AlphaFold-guided molecular replacement for solving challenging crystal structures.

IF 2.6 4区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS
Wei Wang, Zhen Gong, Wayne A Hendrickson
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Abstract

Molecular replacement (MR) is highly effective for biomolecular crystal structure determination, increasingly so as the database of known structures has increased. For candidates without recognizable similarity to known structures, however, crystal structure analyses have nearly always required experiments for de novo phase evaluation. Now, with the unprecedented accuracy of AlphaFold predictions of protein structures from amino-acid sequences, an appreciable expansion of the reach of MR for proteins is realized. Here, we sought to automate an AlphaFold-guided MR procedure that tailors predictions to the MR problem at hand. We first optimized the reliability cutoff parameters for residue inclusion as tested in application to a previously MR-intractable problem. We then examined cases where AlphaFold by default predicts a conformation alternative to that of the candidate structure, devising tests for MR solution either from domain-specific predictions or from predictions based on diverse sequence subclusters. We tested subclustering procedures on an enzyme system that entails multiple MR-challenging conformations. The overall process as implemented in Phenix automatically surveys a succession of trials of increasing computational complexity until an MR solution is found or the options are exhausted. Validated MR solutions were found for 92% of one set of 158 challenging problems from the PDB and 93% of those from a second set of 215 challenges. Thus, many crystal structure analyses that previously required experimental phase evaluation can now be solved by AlphaFold-guided MR. In effect, this and related MR approaches are de novo phasing methods.

alphafold引导分子替代解决具有挑战性的晶体结构。
分子替代(MR)是测定生物分子晶体结构非常有效的方法,随着已知结构数据库的增加,这种方法也越来越有效。然而,对于与已知结构没有可识别的相似性的候选物,晶体结构分析几乎总是需要进行从头相评估的实验。现在,随着AlphaFold对氨基酸序列蛋白质结构预测的前所未有的准确性,实现了MR对蛋白质的范围的显着扩展。在这里,我们试图自动化alphafold引导的MR过程,根据手头的MR问题量身定制预测。我们首先优化了残留物包含的可靠性截止参数,并将其应用于先前的mr棘手问题。然后,我们检查了AlphaFold在默认情况下预测候选结构的构象替代的情况,根据特定领域的预测或基于不同序列子簇的预测为MR解决方案设计测试。我们在一个酶系统上测试了亚聚类程序,该系统需要多个具有核磁共振挑战性的构象。在Phenix中实现的整个过程自动调查一系列增加计算复杂性的试验,直到找到MR解决方案或耗尽选项。在PDB的158个具有挑战性的问题中,有92%的问题得到了验证的MR解决方案,在第二组215个问题中,有93%的问题得到了验证的MR解决方案。因此,许多以前需要实验相位评估的晶体结构分析现在可以通过alphafold引导的MR来解决。实际上,这种方法和相关的MR方法都是新的相位方法。
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来源期刊
Acta Crystallographica. Section D, Structural Biology
Acta Crystallographica. Section D, Structural Biology BIOCHEMICAL RESEARCH METHODSBIOCHEMISTRY &-BIOCHEMISTRY & MOLECULAR BIOLOGY
CiteScore
4.50
自引率
13.60%
发文量
216
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.
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