The Ad‐MD method to calculate NMR shift including effects due to conformational dynamics: The ³¹P NMR shift in DNA

Abstract

A method for averaging of NMR parameters by molecular dynamics (MD) has been derived from the method of statistical averaging in MD snapshots, benchmarked and applied to structurally dynamic interpretation of the 31P NMR shift (δ31P) in DNA phosphates. The method employs adiabatic dependence of an NMR parameter on selected geometric parameter(s) that is weighted by MD‐calculated probability distribution(s) for the geometric parameter(s) (Ad‐MD method). The usage of Ad‐MD for polymers is computationally convenient when one pre‐calculated structural dependence of an NMR parameter is employed for all chemically equivalent units differing only in dynamic behavior. The Ad‐MD method is benchmarked against the statistical averaging method for δ31P in the model phosphates featuring distinctively different structures and dynamic behavior. The applicability of Ad‐MD is illustrated by calculating 31P NMR spectra in the Dickerson‐Drew DNA dodecamer. δ31P was calculated with the B3LYP/IGLO‐III/PCM(water) and the probability distributions for the torsion angles adjacent to the phosphorus atoms in the DNA phosphates were calculated using the OL15 force field.

Theory and computation of nuclear shielding

“…39 Corte ´s and Sarotti 40 predicted NMR parameters of oximes in order to study their E/Z configuration and analyzed the scope and limitations of the leading probabilistic methods. Sychrovsky ´et al 41 calculated the NMR parameters by weighted MD probability contributions (Ad-MD) for 31 P NMR shifts, including the effects due to conformational dynamics in DNA. A contribution from Sundholm and coworkers 42 concentrated on the impact of core electrons on the molecular magnetic response.…”

Systematic QM/MM Study for Predicting 31P NMR Chemical Shifts of Adenosine Nucleotides in Solution and Stages of ATP Hydrolysis in a Protein Environment

“…Furthermore, the QM-based prediction of NMR properties in nucleic acid phosphates can be challenging because phosphate groups represent structurally the most variable segment of nucleic acids . Several studies on nucleic acids , and proteins ,− have highlighted the importance of combining the QM-based prediction of chemical shifts with MM-MD simulations to account for conformational diversity and solvent effects. As mentioned above, NMR shift computations are further complicated by the poor description of phosphate structures by classical force fields.…”

Modeling solvent effects and convergence of 31P‐NMR shielding calculations with COBRAMM

“…Several solvation models have been proposed to better reproduce 31 P chemical shift of different compounds comprising both implicit, 40,[46][47][48] explicit, and mixed implicit-explicit models. 15,31,37,[49][50][51][52] Sklenář co-workers, 38,53 as well as Sychrovský coworkers, have highlighted the importance of sampling and averaging of conformation in phosphorus-containing compounds when explicit solvation is considered, employing classical molecular dynamics (MD)/DFT protocols. 31,37,52 Nevertheless, to the best of our knowledge, an investigation of effects detected by different solvation models, conformational sampling, convergence of the shielding, and especially the potential benefit of QM/MM optimization is not presented in the literature.…”

“…Although less intensively studied than other nuclei, phosphorus is a highly interesting element for the computational investigation of NMR parameters 36 . In fact, it is stable in nature as a 100% abundant isotope ( 31 P), it is widely present in organic, 15 bio‐organic 37,38 and organometallic compounds, 39,40 its chemical shift ranges within 1000 ppm ca., and its nuclear spin is I = 1/2, making the experimental recording of spectra very easy and fast. All these characteristics make 31 P‐NMR one of the most feasible techniques to study small structural changes in chemical processes 41,42 or following catalysts' behavior 43,44 .…”

“…Over the years, many studies have been separately reported on investigations of single effects on the computation of nuclear shielding, especially when solvent effects are employed. Several solvation models have been proposed to better reproduce 31 P chemical shift of different compounds comprising both implicit, 40,46–48 explicit, and mixed implicit‐explicit models 15,31,37,49–52 . Sklenář co‐workers, 38,53 as well as Sychrovský co‐workers, have highlighted the importance of sampling and averaging of conformation in phosphorus‐containing compounds when explicit solvation is considered, employing classical molecular dynamics (MD)/DFT protocols 31,37,52 .…”