PEP-FOLD4

PEP-FOLD4 predicts peptide three-dimensional structures in aqueous solutions for peptides up to 40 amino acids by integrating physical chemistry models to capture pH- and salt-dependent electrostatics and intramolecular interactions.

Key Features:

• Peptide length support: Targets peptides of up to 40 amino acids for structure prediction.
• Debye-Hückel electrostatics: Implements the Debye-Hückel formalism to model interactions between charged side chains and account for pH and salt concentration effects.
• Mie potential for intramolecular forces: Uses a Mie potential to represent all intramolecular forces involving both backbone and side chains.
• Coarse-grained representation: Employs a coarse-grained representation of peptides to simplify molecular descriptions while capturing relevant folding interactions.
• Comparative performance with machine learning: Delivers performance comparable to machine-learning approaches for well-structured peptides.
• Enhanced accuracy for poly-charged peptides: Improves prediction accuracy and conformational modeling for poly-charged peptides under varying pH and salt conditions.

Scientific Applications:

• Protein Engineering: Assists design and assessment of peptides with targeted structural properties.
• Drug Design and Development: Aids identification and evaluation of stable peptide structures relevant to therapeutics and targets.
• Biophysical Studies: Provides insights into peptide conformational changes under different physiological pH and ionic conditions.

Methodology:

Uses a coarse-grained peptide representation combined with the Debye-Hückel formalism for electrostatic interactions between charged side chains and a Mie potential to model intramolecular forces and pH/salt-dependent effects.