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

2015 ◽  
Author(s):  
Anders S Larsen ◽  
Lars A Bratholm ◽  
Anders S Christensen ◽  
Maher Jan Channir ◽  
Jan H. Jensen
Keyword(s):  
Hydrogen Bonding ◽  
Chemical Shift ◽  
Chemical Shifts ◽  
Structural Models ◽  
Protein G ◽  
Chemical Shielding ◽  
The Third ◽  
Entire Structure ◽  
Igg Binding ◽  
Structural Ensembles

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.

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

2015 ◽  
Author(s):  
Anders S Larsen ◽  
Lars A Bratholm ◽  
Anders S Christensen ◽  
Maher Jan Channir ◽  
Jan H. Jensen
Keyword(s):  
Hydrogen Bonding ◽  
Chemical Shift ◽  
Chemical Shifts ◽  
Structural Models ◽  
Protein G ◽  
Chemical Shielding ◽  
The Third ◽  
Entire Structure ◽  
Igg Binding ◽  
Structural Ensembles

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.

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

2015 ◽  
Author(s):  
Anders S Larsen ◽  
Lars A Bratholm ◽  
Anders S Christensen ◽  
Maher Jan Channir ◽  
Jan H. Jensen
Keyword(s):  
Hydrogen Bonding ◽  
Chemical Shift ◽  
Chemical Shifts ◽  
Structural Models ◽  
Protein G ◽  
Chemical Shielding ◽  
The Third ◽  
Entire Structure ◽  
Igg Binding ◽  
Structural Ensembles

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.

scholarly journals ProCS15: a DFT-based chemical shift predictor for backbone and Cβatoms in proteins

PeerJ ◽  
2015 ◽  
Vol 3 ◽  
pp. e1344 ◽  
Author(s):  
Anders S. Larsen ◽  
Lars A. Bratholm ◽  
Anders S. Christensen ◽  
Maher Channir ◽  
Jan H. Jensen
Keyword(s):  
Hydrogen Bonding ◽  
Chemical Shift ◽  
Chemical Shifts ◽  
Structural Models ◽  
Protein G ◽  
Chemical Shielding ◽  
The Third ◽  
Entire Structure ◽  
Igg Binding ◽  
Structural Ensembles

We present ProCS15: a program that computes the isotropic chemical shielding values of backbone and Cβatoms 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.

Kinetics of the Antibody Recognition Site in the Third IgG-Binding Domain of Protein G

2016 ◽  
Vol 128 (33) ◽  
pp. 9719-9722 ◽  
Author(s):  
Supriya Pratihar ◽  
T. Michael Sabo ◽  
David Ban ◽  
R. Bryn Fenwick ◽  
Stefan Becker ◽  
...  
Keyword(s):  
Binding Domain ◽  
Recognition Site ◽  
Protein G ◽  
Antibody Recognition ◽  
The Third ◽  
Igg Binding ◽  
Kinetics Of

The Third IgG-Binding Domain from Streptococcal Protein G

1994 ◽  
Vol 243 (5) ◽  
pp. 906-918 ◽  
Author(s):  
Jeremy P. Derrick ◽  
Dale B. Wigley
Keyword(s):  
Binding Domain ◽  
Protein G ◽  
The Third ◽  
Igg Binding ◽  
Streptococcal Protein G

scholarly journals Protein structure refinement using a quantum mechanics-based chemical shielding predictor

2016 ◽  
Author(s):  
Lars A. Bratholm ◽  
Jan H. Jensen
Keyword(s):  
Quantum Mechanics ◽  
Simulated Annealing ◽  
Chemical Shift ◽  
Force Field ◽  
Chemical Shifts ◽  
Protein Structures ◽  
Empirical Methods ◽  
Structural Refinement ◽  
Chemical Shielding ◽  
Chemical Shift Prediction

The accurate prediction of protein chemical shifts using quantum mechanics (QM)-based method has been the subject of intense research for more than 20 years but so far empirical methods for chemical shift prediction have proven more accurate. In this paper we show that a QM-based predictor of protein backbone and CB chemical shifts (ProCS15, PeerJ 2016, 3:e1344) is of comparable accuracy to empirical chemical shift predictors after chemical shift-based structural refinement that removes small structural errors. We present a method by which quantum chemistry based predictions of isotropic chemical shielding values (ProCS15) can be used to refine protein structures using Markov Chain Monte Carlo (MCMC) simulations, relating the chemical shielding values to the experimental chemical shifts probabilistically. Two kinds of MCMC structural refinement simulations were performed using force field geometry optimized X-ray structures as starting points: Simulated annealing of the starting structure and constant temperature MCMC simulation followed by simulated annealing of a representative ensemble structure. Annealing of the CHARMM structure changes the CA-RMSD by an average of 0.4 Å but lowers the chemical shift RMSD by 1.0 and 0.7 ppm for CA and N. Conformational averaging has a relatively small effect (0.1 - 0.2 ppm) on the overall agreement with carbon chemical shifts but lowers the error for nitrogen chemical shifts by 0.4 ppm. If a residue-specific offset is included the ProCS15 predicted chemical shifts have RMSD values relative to experiment that are comparable to popular empirical chemical shift predictors. The annealed representative ensemble structures differs in CA-RMSD relative to the initial structures by an average of 2.0 Å, with >2.0 Å difference for six proteins. In four of the cases, the largest structural differences arise in structurally flexible regions of the protein as determined by NMR, and in the remaining two cases, the large structural change may be due to force field deficiencies. The overall accuracy of the empirical methods are slightly improved by annealing the CHARMM structure with ProCS15, which may suggest that the minor structural changes introduced by ProCS15-based annealing improves the accuracy of the protein structures. Having established that QM-based chemical shift prediction can deliver the same accuracy as empirical shift predictors we hope this can help increase the accuracy of related approaches such as QM/MM or linear scaling approaches or interpreting protein structural dynamics from QM-derived chemical shift.

