title: Computational design of selective peptides to discriminate between similar PDZ domains in an oncogenic pathway.
abstract: Reagents that target protein-protein interactions to rewire signaling are of great relevance in biological research. Computational protein design may offer a means of creating such reagents on demand, but methods for encoding targeting selectivity are sorely needed. This is especially challenging when targeting interactions with ubiquitous recognition modules--for example, PDZ domains, which bind C-terminal sequences of partner proteins. Here we consider the problem of designing selective PDZ inhibitor peptides in the context of an oncogenic signaling pathway, in which two PDZ domains (NHERF-2 PDZ2-N2P2 and MAGI-3 PDZ6-M3P6) compete for a receptor C-terminus to differentially modulate oncogenic activities. Because N2P2 has been shown to increase tumorigenicity and M3P6 to decreases it, we sought to design peptides that inhibit N2P2 without affecting M3P6. We developed a structure-based computational design framework that models peptide flexibility in binding yet is efficient enough to rapidly analyze tradeoffs between affinity and selectivity. Designed peptides showed low-micromolar inhibition constants for N2P2 and no detectable M3P6 binding. Peptides designed for reverse discrimination bound M3P6 tighter than N2P2, further testing our technology. Experimental and computational analysis of selectivity determinants revealed significant indirect energetic coupling in the binding site. Successful discrimination between N2P2 and M3P6, despite their overlapping binding preferences, is highly encouraging for computational approaches to selective PDZ targeting, especially because design relied on a homology model of M3P6. Still, we demonstrate specific deficiencies of structural modeling that must be addressed to enable truly robust design. The presented framework is general and can be applied in many scenarios to engineer selective targeting.
authors.affiliation: Department of Biological Sciences, Dartmouth College, Hanover, NH 03755, USA.
authors.forename: Fan
authors.initials: F
authors.lastname: Zheng
authors.affiliation: Department of Computer Science, Dartmouth College, Hanover, NH 03755, USA.
authors.forename: Heather
authors.initials: H
authors.lastname: Jewell
authors.affiliation: Department of Chemistry, Dartmouth College, Hanover, NH 03755, USA.
authors.forename: Jeremy
authors.initials: J
authors.lastname: Fitzpatrick
authors.affiliation: Department of Biological Sciences, Dartmouth College, Hanover, NH 03755, USA.
authors.forename: Jian
authors.initials: J
authors.lastname: Zhang
authors.affiliation: Department of Chemistry, Dartmouth College, Hanover, NH 03755, USA.
authors.forename: Dale F
authors.initials: DF
authors.lastname: Mierke
authors.affiliation: Department of Biological Sciences, Dartmouth College, Hanover, NH 03755, USA; Department of Computer Science, Dartmouth College, Hanover, NH 03755, USA. Electronic address: gevorg.grigoryan@dartmouth.edu.
authors.forename: Gevorg
authors.initials: G
authors.lastname: Grigoryan
mesh_terms: D000595:Amino Acid Sequence; D001665:Binding Sites; D003198:Computer Simulation; D009682:Magnetic Resonance Spectroscopy; D008958:Models, Molecular; D008969:Molecular Sequence Data; D015394:Molecular Structure; D054731:PDZ Domains / Q000235:genetics*; D010452:Peptide Biosynthesis; D010455:Peptides / Q000737:chemistry* / Q000235:genetics; D010750:Phosphoproteins / Q000235:genetics / Q000378:metabolism; D011485:Protein Binding; D011487:Protein Conformation; D015202:Protein Engineering / Q000379:methods*; D015203:Reproducibility of Results; D017923:Sodium-Hydrogen Exchangers / Q000235:genetics / Q000378:metabolism; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
chemical_list: D010455:Peptides; D010750:Phosphoproteins; D017923:Sodium-Hydrogen Exchangers; C093376:sodium-hydrogen exchanger regulatory factor
keywords: PDZ domains; computational protein design; interaction selectivity; pathway modulation; selective targeting