Protein Loop Modeling Using a New Hybrid Energy Function and Its Application to Modeling in Inaccurate Structural Environments

Abstract

Protein loop modeling is a tool for predicting protein local structures of particular interest, providing opportunities for applications involving protein structure prediction and de novo protein design. Until recently, the majority of loop modeling methods have been developed and tested by reconstructing loops in frameworks of experimentally resolved structures. In many practical applications, however, the protein loops to be modeled are located in inaccurate structural environments. These include loops in model structures, low-resolution experimental structures, or experimental structures of different functional forms. Accordingly, discrepancies in the accuracy of the structural environment assumed in development of the method and that in practical applications present additional challenges to modern loop modeling methods. This study demonstrates a new strategy for employing a hybrid energy function combining physics-based and knowledge-based components to help tackle this challenge. The hybrid energy function is designed to combine the strengths of each energy component, simultaneously maintaining accurate loop structure prediction in a high-resolution framework structure and tolerating minor environmental errors in low-resolution structures. A loop modeling method based on global optimization of this new energy function is tested on loop targets situated in different levels of environmental errors, ranging from experimental structures to structures perturbed in backbone as well as side chains and template-based model structures. The new method performs comparably to force field-based approaches in loop reconstruction in crystal structures and better in loop prediction in inaccurate framework structures. This result suggests that higher-accuracy predictions would be possible for a broader range of applications. The web server for this method is available at http://galaxy.seoklab.org/loop with the PS2 option for the scoring function.

Exhaustive Conformational Sampling of Complex Fused Ring Macrocycles Using Inverse Kinematics

“…27–30 Such general information is not often available for macrocycles in which case a wide-range scan of all available DoF is used.…”

Constraint methods that accelerate free-energy simulations of biomolecules

“…Typically, additional information on the torsional propensities has been incorporated and combined with either kinematics inspired or other direct methods that seek to build the loops one residue at a time while seeking to minimize a distance function [81][82][83] or Jacobian guided kinematic closure. [84][85][86] Manifold learning and dimensionality reduction 72 techniques can be helpful; however, such techniques must be extended to be able to handle the singularities that distinguish constrained molecular conformation spaces as algebraic varieties rather than smooth manifolds. 71,72,87 …”

Template‐based modeling and ab initio refinement of protein oligomer structures using GALAXY in CAPRI round 30

“…Unreliably modeled loops or termini, called ULRs (Unreliable Local Regions), were predicted by a model‐consensus method that identifies residues showing large deviations among generated models. ULRs of lengths 5–29 were remodeled by loop or terminus modeling methods implemented in GalaxyLoop . Up to two thousand candidate loop conformations were first generated with the FALC (fragment assembly and loop closure) algorithm using the PS1tbm energy .…”

“…We used components of the GALAXY protein modeling package that detect homo‐oligomer templates (GalaxyGemini) and performed template‐based modeling (GalaxyTBM) to build template‐based models of oligomer structures. Additionally, we refined the template‐based models using GalaxyLoop to perform ab initio loop modeling, and used GalaxyRefineComplex for overall model refinement. These program components were tested in previous CASP experiments with some success .…”