecules that bind to a target protein and determine the binding site. Fragment-based drug discovery links weak-binding fragments identified by NMR into potent leads. Venetoclax (Bcl-2 inhibitor), approved for CLL treatment, was discovered using SAR-by-NMR.

Metabolomics and In-Cell NMR

$^1$H NMR provides quantitative metabolic profiles of biofluids (blood, urine, CSF) without separation. Each metabolite produces characteristic peaks, enabling simultaneous detection of hundreds of metabolites. In-cell NMR introduces isotope-labeled proteins into living cells (by electroporation, microinjection, or overexpression) to study protein behavior in the native cellular environment, including the effects of macromolecular crowding and post-translational modifications.

Chapter Summary

  • Larmor frequency $\omega_0 = \gamma B_0$ sets the resonance condition; the population difference $\propto \hbar\gamma B_0 / (2k_BT)$ governs sensitivity.
  • • The Bloch equations describe magnetization evolution with $T_1$ (longitudinal recovery) and $T_2$ (transverse decay) relaxation.
  • Chemical shifts arise from electron shielding ($\omega = \gamma B_0(1-\sigma)$) and provide site-specific structural information.
  • • The NOE ($\propto 1/r^6$) provides distance constraints for structure determination via the Solomon equations.
  • • The Lipari-Szabo model-free analysis extracts order parameters $S^2$ and internal correlation times $\tau_e$ from relaxation data.
  • • Applications span protein structure determination, fragment-based drug discovery, metabolomics, and in-cell NMR.
Rate this chapter: