Determining whether a protein regulates its net electrostatic charge during electron transfer (ET) will deepen our mechanistic understanding of how polypeptides tune rates and free energies of ET (e.g., by affecting reorganization energy, and/or redox potential). Charge regulation during ET has never been measured for proteins because few tools exist to measure the net charge of a folded protein in solution at different oxidation states. Herein, we used a niche analytical tool (protein charge ladders analyzed with capillary electrophoresis) to determine that the net charges of myoglobin, cytochrome c, and azurin change by 0.62±0.06, 1.19±0.02, and 0.51±0.04 units upon single ET. Computational analysis predicts that these fluctuations in charge arise from changes in the pK a values of multiple non‐coordinating residues (predominantly histidine) that involve between 0.42–0.90 eV. These results suggest that ionizable residues can tune the reactivity of redox centers by regulating the net charge of the entire protein–cofactor–solvent complex.

Determining whether a protein regulates its net electrostatic charge during electron transfer (ET) will deepen our mechanistic understanding of how polypeptides tune rates and free energies of ET (e.g., by affecting reorganization energy, and/or redox potential). Charge regulation during ET has never been measured for proteins because few tools exist to measure the net charge of a folded protein in solution at different oxidation states. Herein, we used a niche analytical tool (protein charge ladders analyzed with capillary electrophoresis) to determine that the net charges of myoglobin, cytochrome c, and azurin change by 0.62±0.06, 1.19±0.02, and 0.51±0.04 units upon single ET. Computational analysis predicts that these fluctuations in charge arise from changes in the pKa values of multiple non‐coordinating residues (predominantly histidine) that involve between 0.42–0.90 eV. These results suggest that ionizable residues can tune the reactivity of redox centers by regulating the net charge of the entire protein–cofactor–solvent complex.

The net electrostatic charge (Z) of a folded protein in solution represents a bird's eye view of its surface potentials—including contributions from tightly bound metal, solvent, buffer, and cosolvent ions—and remains one of its most enigmatic properties. Few tools are available to the average biochemist to rapidly and accurately measure Z at pH≠pI. Tools that have been developed more recently seem to go unnoticed. Most scientists are content with this void and estimate the net charge of a protein from its amino acid sequence, using textbook values of pKa. Thus, Z remains unmeasured for nearly all folded proteins at pH≠pI. When marveling at all that has been learned from accurately measuring the other fundamental property of a protein—its mass—one wonders: what are we missing by not measuring the net charge of folded, solvated proteins? A few big questions immediately emerge in bioinorganic chemistry. When a single electron is transferred to a metalloprotein, does the net charge of the protein change by approximately one elementary unit of charge or does charge regulation dominate, that is, do the pKa values of most ionizable residues (or just a few residues) adjust in response to (or in concert with) electron transfer? Would the free energy of charge regulation (ΔΔGz) account for most of the outer sphere reorganization energy associated with electron transfer? Or would ΔΔGz contribute more to the redox potential? And what about metal binding itself? When an apo‐metalloprotein, bearing minimal net negative charge (e.g., Z=−2.0) binds one or more metal cations, is the net charge abolished or inverted to positive? Or do metalloproteins regulate net charge when coordinating metal ions? The author's group has recently dusted off a relatively obscure tool—the “protein charge ladder”—and used it to begin to answer these basic questions.

The “red reflex test” is used to screen children for leukocoria (“white eye”) in a standard pediatric examination, but is ineffective at detecting many eye disorders. Leukocoria also presents in casual photographs. The clinical utility of screening photographs for leukocoria is unreported. Here, a free smartphone application (CRADLE: ComputeR-Assisted Detector of LEukocoria) was engineered to detect photographic leukocoria and is available for download under the name “White Eye Detector.” This study determined the sensitivity, specificity, and accuracy of CRADLE by retrospectively analyzing 52,982 longitudinal photographs of children, collected by parents before enrollment in this study. The cohort included 20 children with retinoblastoma, Coats’ disease, cataract, amblyopia, or hyperopia and 20 control children. For 80% of children with eye disorders, the application detected leukocoria in photographs taken before diagnosis by 1.3 years (95% confidence interval, 0.4 to 2.3 years). The CRADLE application allows parents to augment clinical leukocoria screening with photography.

This is the author manuscript accepted for publication and has undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record.

This is the author manuscript accepted for publication and has undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record.

Repulsive electrostatic forces between prion‐like proteins are a barrier against aggregation. In neuropharmacology, however, a prion's net charge (Z) is not a targeted parameter. Compounds that selectively boost prion Z remain unreported. Here, we synthesized compounds that amplified the negative charge of misfolded superoxide dismutase‐1 (SOD1) by acetylating lysine‐NH3+ in amyloid‐SOD1, without acetylating native‐SOD1. Compounds resembled a “ball and chain” mace: a rigid amyloid‐binding “handle” (benzothiazole, stilbene, or styrylpyridine); an aryl ester “ball”; and a triethylene glycol chain connecting ball to handle. At stoichiometric excess, compounds acetylated up to 9 of 11 lysine per misfolded subunit (ΔZfibril=−8100 per 103 subunits). Acetylated amyloid‐SOD1 seeded aggregation more slowly than unacetylated amyloid‐SOD1 in vitro and organotypic spinal cord (these effects were partially due to compound binding). Compounds exhibited reactivity with other amyloid and non‐amyloid proteins (e.g., fibrillar α‐synuclein was peracetylated; serum albumin was partially acetylated; carbonic anhydrase was largely unacetylated).

Repulsive electrostatic forces between prion‐like proteins are a barrier against aggregation. In neuropharmacology, however, a prion's net charge (Z) is not a targeted parameter. Compounds that selectively boost prion Z remain unreported. Here, we synthesized compounds that amplified the negative charge of misfolded superoxide dismutase‐1 (SOD1) by acetylating lysine‐NH3+ in amyloid‐SOD1, without acetylating native‐SOD1. Compounds resembled a “ball and chain” mace: a rigid amyloid‐binding “handle” (benzothiazole, stilbene, or styrylpyridine); an aryl ester “ball”; and a triethylene glycol chain connecting ball to handle. At stoichiometric excess, compounds acetylated up to 9 of 11 lysine per misfolded subunit (ΔZfibril=−8100 per 103 subunits). Acetylated amyloid‐SOD1 seeded aggregation more slowly than unacetylated amyloid‐SOD1 in vitro and organotypic spinal cord (these effects were partially due to compound binding). Compounds exhibited reactivity with other amyloid and non‐amyloid proteins (e.g., fibrillar α‐synuclein was peracetylated; serum albumin was partially acetylated; carbonic anhydrase was largely unacetylated).