Crooks Richard O, Baxter Daniel, Panek Anna S, Lubben Anneke T, Mason Jody M
Department of Biology and Biochemistry, University of Bath, Claverton Down, Bath BA2 7AY, United Kingdom.
Chemical Characterisation and Analysis Facility, University of Bath, Claverton Down, Bath BA2 7AY, United Kingdom.
J Mol Biol. 2016 Jan 29;428(2 Pt A):385-398. doi: 10.1016/j.jmb.2015.11.022. Epub 2015 Dec 2.
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.
天然存在的蛋白质之间的相互作用具有高度特异性，蛋白质网络失衡与多种疾病相关。对于设计的蛋白质-蛋白质相互作用（PPI），所需的特异性 notoriously 难以设计。为了加速这一过程，我们衍生出了在组合时形成异源特异性PPI的肽。这是通过使用生成肽序列大型虚拟库并在所得相互作用组中搜索优先相互作用肽的软件来实现的。为了证明可行性，我们（i）基于平行二聚体卷曲螺旋基序生成了1536个肽序列，并改变了已知对稳定性和特异性重要的残基，（ii）在1,180,416个成员的相互作用组中筛选预测的Tm值，以及（iii）使用预测的Tm截止点分离出八个肽，这些肽在组合时形成四个异源特异性PPI。这要求八个肽相互作用组内的所有32种假设的脱靶相互作用都不受青睐，并且四个所需的相互作用正确配对。最后，我们通过表征相互作用组内的所有36对来验证该方法。在分析输出时，我们假设几个序列能够采用反平行方向。随后，我们通过去除那些这样做会导致完全互补静电配对的序列来改进软件。我们的方法可用于衍生出越来越大、因此也越来越复杂的异源特异性PPI集合，具有从疾病调节到合成生物学中生物材料和肽的设计等广泛的潜在下游应用。
