水准点(测量)
背景(考古学)
计算机科学
蛋白质结构预测
蛋白质数据库
选型
蛋白质结构
选择(遗传算法)
计算生物学
人工智能
生物
地理
大地测量学
生物化学
古生物学
作者
A. Teplyakov,Jinquan Luo,Galina Obmolova,T. Malia,Raymond W. Sweet,Robyn L. Stanfield,Sreekumar Kodangattil,Juan C. Almagro,Gary L. Gilliland
出处
期刊:Proteins
[Wiley]
日期:2014-03-14
卷期号:82 (8): 1563-1582
被引量:71
摘要
To assess the state-of-the-art in antibody structure modeling, a blinded study was conducted. Eleven unpublished Fab crystal structures were used as a benchmark to compare Fv models generated by seven structure prediction methodologies. In the first round, each participant submitted three non-ranked complete Fv models for each target. In the second round, CDR-H3 modeling was performed in the context of the correct environment provided by the crystal structures with CDR-H3 removed. In this report we describe the reference structures and present our assessment of the models. Some of the essential sources of errors in the predictions were traced to the selection of the structure template, both in terms of the CDR canonical structures and VL/VH packing. On top of this, the errors present in the Protein Data Bank structures were sometimes propagated in the current models, which emphasized the need for the curated structural database devoid of errors. Modeling non-canonical structures, including CDR-H3, remains the biggest challenge for antibody structure prediction.
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