Deformable complex network for refining low-resolution X-ray structures.

Chong Zhang,Jianpeng Ma,Qinghua Wang

doi:10.1107/s139900471501528x

Abstract

In macromolecular X-ray crystallography, building more accurate atomic models based on lower resolution experimental diffraction data remains a great challenge. Previous studies have used a deformable elastic network (DEN) model to aid in low-resolution structural refinement. In this study, the development of a new refinement algorithm called the deformable complex network (DCN) is reported that combines a novel angular network-based restraint with the DEN model in the target function. Testing of DCN on a wide range of low-resolution structures demonstrated that it constantly leads to significantly improved structural models as judged by multiple refinement criteria, thus representing a new effective refinement tool for low-resolution structural determination.

Highlights

It is often a challenge to refine the atomic structures of macromolecular assemblies owing to their weak diffraction of X-rays
To address the weakness in the deformable elastic network (DEN) method in refining macromolecular structures, in this work we introduce a deformable complex network (DCN) method that combines DEN with additional information obtained from a deformable angular network (DAN)
In macromolecular X-ray crystallography, structural refinement based on lower-resolution experimental diffraction data remains a major challenge where new and efficient refinement algorithms are urgently needed

Summary

Introduction

It is often a challenge to refine the atomic structures of macromolecular assemblies owing to their weak diffraction of X-rays. The DEN method delivered substantial improvements for a wide range of low-resolution structures. In order to define the DCN refinement method, we first introduced a deformable angular network (DAN) model. The three atoms, of which one is specified as the vertex and the other two as tail atoms, must be present in both the reference and target structures. They need to satisfy the following additional criteria: (i) all three. Conventional refinement produced ten of the worst results and only one of the best results (lowest r.m.s.d. at 3.5 Aresolution)

Methods

Results

Conclusion