Phospho-eIF4B (Ser406) Antibody

About the Target

eIF4B is an RNA-binding protein and the least evolutionarily conserved translation initiation factor. Despite low sequence conservation, eIF4B homologs across different species share a similar domain architecture, including an N-terminal RNA Recognition Motif (RRM), a central DRYG region, and a C-terminal Arginine-Rich Motif (ARM) domain. eIF4B functions as a co-factor in the eIF4 complex, which consists of the mRNA cap-binding protein eIF4E, the large scaffolding protein eIF4G, and the RNA helicase eIF4A. Depending on the literature source, EIF4B may also be discussed as Phospho-eIF4B (Ser406).

Reported cellular context includes cytosol, which can matter when signal is compared across treatments or changing cell states. Following EIF4B across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.

Research Context

EIF4B is commonly interpreted in the context of cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytosol, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.

Consider these angles when interpreting target-level changes:

• signal enrichment within cytosol relative to the broader cellular background
• signal-dependent shifts after ligand, inhibitor, or growth-factor perturbation
• differences between total target abundance and site-specific regulation when modified forms are compared
• co-patterning with orthogonal markers and control conditions that clarify pathway state

Variant Considerations

If your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for EIF4B. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.

Standardize sampling time, control choice, and downstream analysis thresholds so apparent differences in EIF4B reflect biology rather than handling. When interpreting EIF4B, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.

For multi-run studies, a shared reference condition can keep EIF4B trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.