Back

Screening Peptide Binders to IL-17A Using Classical Molecular Dynamics

Xu, W.; Fu, W.

2026-09-07 biochemistry
10.64898/2026.09.04.749315 bioRxiv
Show abstract

Identifying short peptides that bind therapeutically relevant proteins is a practical step toward developing peptide-based inhibitors. Here we screened 64 tetrapeptides for binding to the IL-17A homodimer using classical all-atom molecular dynamics simulations (GROMACS 2022.2, FF19SB force field, TIP3P water, 200 ns production per complex). Binding was ranked by a composite score that combines short-range interaction energies (Coul-SR + LJ-SR), close-contact frequency, mean intermolecular distance, and hydrogen bond occupancy. The tetrapeptide LYS-THR-CYS-ASP achieved the highest score in the set (composite score 2.85, total interaction energy -556 kJ/mol, average 8.0 H-bonds). Across all 64 simulations, electrostatic interactions accounted for approximately 72% of the total interaction energy. Stronger binders tended to contain charged and polar residues (Asp, Glu, Cys, Arg, Thr), while weaker binders were enriched in hydrophobic residues. Contact analysis identified a recurring interaction surface on IL-17A centered on cysteine and aromatic residues (Chain A: CYS87, Chain B:CYS196, A:HIS86, B:TYR175, B:HIS195), which we describe as a cysteine-aromatic cradle. These results nominate LYS-THR-CYS-ASP as a candidate for experimental binding validation and suggest simple sequence guidelines for designing IL-17A-targeting peptides.

Matching journals

The top 9 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.