{"title":"Deformable complex network for refining low-resolution X-ray structures.","authors":"Chong Zhang, Qinghua Wang, Jianpeng Ma","doi":"10.1107/S139900471501528X","DOIUrl":null,"url":null,"abstract":"<p><p>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. </p>","PeriodicalId":6895,"journal":{"name":"Acta Crystallographica Section D: Biological Crystallography","volume":null,"pages":null},"PeriodicalIF":2.2000,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4631475/pdf/","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Acta Crystallographica Section D: Biological Crystallography","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1107/S139900471501528X","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2015/10/27 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
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.
期刊介绍:
Acta Crystallographica Section D welcomes the submission of articles covering any aspect of structural biology, with a particular emphasis on the structures of biological macromolecules or the methods used to determine them.
Reports on new structures of biological importance may address the smallest macromolecules to the largest complex molecular machines. These structures may have been determined using any structural biology technique including crystallography, NMR, cryoEM and/or other techniques. The key criterion is that such articles must present significant new insights into biological, chemical or medical sciences. The inclusion of complementary data that support the conclusions drawn from the structural studies (such as binding studies, mass spectrometry, enzyme assays, or analysis of mutants or other modified forms of biological macromolecule) is encouraged.
Methods articles may include new approaches to any aspect of biological structure determination or structure analysis but will only be accepted where they focus on new methods that are demonstrated to be of general applicability and importance to structural biology. Articles describing particularly difficult problems in structural biology are also welcomed, if the analysis would provide useful insights to others facing similar problems.