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The Journal of Physical Chemistry B
Article . 2020 . Peer-reviewed
License: STM Policy #29
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Fully Atomistic Multiscale Approach for pKa Prediction

Authors: Laura Zanetti-Polzi; Isabella Daidone; Andrea Amadei;

Fully Atomistic Multiscale Approach for pKa Prediction

Abstract

The ionization state of titratable amino acids strongly affects proteins structure and functioning in a large number of biological processes. It is therefore essential to be able to characterize the pKa of ionizable groups inside proteins and to understand its microscopic determinants in order to gain insights into many functional properties of proteins. A big effort has been devoted to the development of theoretical approaches for the prediction of deprotonation free energies, yet the accurate theoretical/computational calculation of pKa values is recognized as a current challenge. A methodology based on a hybrid quantum/classical approach is here proposed for the computation of deprotonation free energies. The method is applied to calculate the pKa of formic acid, methylammonium, and methanethiol, providing results in good agreement with the corresponding experimental estimates. The pKa is also calculated for aspartic acid and lysine as single residues in solution and for three aspartic/glutamic acids inside a well-characterized protein: hen egg white lysozyme. While for small molecules the method is able to deal with multiple protonation states of all titratable groups, this becomes computationally very expensive for proteins. The calculated pKa values for the single amino acids (except for the zwitterionic aspartic acid) and inside the protein display a systematic shift with respect to the experimental values that suggests that the fine balance between hydrophobic and polar interactions might be not accurately reproduced by the usual classical force-fields, thus affecting the computation of deprotonation free energies. The calculated pKa shifts inside the protein are in good agreement with the corresponding experimental ones (within 1 pKa unit), well reproducing the pKa changes due to the protein environment even in the case of large pKa shifts.

Country
Italy
Keywords

PH MOLECULAR-DYNAMICS; POISSON-BOLTZMANN EQUATION; REDOX POTENTIAL SHIFT; FREE-ENERGY; EXPLICIT SOLVENT; IONIZABLE GROUPS; CONTINUUM MODEL; PROTEIN PK(A); DIELECTRIC FUNCTION; CALCULATING PK(A)S, Entropy, Lysine, Proteins, 612, Hydrogen-Ion Concentration, Amino Acids, Ph molecular-dynamics, Poisson-Boltzmann equation, redox potential shift, free-energy, explicit solvent, ionizable groups, continuum model, protein PK(A); DIELECTRIC FUNCTION; CALCULATING PK(A)S, Settore CHIM/02 - CHIMICA FISICA

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    13
    popularity
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    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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Found an issue? Give us feedback
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
13
Top 10%
Average
Top 10%