S100A5 Human

What is S100A5 and what protein family does it belong to?

S100A5 (also known as S100D) is a protein encoded by the S100A5 gene in humans, located on chromosome 1q21. It belongs to the S100 family of proteins containing 2 EF-hand calcium-binding motifs . This family includes at least 13 members that are clustered on chromosome 1q21 and are involved in regulating cellular processes such as cell cycle progression and differentiation . As with other S100 proteins, S100A5 is localized in the cytoplasm and/or nucleus of cells .

S100A5 forms a homodimer in its functional state, with each monomer containing the characteristic EF-hand calcium-binding domains typical of the S100 family . The protein's primary structure consists of 92 amino acids, and it functions as a calcium sensor that undergoes conformational changes upon calcium binding, allowing it to interact with various target proteins .

What distinguishes S100A5 from other S100 family members?

S100A5 has several unique properties that differentiate it from other S100 family members:

• Exceptional calcium affinity: S100A5 binds calcium with an affinity 20-100 fold higher than other S100 proteins studied under identical conditions .

• Metal-binding versatility: Unlike some S100 proteins, S100A5 can bind multiple metal ions, including calcium (Ca²⁺), zinc (Zn²⁺), and copper (Cu²⁺) .

• Ion competition dynamics: Copper binding to S100A5 strongly impairs calcium binding, suggesting a potential regulatory mechanism .

• Restricted expression pattern: S100A5 is expressed in very restricted regions of the adult brain, unlike some S100 proteins that have broader tissue distribution .

• Ion binding stoichiometry: The homodimeric S100A5 can bind four Ca²⁺ ions with strong positive cooperativity, two Zn²⁺ ions, and four Cu²⁺ ions per dimer .

What are the ion-binding properties of S100A5?

S100A5 demonstrates complex and unique ion-binding capabilities:

• Calcium binding: The S100A5 homodimer binds four Ca²⁺ ions with strong positive cooperativity. This binding affinity is remarkably 20-100 fold higher than other S100 proteins studied under identical conditions .

• Zinc binding: S100A5 binds two Zn²⁺ ions per dimer, with the binding sites likely located at the opposite side of the EF-hands in each subunit .

• Copper binding: The protein can bind four Cu²⁺ ions per dimer. The copper-binding sites likely share ligands with the EF-hands .

• Ion competition: Cu²⁺ binding strongly impairs the binding of Ca²⁺, suggesting a potential regulatory mechanism or role in copper homeostasis .

• Structural stability: Despite binding different ions, the protein maintains its alpha-helical-rich secondary structure, as none of these ions significantly change this characteristic .

How can researchers experimentally characterize S100A5's binding properties?

Researchers can employ several methodological approaches to characterize S100A5's binding properties:

• Flow dialysis: This technique has been successfully used to measure ion binding affinities and cooperativity, revealing that S100A5 binds calcium with strong positive cooperativity .

• Fluorescence spectroscopy: After covalent labeling of an exposed thiol with 2-(4'-(iodoacetamide)anilino)-naphthalene-6-sulfonic acid, researchers can monitor changes in fluorescence upon ion binding. This approach has shown that Cu²⁺ binding, but not Ca²⁺ or Zn²⁺ binding, strongly decreases fluorescence .

• X-ray crystallography: This method provides detailed structural information, as demonstrated in the 6WN7 structure of human S100A5, helping to understand the molecular basis of its interactions .

• Computational docking studies: These can be employed to predict and analyze peptide binding modes at the S100A5 interface, revealing that peptides can exhibit multiple binding modes with few polar contacts .

• Machine learning approaches: Supervised machine learning has been used to train models that identify biochemical features determining peptide binding specificity in S100A5, revealing that hydrophobicity and shape complementarity, rather than polar contacts, are primary determinants .

What is known about the tissue-specific expression of S100A5 in humans?

S100A5 exhibits a highly specific expression pattern:

• Brain expression: S100A5 is expressed in very restricted regions of the adult brain, as demonstrated by immunohistochemical analysis .

• Cancer expression: Recent research has identified S100A5 expression in malignant cells of bladder cancer, where it functions as an immunosuppressive factor and oncogene .

• Cellular localization: As a member of the S100 protein family, S100A5 can be localized in the cytoplasm and/or nucleus of cells, depending on the cellular context .

Understanding the restricted expression pattern of S100A5 is crucial for exploring its physiological roles and potential involvement in disease states. The highly specific expression in brain regions suggests specialized functions in neural tissues that remain to be fully characterized.

What methods should researchers use to detect and quantify S100A5 in biological samples?

Several complementary approaches can be employed to detect and quantify S100A5:

• Immunohistochemistry (IHC): This is particularly useful for visualizing the spatial distribution of S100A5 in tissue sections, as demonstrated in studies examining its expression in brain regions and cancer tissues .

• ELISA: Commercial ELISA kits are available for the quantitative measurement of human S100A5 in biological samples .

• Western blotting: This technique can be used to detect and semi-quantify S100A5 protein levels in tissue or cell lysates, using recombinant human S100A5 as a positive control .

• RT-PCR and qPCR: These methods detect S100A5 gene expression at the mRNA level, useful for comparing expression levels across different tissues or experimental conditions.

• Single-cell RNA sequencing: This advanced technique enables the analysis of S100A5 expression at the single-cell level, providing insights into cell-type-specific expression patterns within heterogeneous tissues .

