Metalloallostery and Transition Metal Signaling: Bioinorganic Copper Chemistry Beyond Active Sites

Abstract

Transition metal chemistry is essential to life, where metal binding to DNA, RNA, and proteins underpins all facets of the central dogma of biology. In this context, metals in proteins are typically studied as static active site cofactors. However, the emergence of transition metal signaling, where mobile metal pools can transiently bind to biological targets beyond active sites, is expanding this conventional view of bioinorganic chemistry. This Minireview focuses on the concept of metalloallostery, using copper as a canonical example of how metals can regulate protein function by binding to remote allosteric sites (e.g., exosites). We summarize advances in and prospects for the field, including imaging dynamic transition metal signaling pools, allosteric inhibition or activation of protein targets by metal binding, and metal-dependent signaling pathways that underlie nutrient vulnerabilities in diseases spanning obesity, fatty liver disease, cancer, and neurodegeneration.

Keywords: Copper Fluorescent Sensor; Cuproplasia; Cuproptosis; Metalloallostery; Transition Metal Signaling.

Figure 1.

Metals and the periodic table of life. The periodic table highlighting in color major chemical elements that are essential for life, classified as non-metals (yellow), metalloids (green), transition metals (blue), and other metals (other colors). Metals are prevalent throughout the central dogma of biology and bind widely to DNA, RNA, and proteins. For example, divalent cations are necessary for DNA polymerase to synthesize DNA, tRNA tertiary structure is stabilized by several magnesium ions, and hemoglobin is a metalloprotein that contains iron-dependent heme groups as cofactors. This Minireview focuses on copper as a canonical transition metal nutrient that expands metal–protein interactions beyond active site coordination to include metalloallostery, where copper can activate or inhibit protein function by binding to remote exosites outside the primary active site. Figure was created with BioRender.com.

Figure 2.

Metalloproteins classified by the type of metal-binding interaction. a) Traditionally, metalloproteins are defined primarily as proteins with metals bound within active sites to regulate their function. These metals are typically part of the static metal pool because they often bind tightly to protein active sites. b) Metallloallostery represents an emerging class of metal–protein interactions, where dynamic interactions between the metal and protein occur at remote exosites outside the active site to regulate their function. These metals are typically part of the labile metal pool, as the interactions are transient and dynamic. c) Examples of these different classes of copper-dependent proteins include copper–zinc superoxide dismutase (SOD1, active site) and phosphodiesterase 3B (PDE3B, allosteric site). SOD1: PDB 1PU0,^[16] PDE3B: PDB 1SO2.^[17] Cu^I and PDE3B copper-binding cysteine are shown in brown. Figure was created with BioRender.com.

Figure 3.

Two major approaches to designing metal sensors for biological imaging. a) Binding-based sensing utilizes lock-and-key molecular recognition, with a metal ion-specific receptor or chelator for selective detection. Upon metal binding, the fluorophore (FL) is turned “on”, indicating that the metal is sensed. b) Activity-based sensing utilizes a metal ion trigger that promotes a reaction upon metal binding. Upon metal binding with a subsequent tandem reaction, the fluorophore (FL) is turned “on”, indicating that the metal is sensed. c) Representative examples of recent copper sensors with varying copper motifs and applications include Copper-Caged Luciferin-1 (CCL-1),^[48] Copper Fluor-4 (CF4),^[42] copper ratiometric indicator utilizing stabilized phosphines (crisp-17),^[44] and FRET copper probe-1 (FCP-1).^[45] Figure was created with BioRender.com.

Figure 4.

Copper metalloallostery influences diverse transition metal signaling pathways that drive cell behavior and are connected to diseases spanning obesity and non-alcoholic fatty liver disease (NAFLD) to cancer. a) Targets of copper metalloallostery. As an example of negative allosteric regulation, phosphodiesterase 3B (PDE3B) is inhibited by binding to copper. PDE3B induces cAMP-dependent lipolysis, demonstrating copper regulation of lipid metabolism. Various kinases important to cell health and cancer pathways are activated by copper. In the MAPK/ERK signaling pathway, mitogen-activated protein kinase kinase 1 and 2 (MEK1/2) activity is enhanced by copper and activates extracellular signal-regulated kinase 1 (ERK1). Pyruvate dehydrogenase kinase 1 (PDK1) and casein kinase 2 (CK2) activities are also copper dependent and activate the protein kinase B (PKB, also known as Akt) signaling pathway. Unc51-like kinase 1 and 2 (ULK1/2) drive autophagy and are another example of copper regulation of cell health. The E2 ubiquitin-conjugating enzyme D (UBE2D) family of enzymes are activated by copper to promote ubiquitin-mediated protein degradation, and thus play a role in regulating protein quality and preventing cell death. b) The importance of a balanced copper homeostasis is exemplified by low copper in Menkes disease and high copper in Wilson’s disease. c) Cuproplasia and cuproptosis are newly discovered copper-dependent cell proliferation and cell death pathways, respectively, that are metal-dependent disease vulnerabilities that can be exploited for development of new diagnostic and treatment platforms. Figure was created with BioRender.com.

Figure 5.

Copper metalloallostery regulates gene expression through copper-dependent transcription factors. a) AlphaFold^[78,79] predicted structures of S. cerevisiae transcription factors Ace1 (Uniprot P15315) and Mac1 (Uniprot P35192) with labeled Cu^I-binding cysteine motifs (brown) and DNA-binding regions (cyan). b) Ace1 regulation of CUP1, CRS5, and SOD1 expression in response to copper excess. c) Mac1 regulation of CTR1/3 and FRE1/7 expression in response to copper deficiency. Figure was created with BioRender.com.