APOP

APOP predicts allosteric pockets in protein structures to identify sites that can modulate protein function through ligand-induced conformational changes.

Key Features:

• Elastic Network Model: APOP perturbs an elastic network model by stiffening pairwise interactions across candidate pockets to simulate ligand-binding effects.
• Global Mode Frequency Analysis: It ranks predicted pockets by shifts in global mode frequencies indicative of altered protein dynamics upon perturbation.
• Local Hydrophobicity Assessment: It computes mean local hydrophobicities of predicted pockets to evaluate chemical environments that favor ligand binding.
• High Prediction Success Rate: Validated on a dataset of allosteric proteins including monomers and multimeric assemblages, APOP identifies known allosteric pockets in 92 of 104 test cases within the top three rankings.
• Discovery of Novel Pockets: It reveals novel alternative allosteric pockets, including large central cavities at the centers of protein assemblages that can modulate dynamics when liganded.

Scientific Applications:

• Protein allostery research: APOP locates regulatory sites to study mechanisms of allosteric modulation and conformational dynamics.
• Drug discovery: APOP prioritizes known and novel allosteric sites as candidate targets for therapeutic modulation and drug discovery.

Methodology:

APOP simulates ligand-induced conformational changes using an elastic network model, perturbs the network by stiffening pairwise interactions across candidate pockets, calculates shifts in global mode frequencies and mean local hydrophobicities, and ranks pockets by frequency shifts.