Potential aggregation hot spots in recombinant human keratinocyte growth factor: a computational study.

Area of Science:

• Protein Engineering
• Biopharmaceutical Development
• Computational Biology

Background:

• Recombinant human keratinocyte growth factor (rhKGF) is a therapeutic protein prone to aggregation.
• Protein aggregation leads to loss of function and reduced therapeutic efficacy, even at moderate temperatures.

Purpose of the Study:

• To identify and characterize aggregation-prone regions (APRs) in rhKGF using computational tools.
• To pinpoint specific residues and regions responsible for rhKGF's intrinsic aggregation propensity.

Main Methods:

• Utilized a suite of sequence-based computational tools (TANGO, ZipperDB, AGGRESCAN, etc.) to predict APRs.
• Employed structure-based tools (SolubiS, CamSol, Aggrescan3D, SAP) to map predicted APRs onto the rhKGF structure.
• Analyzed the surface exposure and buried nature of identified APRs in the native protein state.

Main Results:

• Sequence-based analysis identified APRs primarily in regions 10-30, 40-60, 61-66, 88-120, and 130-140.
• Structure mapping revealed surface-exposed APRs (e.g., F16-R25, R47-I56) that can promote aggregation without unfolding.
• Structure-based SAP tool highlighted dynamically-exposed hydrophobic residues (e.g., V12, A50, V51, L88) as key mediators of native-state aggregation.

Conclusions:

• Identified specific APRs that dictate rhKGF's inherent aggregation tendency.
• These identified regions serve as critical targets for protein engineering strategies to enhance rhKGF stability and reduce aggregation.