An experiment-based algorithm for predicting the partitioning of unfolded peptides into phosphatidylcholine bilayer...

Area of Science:

• Biophysics
• Biochemistry
• Computational Biology

Background:

• Understanding polypeptide partitioning into membrane interfaces is crucial for membrane protein stability and peptide design.
• Existing hydrophobicity scales for amino acids are incomplete due to missing N- and C-terminal group data.

Purpose of the Study:

• To complete existing hydrophobicity scales by determining partitioning free energies of N- and C-terminal groups.
• To develop a simple algorithm for computing absolute partitioning free energies of unfolded peptides into phosphatidylcholine bilayer interfaces.

Main Methods:

• Measured pH-dependent partitioning of host-guest pentapeptides into POPC bilayer interfaces and n-octanol.
• Combined new measurements with existing data to derive hydrophobicity scale values for terminal groups.

Main Results:

• Determined hydrophobicity scale values for N- and C-terminal protonation, deprotonation, acetylation, and amidation.
• Found that a charged N terminus has a significantly smaller effect on bilayer partitioning than a charged C terminus.

Conclusions:

• The developed hydrophobicity scales and algorithm enable accurate computation of unfolded peptide partitioning free energies.
• This work enhances the ability to predict peptide behavior at membrane interfaces, aiding in drug design and understanding protein stability.