Conformational Sampling and Structure Prediction of Multi-Loops in Proteins using Distance-Guided Sequential Chain-Growth Monte Carlo Method

Abstract

Protein loops are critical to their overall biochemical functions. The irregularity and flexibility of loops make their structures difficult to determine experimentally and challenging to model computationally. As loops are often in spatial proximity and interact with each other, modeling multiple loops simultaneously is an especially challenging task for protein structure prediction. We have developed a new method called Multi-loops Distance-guided Sequential chain-GROwth Monte Carlo (m-DiSGRO) for conformational sampling and structure prediction of multi-loop regions in protein. m-DiSGRO simultaneously grows interacting loops. Our method successfully achieves an average minimum RMSD of 1.43 angstrom and an average lowest energy RMSD of 2.78 angstrom for 36 pairs of interacting protein loops of the total length ranging from 12 residues to 24 residues, with a mean length of 18. Our method also succeeded in modeling multi-loops in beta-barrel membrane protein. For the outer-membrane protein G (OmpG) with 3 interacted loops of a total length of 12 + 12 + 10 =34 residues, the minimal RMSD and lowest energy RMSD conformations of the loop region compared to the native structure is only 2.51 angstrom and 2.65 angstrom, respectively.