Kinetics of the Antibody Recognition Site in the Third IgG-Binding Domain of Protein G

2016 ◽  
Vol 55 (33) ◽  
pp. 9567-9570 ◽  
Author(s):  
Supriya Pratihar ◽  
T. Michael Sabo ◽  
David Ban ◽  
R. Bryn Fenwick ◽  
Stefan Becker ◽  
...  
Keyword(s):  
Binding Domain ◽  
Recognition Site ◽  
Protein G ◽  
Antibody Recognition ◽  
The Third ◽  
Igg Binding ◽  
Kinetics Of

scholarly journals Protein structure refinement using a quantum mechanics-based chemical shielding predictor

2017 ◽  
Vol 8 (3) ◽  
pp. 2061-2072 ◽  
Author(s):  
Lars A. Bratholm ◽  
Jan H. Jensen
Keyword(s):  
Quantum Mechanics ◽  
Protein Structure ◽  
Chemical Shift ◽  
Chemical Shifts ◽  
Structure Refinement ◽  
Structural Refinement ◽  
Chemical Shielding ◽  
Protein Backbone ◽  
Protein Structure Refinement ◽  
Comparable Accuracy

We show that a QM-based predictor of a protein backbone and CB chemical shifts is of comparable accuracy to empirical chemical shift predictors after chemical shift-based structural refinement that removes small structural errors (errors in chemical shifts shown in red).

scholarly journals Protein structure refinement using a quantum mechanics-based chemical shielding predictor

2016 ◽  
Author(s):  
Lars A. Bratholm ◽  
Jan H. Jensen
Keyword(s):  
Quantum Mechanics ◽  
Simulated Annealing ◽  
Chemical Shift ◽  
Force Field ◽  
Chemical Shifts ◽  
Protein Structures ◽  
Empirical Methods ◽  
Structural Refinement ◽  
Chemical Shielding ◽  
Chemical Shift Prediction

The accurate prediction of protein chemical shifts using quantum mechanics (QM)-based method has been the subject of intense research for more than 20 years but so far empirical methods for chemical shift prediction have proven more accurate. In this paper we show that a QM-based predictor of protein backbone and CB chemical shifts (ProCS15, PeerJ 2016, 3:e1344) is of comparable accuracy to empirical chemical shift predictors after chemical shift-based structural refinement that removes small structural errors. We present a method by which quantum chemistry based predictions of isotropic chemical shielding values (ProCS15) can be used to refine protein structures using Markov Chain Monte Carlo (MCMC) simulations, relating the chemical shielding values to the experimental chemical shifts probabilistically. Two kinds of MCMC structural refinement simulations were performed using force field geometry optimized X-ray structures as starting points: Simulated annealing of the starting structure and constant temperature MCMC simulation followed by simulated annealing of a representative ensemble structure. Annealing of the CHARMM structure changes the CA-RMSD by an average of 0.4 Å but lowers the chemical shift RMSD by 1.0 and 0.7 ppm for CA and N. Conformational averaging has a relatively small effect (0.1 - 0.2 ppm) on the overall agreement with carbon chemical shifts but lowers the error for nitrogen chemical shifts by 0.4 ppm. If a residue-specific offset is included the ProCS15 predicted chemical shifts have RMSD values relative to experiment that are comparable to popular empirical chemical shift predictors. The annealed representative ensemble structures differs in CA-RMSD relative to the initial structures by an average of 2.0 Å, with >2.0 Å difference for six proteins. In four of the cases, the largest structural differences arise in structurally flexible regions of the protein as determined by NMR, and in the remaining two cases, the large structural change may be due to force field deficiencies. The overall accuracy of the empirical methods are slightly improved by annealing the CHARMM structure with ProCS15, which may suggest that the minor structural changes introduced by ProCS15-based annealing improves the accuracy of the protein structures. Having established that QM-based chemical shift prediction can deliver the same accuracy as empirical shift predictors we hope this can help increase the accuracy of related approaches such as QM/MM or linear scaling approaches or interpreting protein structural dynamics from QM-derived chemical shift.

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