Centre for Structural Systems Biology (CSSB), Leibniz-Institut für Virologie (LIV), Hamburg, Germany.
University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany.
Proteins. 2023 Dec;91(12):1935-1951. doi: 10.1002/prot.26644.
CASP assessments primarily rely on comparing predicted coordinates with experimental reference structures. However, experimental structures by their nature are only models themselves-their construction involves a certain degree of subjectivity in interpreting density maps and translating them to atomic coordinates. Here, we directly utilized density maps to evaluate the predictions by employing a method for ranking the quality of protein chain predictions based on their fit into the experimental density. The fit-based ranking was found to correlate well with the CASP assessment scores. Overall, the evaluation against the density map indicated that the models are of high accuracy, and occasionally even better than the reference structure in some regions of the model. Local assessment of predicted side chains in a 1.52 Å resolution map showed that side-chains are sometimes poorly positioned. Additionally, the top 118 predictions associated with 9 protein target reference structures were selected for automated refinement, in addition to the top 40 predictions for 11 RNA targets. For both proteins and RNA, the refinement of CASP15 predictions resulted in structures that are close to the reference target structure. This refinement was successful despite large conformational changes often being required, showing that predictions from CASP-assessed methods could serve as a good starting point for building atomic models in cryo-EM maps for both proteins and RNA. Loop modeling continued to pose a challenge for predictors, and together with the lack of consensus amongst models in these regions suggests that modeling, in combination with model-fit to the density, holds the potential for identifying more flexible regions within the structure.
CASP 评估主要依赖于将预测坐标与实验参考结构进行比较。然而,实验结构本身就只是模型——它们的构建涉及到在解释密度图并将其转换为原子坐标时的一定程度的主观性。在这里,我们直接利用密度图来评估预测,采用了一种根据其与实验密度的拟合程度对蛋白质链预测质量进行排序的方法。基于拟合的排名与 CASP 评估得分很好地相关。总体而言,与密度图的评估表明,这些模型具有很高的准确性,并且在模型的某些区域,其准确性甚至比参考结构还要好。在分辨率为 1.52Å 的密度图中对预测侧链的局部评估表明,侧链有时定位不佳。此外,选择了与 9 个蛋白质目标参考结构相关的前 118 个预测以及 11 个 RNA 目标的前 40 个预测进行自动细化。对于蛋白质和 RNA,CASP15 预测的细化导致结构与参考目标结构非常接近。尽管通常需要进行大的构象变化,但这种细化是成功的,这表明来自 CASP 评估方法的预测可以作为在 cryo-EM 图谱中构建蛋白质和 RNA 原子模型的良好起点。环建模仍然是预测器面临的挑战,并且这些区域的模型之间缺乏共识表明,建模与模型与密度的拟合相结合,有可能识别结构内更灵活的区域。