Deriving Heterospecific Self-Assembling Protein-Protein Interactions Using a Computational Interactome Screen.
Deriving Heterospecific Self-Assembling Protein-Protein Interactions Using a Computational Interactome Screen.
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DOI：
10.1016/j.jmb.2015.11.022
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发表时间：
2016-01-29
影响因子：
5.6
通讯作者：
Mason JM
中科院分区：
文献类型：
--
作者：
Crooks RO;Baxter D;Panek AS;Lubben AT;Mason JM
自然产生的蛋白质之间的相互作用是高度特异的，蛋白质网络失衡与许多疾病有关。对于设计的蛋白质-蛋白质相互作用(PPI)，所需的特异性可能是出了名的难以设计。为了加速这一过程，我们已经获得了当结合时形成异种特异性PPI的多肽。这是使用软件来实现的，该软件生成了大量的肽序列虚拟文库，并在所得到的相互作用体中搜索优先相互作用的多肽。为了证明可行性，我们(I)根据平行的二聚螺旋基序和已知对稳定性和特异性很重要的各种残基产生了1536个肽序列，(Ii)筛选了1,180,416个成员的相互作用组以获得预测的Tm值，(Iii)使用预测的TM截止点分离出8个肽，当组合时形成4个异种PPI。这需要八肽相互作用组中的所有32个假设的靶外相互作用都是不受欢迎的，并且四个所需的相互作用正确配对。最后，我们通过对相互作用体中的所有36对进行特征描述来验证该方法。在分析输出时，我们假设有几个序列能够采用反平行方向。我们随后改进了软件，删除了这样做会导致完全互补的静电配对的序列。我们的方法可以用于衍生越来越大的、因此复杂的异种PPI集合，具有广泛的潜在下游应用，从疾病调节到合成生物学中的生物材料和肽的设计。自然发生的蛋白质-蛋白质相互作用(PPI)具有高度的特异性。然而，对于设计的PPI来说，专用性可能是出了名的难以设计。我们通过计算筛选了一个巨大的互作基因组，得到了四个异种PPI。八个多肽形成四个异种卷曲；所有32个Off靶标都不受欢迎。该方法可以得到更大且日益复杂的异种PPI集合
Interactions between naturally occurring proteins are highly specific, with protein-network imbalances associated with numerous diseases. For designed protein–protein interactions (PPIs), required specificity can be notoriously difficult to engineer. To accelerate this process, we have derived peptides that form heterospecific PPIs when combined. This is achieved using software that generates large virtual libraries of peptide sequences and searches within the resulting interactome for preferentially interacting peptides. To demonstrate feasibility, we have (i) generated 1536 peptide sequences based on the parallel dimeric coiled-coil motif and varied residues known to be important for stability and specificity, (ii) screened the 1,180,416 member interactome for predicted Tm values and (iii) used predicted Tm cutoff points to isolate eight peptides that form four heterospecific PPIs when combined. This required that all 32 hypothetical off-target interactions within the eight-peptide interactome be disfavoured and that the four desired interactions pair correctly. Lastly, we have verified the approach by characterising all 36 pairs within the interactome. In analysing the output, we hypothesised that several sequences are capable of adopting antiparallel orientations. We subsequently improved the software by removing sequences where doing so led to fully complementary electrostatic pairings. Our approach can be used to derive increasingly large and therefore complex sets of heterospecific PPIs with a wide range of potential downstream applications from disease modulation to the design of biomaterials and peptides in synthetic biology. Naturally occurring protein–protein interactions (PPIs) are highly specific. For designed PPIs, however, specificity can be notoriously difficult to engineer. We have computationally screened a vast interactome to derive four heterospecific PPIs. Eight peptides form four heterospecific coiled coils; all 32 off targets are disfavoured. The method can derive larger and increasingly complex sets of heterospecific PPIs