Related Experiment Videos
Interleukin-1 receptor (IL-1R) liquid formulation development using differential scanning calorimetry
R L Remmele1, N S Nightlinger, S Srinivasan
1Immunex Corporation, Seattle, WA 98101, USA. rremmele@immunex.com
Pharmaceutical Research
|April 2, 1998
Summary
Differential scanning calorimetry (DSC) revealed three melting transitions for Interleukin-1 Receptor (IL-1R), indicating stability in citrate buffer at pH 6 with NaCl. Optimal conditions enhance protein stability and prevent aggregation.
Area of Science:
- Biochemistry
- Protein Stability
- Formulation Science
Background:
- Interleukin-1 Receptor (IL-1R) is a crucial protein in immune response.
- Understanding IL-1R stability in aqueous solutions is vital for therapeutic applications.
- Protein aggregation and degradation impact drug efficacy and safety.
Purpose of the Study:
- To determine solution conditions that enhance the stability of aqueous Interleukin-1 Receptor (IL-1R).
- To investigate the relationship between thermal unfolding and aggregation.
- To identify optimal excipients for IL-1R stabilization.
Main Methods:
- Differential Scanning Calorimetry (DSC) was used to assess thermal stability and melting transitions (Tm).
- SDS-PAGE monitored degradation products to determine optimal pH.
- SEC evaluated the correlation between thermal unfolding and aggregation.
- Circular Dichroism (CD) confirmed secondary structure content.
Main Results:
- IL-1R exhibits approximately 39% beta-sheet structure.
- DSC identified three melting transitions for IL-1R, with Tm values around 47°C and 66°C.
- Sodium chloride (NaCl) demonstrated significant stabilizing effects, shifting a transition to 53°C.
- Preservatives like phenol, m-cresol, and benzyl alcohol showed varying degrees of stabilization.
Conclusions:
- The three observed melting transitions correspond to the unfolding of IL-1R's three immunoglobulin-like domains.
- Optimal stability was achieved in 20 mM sodium citrate at pH 6, with NaCl for isotonicity.
- DSC effectively correlated predicted stability rankings with observed aggregation levels.