Model for screened, charge-regulated electrostatics of an eye lens protein: Bovine gammaB-crystallin

Abstract

We model screened, site-specific charge regulation of the eye lens protein bovine gammaB-crystallin (γ B) and study the probability distributions of its proton occupancy patterns. Using a simplified dielectric model, we solve the linearized Poisson-Boltzmann equation to calculate a 54 × 54 work-of-charging matrix, each entry being the modeled voltage at a given titratable site, due to an elementary charge at another site. The matrix quantifies interactions within patches of sites, including γB charge pairs. We model intrinsic pK values that would occur hypothetically in the absence of other charges, with use of experimental data on the dependence of pK values on aqueous solution conditions, the dielectric model, and literature values. We use Monte Carlo simulations to calculate a model grand-canonical partition function that incorporates both the work-of-charging and the intrinsic pK values for isolated γB molecules and we calculate the probabilities of leading proton occupancy configurations, for 4 < pH < 8 and Debye screening lengths from 6 to 20 Å. We select the interior dielectric value to model γB titration data. At pH 7.1 and Debye length 6.0 Å, on a given γB molecule the predicted top occupancy pattern is present nearly 20% of the time, and 90% of the time one or another of the first 100 patterns will be present. Many of these occupancy patterns differ in net charge sign as well as in surface voltage profile. We illustrate how charge pattern probabilities deviate from the multinomial distribution that would result from use of effective pK values alone and estimate the extents to which γB charge pattern distributions broaden at lower pH and narrow as ionic strength is lowered. These results suggest that for accurate modeling of orientation-dependent γB-γB interactions, consideration of numerous pairs of proton occupancy patterns will be needed.

Quantifying viscosity and surface tension of multicomponent protein-nucleic acid condensates

“…For oppositely charged polymers, it is intuitive to expect that phase separation is maximal at their formal charge-neutral stoichiometry conditions ([T]/ [Arg] ¼ 1). However, this prediction may not hold for peptides and NAs because of a combined effect of uneven local charge distributions on the peptide chain (33), charge regulation effects (34,35), and the presence of short-range non-electrostatic interactions (22).…”

Learning about Biomolecular Solvation from Water in Protein Crystals

“…Although the position of many of the hydrogens on the protein chain can be inferred on the basis of an elementary description of bonding (partly explaining the success of structure validation tools, such as MolProbity), side-chain protonation states can remain somewhat ambiguous, as do the positions of side-chain hydrogens with a rotational degree of freedom. This problem is especially acute for side chains that contribute to an enzymatic pathway or to protein–protein interactions, such as salt bridges. − Prediction servers have thus been developed to infer p K a values and titration curves of individual side chains, based on the electrostatic properties of neighboring residues. , Other software packages rely on less involved algorithms to assign protonation states. For instance, MolProbity picks the most suitable protonation state and hydrogen atom position that minimizes clashes, whereas Gromacs analyzes the hydrogen-bonding network around it .…”

Measuring how two proteins affect each other's net charge in a crowded environment

“…13 Lund and coworkers proposed that charge regulation will be greatest when proteins with values of net charge nearest to zero are in close proximity to proteins of greater net charge (positive or negative). 13 This type of charge regulation during binding or crowding is generally assumed in proteins (or colloids) 14,[18][19][20] but has never been directly measured in proteins because it is difficult to simulate crowding in vitro let alone measure the net charge of a folded protein in solution at pI ≠ pH. Thus, it has been unclear how to directly measure the net charge of two folded proteins that are crowding each other, but are not directly binding.…”