Abstract
Predicting the biological function potential of post-translational modifications (PTMs) is becoming increasingly important in light of the exponential increase in available PTM data from high-throughput proteomics. We developed structural analysis of PTM hotspots (SAPH-ire)—a quantitative PTM ranking method that integrates experimental PTM observations, sequence conservation, protein structure, and interaction data to allow rank order comparisons within or between protein families. Here, we applied SAPH-ire to the study of PTMs in diverse G protein families, a conserved and ubiquitous class of proteins essential for maintenance of intracellular structure (tubulins) and signal transduction (large and small Ras-like G proteins). A total of 1728 experimentally verified PTMs from eight unique G protein families were clustered into 451 unique hotspots, 51 of which have a known and cited biological function or response. Using customized software, the hotspots were analyzed in the context of 598 unique protein structures. By comparing distributions of hotspots with known versus unknown function, we show that SAPH-ire analysis is predictive for PTM biological function. Notably, SAPH-ire revealed high-ranking hotspots for which a functional impact has not yet been determined, including phosphorylation hotspots in the N-terminal tails of G protein gamma subunits—conserved protein structures never before reported as regulators of G protein coupled receptor signaling. To validate this prediction we used the yeast model system for G protein coupled receptor signaling, revealing that gamma subunit–N-terminal tail phosphorylation is activated in response to G protein coupled receptor stimulation and regulates protein stability in vivo. These results demonstrate the utility of integrating protein structural and sequence features into PTM prioritization schemes that can improve the analysis and functional power of modification-specific proteomics data.
Highlights
Quence features into Post-translational modifications (PTMs) prioritization schemes that can improve the analysis and functional power of modification-specific proteomics data
Combining Sequence and Structural Characteristics of Modified Residues Distinguishes PTM Hotspots with a known function (Known) Biological Function—SAPH-ire was originally developed for the analysis of PTMs on large heterotrimeric G proteins because of the abundance of structural, mutational, functional and PTM data as well as their medical significance
The complex is activated by G protein coupled receptors (GPCRs), which can be stimulated by a wide-array of extracellular ligands including hormones, neurotransmitters, pheromones, light, among other compounds [22, 23]
Summary
SAPH-ire—SAPH-ire is comprised of three modular components: one, multiple sequence alignment (MSA) and PTM hotspot generation; two, structural projection of PTM hotspots; and three, hotspot ranking via the function potential (FP) calculation. Using FP-calculator (FPC), FP scores are calculated for each PTM hotspot within the family, which combines the total observed PTMs at an alignment position, the weighted solvent accessibility of the residue within the projected structural target, the protein interface residence, and sequence conservation within the MSA. PS ϭSASA͑Total PTMs, CS ϭ NPRC, FP ϭ 2͑IS͑CS, FPb ϭ 0.25͑IS͑CSwhere PS refers to PTM Score; SASA is the structurally derived (as opposed to sequence-derived) solvent accessible surface area; IS (interface score) is the PTM score weighted if the hotspot residue is found at a protein interface; CS is the weighted residue conservation score; PRC (Ptm_Res_Con) is the percent conservation of a modifiable residue at the projected PTM site (e.g. percentage of serine threonine or tyrosine conserved at projected sites of phosphorylation, lysine for ubiquitination, etc.), and FP is the function potential score for residues at protein interfaces and exposed surfaces (FP) or at solvent inaccessible surfaces (FPb) as determined from the SASA output from the POPS algorithm applied to the isolated target protein structure (i.e. in the absence of other proteins). Statistical Analysis—Statistical analysis of SAPH-ire data output as well as for quantified MAPK and HA immunoblots was achieved using GraphPad Prism software version 6
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