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PROPKA3: Consistent Treatment of Internal and Surface Residues in Empirical p KaPredictions

Olsson, Mats H. M., Søndergaard, Chresten R., Rostkowski, Michal, Jensen, Jan H.·2011·Journal of Chemical Theory and Computation

Abstract

In this study, we have revised the rules and parameters for one of the most commonly used empirical pKa predictors, PROPKA, based on better physical description of the desolvation and dielectric response for the protein. We have introduced a new and consistent approach to interpolate the description between the previously distinct classifications into internal and surface residues, which otherwise is found to give rise to an erratic and discontinuous behavior. Since the goal of this study is to lay out the framework and validate the concept, it focuses on Asp and Glu residues where the protein pKa values and structures are assumed to be more reliable. The new and improved implementation is evaluated and discussed; it is found to agree better with experiment than the previous implementation (in parentheses): rmsd = 0.79 (0.91) for Asp and Glu, 0.75 (0.97) for Tyr, 0.65 (0.72) for Lys, and 1.00 (1.37) for His residues. The most significant advance, however, is in reducing the number of outliers and removing unreasonable sensitivity to small structural changes that arise from classifying residues as either internal or surface.

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Metadata

Authors
Olsson, M. H. M., Søndergaard, C. R., Rostkowski, M., & Jensen, J. H.
Venue
Journal of Chemical Theory and Computation
Published
2011-01-06
Volume
7
Issue
2
Pages
525-537
ISSN
  • 1549-9618 (ISSN-L)
  • 1549-9626
OpenAlex
W2330799739
Cited by
4,435
References
0
FWCI
35.27
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: PROPKA3: Consistent Treatment of Internal and Surface Residues in Empirical p KaPredictions. https://app.cochat.ai/papers/10.1021/ct100578z
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Olsson, M. H. M., Søndergaard, C. R., Rostkowski, M., & Jensen, J. H. (2011). PROPKA3: Consistent Treatment of Internal and Surface Residues in Empirical p KaPredictions. Journal of Chemical Theory and Computation. https://doi.org/10.1021/ct100578z

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