KEGG: fca:493970
STRING: 9685.ENSFCAP00000023698
MCL1 is an antiapoptotic member of the BCL2 family characterized by a relatively short half-life. The protein contains multiple BCL-2 homology (BH) domains that are critical for its function. The carboxy terminal of MCL1 shares significant sequence homology with bcl-2. MCL1 exists in at least two distinct isoforms: MCL1L (long form) and MCL1S (short form), with an additional MCL1ES (extra short form) also reported. Each isoform has distinct functions - the longer isoform (MCL1L) inhibits apoptosis while the shorter isoform (MCL1S) promotes cell death .
MCL1 serves as a rapid sensor that regulates cell death due to its characteristically short half-life, unlike other more stable BCL-2 family members. Beyond apoptosis regulation, MCL1 has unique functions in cell cycle progression and mitochondrial homeostasis. The protein can heterodimerize with and neutralize pro-apoptotic BCL-2 family members such as Bim or Bak. MCL1 expression increases upon exposure to various DNA damaging agents (ionizing radiation, ultraviolet radiation, and alkylating drugs), working in concert with changes in GADD45, Bax, and bcl-2 expression .
MCL1 is prominently associated with mitochondria, which aligns with its role in regulating apoptosis and mitochondrial function. The protein's localization is critical for its ability to interact with other BCL-2 family proteins and regulate cell survival. Through its mitochondrial association, MCL1 can influence various cellular processes including energy metabolism, particularly fatty acid oxidation (FAO). Recent research has shown that MCL1 functions as a master regulator of FAO, which creates unique vulnerabilities in MCL1-driven cancer cells that can be targeted therapeutically .
Recombinant MCL1 proteins are typically expressed in E. coli expression systems under controlled conditions. For optimal expression, consider using a bacterial expression vector with a strong promoter (T7 or tac) and fusion tags (His, GST, or MBP) to facilitate purification. Culture conditions should be optimized with induction at OD600 0.6-0.8 using IPTG concentrations of 0.1-1.0 mM, with temperatures lowered to 16-25°C during induction to increase soluble protein yield. It's important to include protease inhibitors during purification due to MCL1's susceptibility to degradation. For research applications requiring post-translational modifications, consider mammalian or insect cell expression systems rather than bacterial systems .
To study MCL1 protein stability:
Employ cycloheximide chase assays: Treat cells with cycloheximide to inhibit new protein synthesis, then harvest at various timepoints to assess MCL1 degradation rates
Pulse-chase experiments: Label proteins with radioisotopes or other tags, then track MCL1 degradation over time
Ubiquitination assays: Assess polyubiquitination patterns using immunoprecipitation followed by Western blotting
Phosphorylation analysis: Evaluate phosphorylation status using phospho-specific antibodies or mass spectrometry
Reverse-phase protein array: For high-throughput analysis of protein expression and post-translational modifications
Recent studies have shown that MCL1 inhibitors can paradoxically induce MCL1 protein stability, understanding the mechanisms of which requires these specialized techniques .
To investigate MCL1's interactions with other proteins:
Co-immunoprecipitation (Co-IP): Pull down MCL1 and identify binding partners
Proximity ligation assay (PLA): Visualize protein-protein interactions in situ
Fluorescence resonance energy transfer (FRET): Measure real-time interactions in living cells
Surface plasmon resonance (SPR): Determine binding kinetics and affinity constants
Isothermal titration calorimetry (ITC): Quantify thermodynamic parameters of binding
BH3 profiling: Assess functional interactions between anti-apoptotic and pro-apoptotic proteins
Molecular dynamics simulations: Predict key binding regions and interaction energies
These approaches have revealed that MCL1 predominantly interacts with specific pro-apoptotic BCL-2 family members such as Bim, Bak, and NOXA, with distinct binding patterns compared to other anti-apoptotic proteins like BCL-2 or BCL-xL .
