Toward the Quantum Chemical Calculation of NMR Chemical Shifts of Proteins. 3. Conformational Sampling and Explicit Solvents Model

Abstract

Fragment-based quantum chemical calculations are able to accurately calculate NMR chemical shifts even for very large molecules like proteins. But even with systematic optimization of the level of theory and basis sets as well as the use of implicit solvents models, some nuclei like polar protons and nitrogens suffer from poor predictions. Two properties of the real system, strongly influencing the experimental chemical shifts but almost always neglected in the calculations, will be discussed here in great detail: (1) conformational averaging and (2) interactions with first-shell solvent molecules. Classical molecular dynamics simulations in explicit water were carried out for obtaining a representative ensemble including the arrangement of neighboring solvent molecules, which was then subjected to quantum chemical calculations. We could demonstrate with the small test system N-methyl acetamide (NMA) that the calculated chemical shifts show immense variations of up to 6 ppm and 50 ppm for protons and nitrogens, respectively, depending on the snapshot taken from a classical molecular dynamics simulation. Applying the same approach to the HA2 domain of the influenza virus glycoprotein hemagglutinin, a 32-amino-acid-long polypeptide, and comparing averaged values to the experiment, chemical shifts of nonpolar protons and carbon atoms in proteins were calculated with unprecedented accuracy. Additionally, the mean absolute error could be reduced by a factor of 2.43 for polar protons, and reasonable correlations were obtained for nitrogen and carbonyl carbon in contrast to all other studies published so far.

ProCS15: A DFT-based chemical shift predictor for backbone and C β atoms in proteins

“…These accuracies are very similar to DFT-based predictions made by other researchers (e.g. (Zhu et al, 2012), (Zhu et al, 2013), (Exner et al, 2012)) as well as CheShift-2 (Martin et al, 2013), which is another DFT-based chemical shift predictor for Cα and Cβ atoms. The RMSD values computed using ProCS15 for Ubiquitin can be reduced by as much as 0.7, 0.1, and 0.5 ppm for carbon, hydrogen, and nitrogen by using NMR-derived structural ensembles.…”

“…For example, Zhu, He and Zhang (Zhu et al, 2012) used B3LYP/6-31G(d,p) to compute hydrogen and carbon chemical shifts for small proteins that correlate well with experimental measurements with r values typically ≥ 0.98 when solvent effects are taken into account. Exner, Möller, and co-workers (Exner et al, 2012) have obtained similar results using B3LYP/6-31G(d) and even observed a correlation of 0.81 for the notoriously difficult amide N by averaging over several snapshots. Finally, Vila, Baldoni and Scheraga (Vila et al, 2009b) on Cα chemical shifts in Ubiquitin and found very little difference in performance with all r and RMSD values in the range 0.902 -0.908 and 2.12 -2.30 ppm.…”

“…In a later study (Zhu et al, 2013), the same researchers reproduced the chemical shifts of amide protons in GB3 to within 0.5 ppm using a locally dense 6-31++G(d,p)/4-31G(d) basis set and a variety of functionals including OPBE. Similarly, Exner and co-workers (Exner et al, 2012) used B3LYP/6-31G(d)//AMBER and an implicit solvent model to reproduce the H N chemical shifts of the HA2 Domain to within 0.5 ppm using a single structure and 0.3 pm using several MD snapshots.…”

“…The agreement with experiment is quite remarkable with RMSD values around 1, 0.3, and 2 ppm for carbon, hydrogen, and nitrogen atoms. Chemical shift predictions based on quantum mechanical (QM) calculations (mostly density functional theory, DFT) are becoming increasingly feasible for small proteins (Zhu et al, 2012(Zhu et al, , 2013Exner et al, 2012;Sumowski et al, 2014;Swails et al, 2015) and Vila, Scheraga and co-workers have gone on to develop a DFT-based chemical shift predictor for Cα and Cβ atoms called CheShift-2 (Martin et al, 2013). Generally, these QM-based methods yield chemical shifts that deviate significantly more from experiment than the empirical methods, with RMSD values that generally are at least twice as large.…”

MoD-QM/MM Structural Refinement Method: Characterization of Hydrogen Bonding in the Oxytricha nova G-Quadruplex

“…For reliable comparisons of NMR chemical shifts, it is important to consider the influence of explicit solvent molecules and counterions. 123–125 In this work, solvated configurations were sampled by using NPT explicit solvent molecular dynamics (see Computational Details). After equilibration, snapshots were randomly sampled from a 2 ns trajectory, including all water molecules and counterions within 20 Å of the center of the guanine quadruplex.…”