Phospho-PDGF Receptor β (Tyr771) Antibody

About the Target

PDGFRB is a target of interest in many antibody-based workflows. The platelet-derived growth factor (PDGF) family consists of several dimeric isoforms linked by disulfide bonds, including PDGF-AA, PDGF-AB, PDGF-BB, PDGF-CC, and PDGF-DD. These isoforms exhibit specific binding affinities to two closely related receptor tyrosine kinases: PDGF receptor α (PDGFRα) and PDGF receptor β (PDGFRβ). PDGFRα homodimers interact with all PDGF isoforms except those containing PDGF-D, whereas PDGFRβ homodimers bind to PDGF-BB, PDGF-DD, and the PDGF-AB heterodimer. Depending on the literature source, PDGFRB may also be discussed as Phospho-PDGF Receptor beta (Tyr771).

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

Research Context

PDGFRB 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 cell membrane, cytoplasmic vesicle, and lysosome, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.

Consider these angles when interpreting target-level changes:

• apparent redistribution between cell membrane, cytoplasmic vesicle, and lysosome across matched conditions
• 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 PDGFRB. 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 PDGFRB reflect biology rather than handling. When interpreting PDGFRB, 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 PDGFRB 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.