Chang Liwei, Perez Alberto
Department of Chemistry, University of Florida, Gainesville, FL, USA.
Quantum Theory Project, University of Florida, Gainesville, FL, USA.
Angew Chem Int Ed Engl. 2023 Feb 6;62(7):e202213362. doi: 10.1002/anie.202213362. Epub 2023 Jan 12.
AlphaFold has revolutionized structural biology by predicting highly accurate structures of proteins and their complexes with peptides and other proteins. However, for protein-peptide systems, we are also interested in identifying the highest affinity binder among a set of candidate peptides. We present a novel competitive binding assay using AlphaFold to predict structures of the receptor in the presence of two peptides. For systems in which the individual structures of the peptides are well predicted, the assay captures the higher affinity binder in the bound state, and the other peptide in the unbound form with statistical significance. We test the application on six protein receptors for which we have experimental binding affinities to several peptides. We find that the assay is best suited for identifying medium to strong peptide binders that adopt stable secondary structures upon binding.
AlphaFold通过预测蛋白质及其与肽和其他蛋白质的复合物的高精度结构,彻底改变了结构生物学。然而,对于蛋白质-肽系统,我们也有兴趣在一组候选肽中识别出亲和力最高的结合物。我们提出了一种新颖的竞争性结合测定法,利用AlphaFold预测在存在两种肽的情况下受体的结构。对于肽的单个结构能得到很好预测的系统,该测定法能在结合状态下捕获更高亲和力的结合物,而另一种肽则以未结合形式存在,具有统计学意义。我们在六种蛋白质受体上测试了该应用,我们对这些受体与几种肽的结合亲和力有实验数据。我们发现该测定法最适合识别在结合时形成稳定二级结构的中等至强肽结合物。