Systematic identification of conditionally folded intrinsically disordered regions by AlphaFold2.
Systematic identification of conditionally folded intrinsically disordered regions by AlphaFold2.
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DOI：
10.1073/pnas.2304302120
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发表时间：
2023-10-31
影响因子：
11.1
通讯作者：
Forman-Kay JD
中科院分区：
文献类型：
--
作者：
Alderson TR;Pritišanac I;Kolarić Đ;Moses AM;Forman-Kay JD
AlphaFold2和其他基于机器学习的方法可以准确预测大多数蛋白质的结构。然而，近三分之二的人类蛋白质含有高度灵活且不能自主折叠的片段，也称为固有无序区（IDR）。一般来说，IDR在大量不同的构象之间迅速相互转换，这对定义一种或少量稳定构象的蛋白质结构预测方法提出了一个重大问题。在这里，我们发现AlphaFold2可以很容易地识别在某些条件下折叠（条件性折叠）的IDR子集的结构。我们利用AlphaFold2对条件性折叠IDR的预测来量化生命树中条件性折叠的程度，并使IDR中的致病突变合理化。AlphaFold蛋白质结构数据库包含数百万种蛋白质的预测结构。对于大多数含有不采用稳定结构的固有无序区（IDR）的人类蛋白质，通常假设这些区域具有反映低置信度结构预测的低AlphaFold2置信度分数。在这里，我们发现AlphaFold2为近15%的人类IDR分配了可信的结构。通过与已知有条件折叠的IDR子集的实验NMR数据（即，在结合时或在其他特定条件下），我们发现AlphaFold2经常预测有条件折叠状态的结构。基于已知有条件折叠的IDR数据库，我们估计AlphaFold2可以以高达88%的精度和10%的假阳性率识别有条件折叠的IDR，考虑到有条件折叠的IDR结构在其训练数据中的代表性最低，这是非常值得注意的。我们发现，人类疾病的突变是近五倍丰富的有条件折叠的IDRs的IDRs一般和高达80%的原核生物的IDRs预测有条件地折叠，相比之下，不到20%的真核生物的IDRs。这些结果表明，人类和其他真核生物蛋白质组中的大多数IDR在没有条件折叠的情况下发挥作用，但获得折叠的区域对突变更敏感。我们强调，AlphaFold2预测不揭示IDRs内的功能相关的结构可塑性，并且不能提供有条件折叠的IDRs的现实的集成表示。
AlphaFold2 and other machine learning-based methods can accurately predict the structures of most proteins. However, nearly two-thirds of human proteins contain segments that are highly flexible and do not autonomously fold, otherwise known as intrinsically disordered regions (IDRs). In general, IDRs interconvert rapidly between a large number of different conformations, posing a significant problem for protein structure prediction methods that define one or a small number of stable conformations. Here, we found that AlphaFold2 can readily identify structures for a subset of IDRs that fold under certain conditions (conditional folding). We leverage AlphaFold2’s predictions of conditionally folded IDRs to quantify the extent of conditional folding across the tree of life, and to rationalize disease-causing mutations in IDRs. The AlphaFold Protein Structure Database contains predicted structures for millions of proteins. For the majority of human proteins that contain intrinsically disordered regions (IDRs), which do not adopt a stable structure, it is generally assumed that these regions have low AlphaFold2 confidence scores that reflect low-confidence structural predictions. Here, we show that AlphaFold2 assigns confident structures to nearly 15% of human IDRs. By comparison to experimental NMR data for a subset of IDRs that are known to conditionally fold (i.e., upon binding or under other specific conditions), we find that AlphaFold2 often predicts the structure of the conditionally folded state. Based on databases of IDRs that are known to conditionally fold, we estimate that AlphaFold2 can identify conditionally folding IDRs at a precision as high as 88% at a 10% false positive rate, which is remarkable considering that conditionally folded IDR structures were minimally represented in its training data. We find that human disease mutations are nearly fivefold enriched in conditionally folded IDRs over IDRs in general and that up to 80% of IDRs in prokaryotes are predicted to conditionally fold, compared to less than 20% of eukaryotic IDRs. These results indicate that a large majority of IDRs in the proteomes of human and other eukaryotes function in the absence of conditional folding, but the regions that do acquire folds are more sensitive to mutations. We emphasize that the AlphaFold2 predictions do not reveal functionally relevant structural plasticity within IDRs and cannot offer realistic ensemble representations of conditionally folded IDRs.
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影响因子：
13.8
作者：
Bardwell JC;Jakob U
通讯作者：
Jakob U
影响因子：
15
作者：
Bhowmick A;Brookes DH;Yost SR;Dyson HJ;Forman-Kay JD;Gunter D;Head-Gordon M;Hura GL;Pande VS;Wemmer DE;Wright PE;Head-Gordon T
通讯作者：
Head-Gordon T
影响因子：
6.8
作者：
Borcherds W;Bremer A;Borgia MB;Mittag T
通讯作者：
Mittag T
DOI：
10.1016/j.str.2021.04.010
发表时间：
2021-06-03
期刊：
Structure (London, England : 1993)
影响因子：
--
作者：
Burley SK;Berman HM
通讯作者：
Berman HM
影响因子：
14.8
作者：
Borcherds, Wade;Theillet, Francois-Xavier;Daughdrill, Gary W.
通讯作者：
Daughdrill, Gary W.