MCL1 overexpression contributes to cancer cell survival and resistance to diverse chemotherapeutic agents through multiple mechanisms:
Direct inhibition of apoptosis by sequestering pro-apoptotic BCL-2 family members
Regulation of mitochondrial function and energy metabolism
Control of cell cycle progression
Modulation of DNA damage responses
In various cancer types, increased MCL1 expression correlates with poor prognosis and treatment resistance. For example, in glioblastoma, higher MCL1 expression is associated with immunosuppression, with significantly higher expression of immune checkpoint genes like CD274 and TIMP3 in MCL1-high tumors. This suggests that combining MCL1 inhibitors with immune checkpoint inhibitors might be therapeutically beneficial .
Several MCL1 inhibitors are currently under preclinical and clinical development:
AMG-176 and AZD5991 have shown promise in preclinical studies and are being tested for treating hematologic malignancies
MIM1 has been used as a reference compound in the development of next-generation inhibitors
Novel small molecule inhibitors are being identified through computational screening from natural product databases
Recent research has identified key amino acid residues, including PHE270 and MET250, as critical binding sites for MCL1 inhibition. Novel compounds ZINC000013374322 and ZINC000001090002 have demonstrated superior pharmacological properties and lower toxicity compared to reference inhibitors in computational studies. Current clinical challenges include balancing efficacy with toxicity, as MCL1's role in normal tissues raises concerns about potential side effects .
The MCL1-associated prognostic signature (MPS) has been developed as a tool to predict patient prognosis in cancers like glioblastoma. To implement this approach:
Collect RNA-seq data from patient samples
Quantify expression of MCL1-related genes (TSHR, HIST3H2A, ARGE, OSMR, ARHGEF25)
Calculate risk scores using the formula: risk score = (−0.112721)TSHR + (−0.016743)HIST3H2A + 0.030476ARGE + 0.046739OSMR + 0.005866*ARHGEF25
Stratify patients into high-risk and low-risk groups based on optimal cut-off values
Validate using survival analysis (e.g., Kaplan-Meier curves)
This signature has shown high accuracy in predicting 1-year survival (AUC = 0.741) and 3-year survival (AUC = 0.775) in glioblastoma patients. This approach demonstrates the potential of MCL1-based molecular signatures for prognostication and treatment stratification in cancer research .
Recent discoveries have identified MCL1 as a master regulator of fatty acid oxidation (FAO), creating a metabolic vulnerability in MCL1-driven cancers. The relationship operates through:
Direct interaction of MCL1 with mitochondrial FAO machinery
Regulation of key enzymes in the fatty acid metabolism pathway
Influence on mitochondrial membrane dynamics and function
Research has demonstrated that MCL1-driven cancer cells become uniquely susceptible to FAO inhibitors. In experimental models, genetic deletion of Mcl-1 in cancer cells can be rescued by re-expression of human MCL1, indicating a specific dependency. This metabolic function of MCL1 appears to be distinct from its anti-apoptotic role, opening new therapeutic avenues. When designing experiments to target this vulnerability, researchers should consider combining FAO inhibitors with conventional therapies to overcome resistance mechanisms .
Beyond its canonical role in apoptosis regulation, MCL1 serves multiple non-apoptotic functions that significantly impact therapeutic targeting:
Cell cycle regulation: MCL1 influences cell cycle progression through interaction with cell cycle proteins
Mitochondrial dynamics: MCL1 regulates mitochondrial fusion/fission and cristae structure
Energy metabolism: MCL1 governs fatty acid oxidation and other metabolic pathways
DNA damage response: MCL1 participates in DNA repair mechanisms
These non-apoptotic functions may explain why MCL1 inhibitors sometimes have unexpected effects. When designing MCL1-targeted therapies, researchers need to consider potential impacts on these alternative functions. For example, inhibitors targeting only the anti-apoptotic function might miss critical metabolic dependencies. This complexity necessitates careful experimental design when evaluating MCL1 inhibitors, including assessment of mitochondrial function, metabolic parameters, and cell cycle effects beyond simple cell death assays .
