Literature DB >> 26605634

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

Thomas E Exner1,2, Andrea Frank1, Ionut Onila2, Heiko M Möller1.   

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.

Entities:  

Year:  2012        PMID: 26605634     DOI: 10.1021/ct300701m

Source DB:  PubMed          Journal:  J Chem Theory Comput        ISSN: 1549-9618            Impact factor:   6.006


  11 in total

1.  Benchmark fragment-based (1)H, (13)C, (15)N and (17)O chemical shift predictions in molecular crystals.

Authors:  Joshua D Hartman; Ryan A Kudla; Graeme M Day; Leonard J Mueller; Gregory J O Beran
Journal:  Phys Chem Chem Phys       Date:  2016-07-19       Impact factor: 3.676

2.  Automated assignment of NMR chemical shifts based on a known structure and 4D spectra.

Authors:  Matthias Trautwein; Kai Fredriksson; Heiko M Möller; Thomas E Exner
Journal:  J Biomol NMR       Date:  2016-08-02       Impact factor: 2.835

Review 3.  Using quantum chemistry to estimate chemical shifts in biomolecules.

Authors:  David A Case
Journal:  Biophys Chem       Date:  2020-09-16       Impact factor: 2.352

4.  Accurate ab initio prediction of NMR chemical shifts of nucleic acids and nucleic acids/protein complexes.

Authors:  Andrea Victora; Heiko M Möller; Thomas E Exner
Journal:  Nucleic Acids Res       Date:  2014-11-17       Impact factor: 16.971

5.  Modeling pH-Dependent NMR Chemical Shift Perturbations in Peptides.

Authors:  Efrosini Artikis; Charles L Brooks
Journal:  Biophys J       Date:  2019-06-12       Impact factor: 4.033

6.  AFNMR: automated fragmentation quantum mechanical calculation of NMR chemical shifts for biomolecules.

Authors:  Jason Swails; Tong Zhu; Xiao He; David A Case
Journal:  J Biomol NMR       Date:  2015-08-02       Impact factor: 2.835

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

Authors:  Junming Ho; Michael B Newcomer; Christina M Ragain; Jose A Gascon; Enrique R Batista; J Patrick Loria; Victor S Batista
Journal:  J Chem Theory Comput       Date:  2014-10-08       Impact factor: 6.006

8.  Can quantum-chemical NMR chemical shifts be used as criterion for force-field development.

Authors:  Thomas E Exner; Andrea Frank; Heiko M Möller; Martin Dračínský
Journal:  J Cheminform       Date:  2014-03-11       Impact factor: 5.514

9.  ProCS15: a DFT-based chemical shift predictor for backbone and Cβ atoms in proteins.

Authors:  Anders S Larsen; Lars A Bratholm; Anders S Christensen; Maher Channir; Jan H Jensen
Journal:  PeerJ       Date:  2015-10-20       Impact factor: 2.984

10.  Protein structure refinement using a quantum mechanics-based chemical shielding predictor.

Authors:  Lars A Bratholm; Jan H Jensen
Journal:  Chem Sci       Date:  2016-12-01       Impact factor: 9.825

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