Chapter 11
pK
a
Calculations in Membrane Proteins from Molecular
Dynamics Simulations
Nuno F. B. Oliveira, Toma ´ s F. D. Silva, Pedro B. P. S. Reis,
and Miguel Machuqueiro
Abstract
The conformational changes of membrane proteins are crucial to their function and usually lead to
fluctuations in the electrostatic environment of the protein surface. A very effective way to quantify these
changes is by calculating the pK
a
values of the protein’s titratable residues, which can be regarded as
electrostatic probes. To achieve this, we need to take advantage of the fast and reliable pK
a
calculators
developed for globular proteins and adapt them to include the explicit effects of membranes. Here, we
provide a detailed linear response approximation protocol that uses our own software (PypKa) to calculate
reliable pK
a
values from short MD simulations of membrane proteins.
Key words Protonation, Conformation, Lipid bilayer, Poisson–Boltzmann, Monte Carlo, Linear
response approximation
1 Introduction
Membrane proteins (MPs) are key players in many biological pro-
cesses and have been estimated to be 20 to 30% of all proteins
encoded in the human genome [1]. These proteins can insert
partially or present a full insertion across the lipid bilayer. It is
remarkable how MPs live in such an anisotropic environment,
which changes from very high dielectric water to polar head
group region and very low dielectric region in the lipid tails, all
over a few angstroms distance. These are the two-extreme media in
terms of polarity, and MPs were evolved to take advantage of this
scenario. The complexity of the embedding media provides ample
possibilities for electrostatic, hydrogen bond, and Van der Waals-
type interactions. It is no surprise that physicochemical properties
like pH or ionic strength can also influence the MPs conformational
Irina S. Moreira et al. (eds.), Computational Design of Membrane Proteins, Methods in Molecular Biology, vol. 2315,
https://doi.org/10.1007/978-1-0716-1468-6_11, © Springer Science+Business Media, LLC, part of Springer Nature 2021
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