SPEACH_AF: Sampling protein ensembles and conformational heterogeneity with Alphafold2.
SPEACH_AF: Sampling protein ensembles and conformational heterogeneity with Alphafold2.
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DOI：
10.1371/journal.pcbi.1010483
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发表时间：
2022-08
影响因子：
4.3
通讯作者：
中科院分区：
文献类型：
--
作者：
Deepmind的Alphafold 2在CASP XIV中预测蛋白质结构方面的前所未有的表现，以及为多个蛋白质组和蛋白质序列库创建结构数据库，正在重塑结构生物学。然而，由于该数据库返回的是单一结构，因此Alphafold捕获蛋白质内在构象灵活性的能力受到了质疑。在这里，我们提出了一个通用的方法来驱动Alphafold2通过简单的操作，通过在硅片诱变的多序列比对模型的替代蛋白质构象。该方法基于这样的假设，即多序列比对也必须编码蛋白质结构异质性，因此其合理的操作将使Alphafold 2能够对交替构象进行采样。一个系统的建模管道对标准的蛋白质构象的灵活性的例子进行基准，并应用于询问膜蛋白的构象景观。这项工作通过产生多种蛋白质构象来进行生物学、生化学、生物药理学测试，并用于基于结构的药物设计，从而拓宽了Alphafold 2的适用性。Alphafold 2的蛋白质预测能力已经引起了许多问题。主要问题之一是Alphafold 2的结构是否适合揭示蛋白质的内在构象异质性。以高精度获得看不见或隐藏的构象的潜力将极大地推进广泛的结构生物学研究。我们已经设计了一种方法的多序列比对（MSA），是中央Alphafold2的预测能力的计算机诱变。该方法一致地揭示了未修改的默认MSA所未见的构象。相对于实验结构的预测构象的合奏分析完全支持的模型的生化意义。
The unprecedented performance of Deepmind’s Alphafold2 in predicting protein structure in CASP XIV and the creation of a database of structures for multiple proteomes and protein sequence repositories is reshaping structural biology. However, because this database returns a single structure, it brought into question Alphafold’s ability to capture the intrinsic conformational flexibility of proteins. Here we present a general approach to drive Alphafold2 to model alternate protein conformations through simple manipulation of the multiple sequence alignment via in silico mutagenesis. The approach is grounded in the hypothesis that the multiple sequence alignment must also encode for protein structural heterogeneity, thus its rational manipulation will enable Alphafold2 to sample alternate conformations. A systematic modeling pipeline is benchmarked against canonical examples of protein conformational flexibility and applied to interrogate the conformational landscape of membrane proteins. This work broadens the applicability of Alphafold2 by generating multiple protein conformations to be tested biologically, biochemically, biophysically, and for use in structure-based drug design. Many questions have arisen with the remarkable protein prediction capability of Alphafold2. One of the main questions is whether Alphafold2’s architecture is amenable to reveal the intrinsic conformational heterogeneity of proteins. The potential to obtain unseen or hidden conformations with high accuracy would greatly advance a broad range of structural biology pursuits. We have devised a method of in silico mutagenesis of the multiple sequence alignments (MSA) that are central to Alphafold2’s prediction capabilities. The approach consistently unveils conformations not seen with the unmodified default MSA. Analysis of the ensembles of predicted conformations relative to experimental structures fully support the biochemical significance of the models.
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DOI：
10.1016/j.jbc.2021.100749
发表时间：
2021-01
期刊：
The Journal of biological chemistry
影响因子：
--
作者：
Miller MD;Phillips GN Jr
通讯作者：
Phillips GN Jr
DOI：
10.1093/bioinformatics/btab881
发表时间：
2022-03-28
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Outeiral C;Nissley DA;Deane CM
通讯作者：
Deane CM
影响因子：
64.8
作者：
Jumper J;Evans R;Pritzel A;Green T;Figurnov M;Ronneberger O;Tunyasuvunakool K;Bates R;Žídek A;Potapenko A;Bridgland A;Meyer C;Kohl SAA;Ballard AJ;Cowie A;Romera-Paredes B;Nikolov S;Jain R;Adler J;Back T;Petersen S;Reiman D;Clancy E;Zielinski M;Steinegger M;Pacholska M;Berghammer T;Bodenstein S;Silver D;Vinyals O;Senior AW;Kavukcuoglu K;Kohli P;Hassabis D
通讯作者：
Hassabis D
影响因子：
14.9
作者：
NCBI Resource Coordinators
通讯作者：
NCBI Resource Coordinators
影响因子：
5.8
作者：
Mirdita, Milot;Steinegger, Martin;Soeding, Johannes
通讯作者：
Soeding, Johannes