How does S100A5 contribute to tumor progression and immunosuppression?

Recent research has revealed significant roles for S100A5 in cancer biology:

• Immunosuppressive effects: S100A5 expression in malignant cells inhibits CD8⁺ T cell recruitment by decreasing pro-inflammatory chemokine secretion .

• Inhibition of anti-tumor immunity: S100A5 attenuates effector T cell killing of cancer cells by inhibiting CD8⁺ T cell proliferation and cytotoxicity .

• Oncogenic properties: Beyond its immunosuppressive functions, S100A5 acts as an oncogene, promoting tumor proliferation and invasion .

• Spatial exclusion: Clinically, there is a spatially exclusive relationship between S100A5⁺ tumor cells and CD8⁺ T cells in tissue microarrays, suggesting that S100A5 creates a non-permissive microenvironment for T cell infiltration .

• Clinical correlation: S100A5 expression negatively correlates with immunotherapy efficacy in both real-world and public immunotherapy cohorts .

How can targeting S100A5 enhance cancer immunotherapy?

Targeting S100A5 presents a promising strategy to improve immunotherapy efficacy:

• Converting "cold" tumors: S100A5 shapes a non-inflamed tumor microenvironment in bladder cancer. Targeting S100A5 can convert these "cold" tumors into "hot" tumors that are more responsive to immunotherapy .

• Synergistic effects: Targeting S100A5 synergizes with anti-PD-1 treatment by enhancing the infiltration and cytotoxicity of CD8⁺ T cells .

• Improved chemokine signaling: Inhibiting S100A5 may restore pro-inflammatory chemokine secretion, enhancing T cell recruitment to the tumor site .

• Overcoming resistance: Given that S100A5 negatively correlates with immunotherapy efficacy, targeting this protein might help overcome resistance to immune checkpoint blockade therapies .

What machine learning approaches have been used to study S100A5 peptide recognition?

Advanced computational methods have provided insights into S100A5's binding properties:

• Feature-based analysis: Rather than treating peptides as amino acid sequences, researchers have used supervised machine learning to model peptides as collections of biochemical features .

• Random Forest modeling: This approach was used to train models against high-throughput phage display datasets collected for human S100A5, revealing key determinants of binding specificity .

• Identification of binding determinants: Machine learning models identified hydrophobicity and shape complementarity, rather than polar contacts, as the primary determinants of peptide binding specificity in S100A5 .

• Structural validation: Crystal structure determination of S100A5 and computational docking studies of diverse peptides confirmed the machine learning predictions, showing that peptides exhibit multiple binding modes at the S100A5 peptide interface with few polar contacts .

• Target prediction: Trained models were used to predict new, plausible binding targets in the human proteome, successfully identifying a fragment of α-1-syntrophin that binds to S100A5 .

What multi-omics approaches are useful for studying S100A5 in the tumor microenvironment?

Integrated multi-omics approaches provide comprehensive insights into S100A5's role in cancer:

• Systematic multi-omics analysis: This approach identified S100A5 as a novel immunosuppressive target for bladder cancer .

• Single-cell RNA sequencing: This technique reveals the heterogeneity of tumor and immune cell populations, allowing researchers to understand how S100A5 affects different cell types within the tumor microenvironment .

• Cell-cell communication analysis: Tools like CellChat can be used to infer and analyze communication between different cell types influenced by S100A5 expression .

• Spatial transcriptomics/proteomics: These methods can reveal the spatial relationships between S100A5-expressing cells and immune cells within the tumor microenvironment .

• Integrated analysis of immunotherapy cohorts: Combining genomic, transcriptomic, and clinical data from immunotherapy cohorts can help understand how S100A5 expression influences treatment response .

What are the most promising therapeutic strategies targeting S100A5?

Several therapeutic approaches could be developed to target S100A5:

• Small molecule inhibitors: Developing compounds that specifically bind to S100A5 and interfere with its function could be an effective strategy.

• Combination therapies: Based on recent findings, combining S100A5 inhibition with immune checkpoint blockade (particularly anti-PD-1/PD-L1 therapy) shows promise for enhancing cancer immunotherapy efficacy .

• Drug repurposing: Exploring existing drugs that might modulate S100A5 function, similar to how niclosamide has been investigated for other S100 proteins mentioned in the literature .

• Gene silencing approaches: RNA interference or CRISPR-based strategies could be employed to downregulate S100A5 expression in cancer cells.

• Targeting downstream pathways: Identifying and targeting the signaling pathways affected by S100A5 could provide alternative therapeutic strategies.

What critical knowledge gaps remain in S100A5 research?

Despite recent advances, several important questions about S100A5 remain unanswered:

• Physiological roles in the brain: Given its restricted expression in brain regions, the normal physiological functions of S100A5 in neural tissues remain largely unexplored .

• Molecular mechanisms of immunosuppression: While S100A5 has been shown to inhibit CD8⁺ T cell function, the precise molecular mechanisms mediating these effects require further investigation .

• Complete interactome: The full spectrum of proteins interacting with S100A5 under different conditions (calcium-bound, copper-bound, etc.) remains to be characterized.

• Potential roles in other cancers: Current research has focused on bladder cancer, but S100A5 may play important roles in other malignancies that warrant investigation .

• Copper homeostasis connection: Given S100A5's strong copper-binding properties and the competition between copper and calcium binding, its potential role in copper homeostasis, particularly in the brain, deserves further study .