MCL1 function and stability are tightly regulated through various post-translational modifications:
Phosphorylation: Multiple kinases (GSK-3, JNK, ERK) phosphorylate MCL1 at different sites, affecting both stability and protein interactions
Ubiquitination: E3 ligases (MULE, FBW7, β-TrCP) target MCL1 for proteasomal degradation
Deubiquitination: USP9X and other deubiquitinases remove ubiquitin and stabilize MCL1
Cleavage: Caspases can cleave MCL1, converting it from anti- to pro-apoptotic forms
These modifications create a complex regulatory network that allows rapid adjustment of MCL1 levels and function in response to cellular stress. Experimental approaches to study these modifications include site-directed mutagenesis of modification sites, use of kinase or proteasome inhibitors, and targeted mass spectrometry. Understanding these modifications is crucial for developing drugs that might modulate MCL1 function through altering its post-translational modification patterns rather than direct binding inhibition .
When designing experiments with MCL1 inhibitors, researchers should consider:
Cell line selection: Different cell types have varying dependencies on MCL1 versus other BCL-2 family members
Inhibitor specificity: Confirm target engagement using thermal shift assays or CETSA (Cellular Thermal Shift Assay)
Combination strategies: Test MCL1 inhibitors with other BCL-2 family inhibitors (venetoclax) or conventional therapies
Resistance mechanisms: Monitor for compensatory upregulation of other anti-apoptotic proteins
Paradoxical effects: Some MCL1 inhibitors induce MCL1 protein stability while blocking function
Non-apoptotic functions: Assess impacts on metabolism, cell cycle, and mitochondrial function
In vivo translation: Consider pharmacokinetics, tissue distribution, and potential toxicities
Recent studies have shown that MCL1 inhibitors like AMG-176 and AZD5991 induce and stabilize MCL1 protein while inhibiting its function. Understanding this paradox is essential for proper experimental interpretation and therapeutic development .
To effectively compare feline and human MCL1:
Sequence alignment: Use bioinformatics tools to identify conserved domains and species-specific variations
Structural modeling: Generate comparative models to visualize structural differences
Expression vectors: Create constructs for both species variants with identical tags and promoters
Functional assays: Compare anti-apoptotic function using standardized cell death assays
Binding studies: Assess interaction with conserved binding partners (BIM, BAK) using identical methods
Inhibitor sensitivity: Compare response to the same panel of MCL1 inhibitors
Chimeric proteins: Create domain-swap constructs to identify functionally important regions
When conducting cross-species comparisons, it's crucial to use consistent experimental conditions and ensure that differences in post-translational modifications are accounted for. This approach can provide valuable insights into evolutionarily conserved functions versus species-specific adaptations of MCL1 .
Essential controls for recombinant MCL1 experiments include:
Protein quality controls:
Purity assessment via SDS-PAGE and mass spectrometry
Proper folding verification through circular dichroism
Activity confirmation via binding assays with known partners
Experimental controls:
Inactive MCL1 mutants (BH3 domain mutants)
Alternative BCL-2 family members (BCL-2, BCL-xL)
Vehicle controls for delivery systems
Rescue experiments:
Genetic knockout followed by reintroduction of wild-type or mutant MCL1
Species-specific rescue (e.g., human MCL1 in mouse Mcl-1 knockout)
Specificity controls:
Competitive binding assays with known ligands
Dose-response curves to demonstrate specific effects
Knockdown/knockout validation to confirm antibody specificity
Research has demonstrated the importance of these controls, particularly in rescue experiments. For example, exogenous human MCL1 expression can rescue the phenotype of mouse Mcl-1 deletion in B-ALL cells, confirming functional conservation across species and validating the specificity of observed effects .