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

Abstract

We present ProCS15: A program that computes the isotropic chemical shielding values of backbone and C β atoms given a protein structure in less than a second. ProCS15 is based on around 2.35 million OPBE/6-31G(d,p)//PM6 calculations on tripeptides and small structural models of hydrogen-bonding. The ProCS15-predicted chemical shielding values are compared to experimentally measured chemical shifts for Ubiquitin and the third IgG-binding domain of Protein G through linear regression and yield RMSD values of up to 2.2, 0.7, and 4.8 ppm for carbon, hydrogen, and nitrogen atoms. These RMSD values are very similar to corresponding RMSD values computed using OPBE/6-31G(d,p) for the entire structure for each proteins. These maximum RMSD values can be reduced by using NMR-derived structural ensembles of Ubiquitin. For example, for the largest ensemble the largest RMSD values are 1.7, 0.5, and 3.5 ppm for carbon, hydrogen, and nitrogen. The corresponding RMSD values predicted by several empirical chemical shift predictors range between 0.7 - 1.1, 0.2 - 0.4, and 1.8 - 2.8 ppm for carbon, hydrogen, and nitrogen atoms, respectively.

Modeling pH-Dependent NMR Chemical Shift Perturbations in Peptides

“…In the aspartic acid tripeptide (Fig. 3 A), the computed deshielding is most evident in the 13 Cb, 13 Cg, and 13 CO nuclei, which have a downfield…”

“…3 and Table 1. At first glance, it is evident that the computed 13 C perturbations are significant, ranging from À2.5 to 7.5 ppm. As expected, the largest CSPs are observed in the carbon atoms near the (de)protonation site and generally all atoms in the titratable group.…”

“…shift of 6.9, 2.4, and 3.2 ppm, respectively. The large perturbations in the backbone 13 Ca (3.5 ppm) and side-chain 13 Cb (6.9 ppm) atoms suggest notable differences in the secondary structures (3,48) of the deprotonated and protonated tripeptide forms. These results mirror the Ramachandran plots in Fig.…”

“…Nevertheless, both experimental and computational studies of model peptides have enabled a greater understanding of the relationship between chemical shifts and physical attributes of the peptides and their environments (3)(4)(5)(6). In combination with classical descriptions of chemical phenomena (7)(8)(9)(10), empirical observations have been used to inform highly accurate chemical shift prediction programs (11)(12)(13)(14)(15). In addition, many popular predictors also employ machine-learning algorithms and are trained with large databases of chemical shifts obtained either from experimental NMR data repositories (11,13,14), such as the Biological Magnetic Resonance Bank (16), or through numerous quantum mechanical calculations (13,15,17).…”

“…It has been demonstrated that nuclei on the titratable residue exhibit prominent CSPs and serve as reporters for pK a determination in NMR titration experiments (18,21). In a bioinformatics survey of the existing NMR pH titration data sets deposited in the Biological Magnetic Resonance Bank, Farrell et al (21) report significant CSPs (0.1-0.9 ppm: 1 H; 0.7-2.9 ppm: 15 N; and 1.2-3.7 ppm: 13 C) associated with model pK a values.…”