Resolving Missing Protein Problems Using Functional Class Scoring

Despite technological advances in proteomics, incomplete coverage and inconsistency issues persist, resulting in “data holes”. These data holes cause the missing protein problem (MPP), where relevant proteins are persistently unobserved, or sporadically observed across samples. This hinders biomarker and drug discovery from proteomics data. Network-based approaches are powerful: The Functional Class Scoring (FCS) method using protein complexes was able to easily recover missed proteins with weak or partial support. However, there are limitations: The verification approach (in determining missing protein recovery) is potentially biased as the test data was based on relatively outdated Data-Dependent Acquisition (DDA) proteomics and FCS does not provide a scoring scheme for individual protein components (in significant complexes). To address these issues: First, we devised a more rigorous evaluation of FCS based on same-sample technical replicates. And second, we evaluate using data from more recent Data-Independent Acquisition (DIA) technologies (viz. SWATH).Although cross-replicate examination reveals some inconsistencies amongst same-class samples, tissue-differentiating signal is nonetheless strongly conserved. This confirms FCS as a viable method that selects biologically meaningful networks. We also report that predicted missing proteins are statistically significant based on FCS p-values. Although cross-replicate verification rates are not spectacular, the predicted missing proteins as a whole, have higher peptide support than non-predicted proteins. FCS also has the capacity to predict missing proteins that are often lost due to weak specific peptide support. As a yet unresolved limitation, we find that FCS cannot assign meaningful probabilities to individual protein components (no relationship between actual probability of verification and FCS-assigned probability) as it only provides a p-value at the level of complexes.

A Bird's-Eye View of Proteomics

: Modern protein science is broadening horizons by moving toward the systemic description of proteins in their natural habitats. This implies a transition from a classical reductionist approach associated with consideration of the unique structure and specific biological activity of an individual protein in a purified form to studying entire proteomes and their functions. This mini-review provides a brief description of structural, functional, and expression proteomics, the dark proteome (or unfoldome), and some of the tools utilized in the analyses of proteomes.

Heterogeneous protein co-assemblies with tunable functional domain stoichiometry

In nature, the precise heterogeneous co-assembly of different protein domains gives rise to supramolecular machines that perform complex functions through the co-integrated activity of the individual protein subunits. A synthetic...

Methods for Identification of Substrates/Inhibitors of FCP/SCP Type Protein Ser/Thr Phosphatases

Protein phosphorylation is the most widespread type of post-translational modification and is properly controlled by protein kinases and phosphatases. Regarding the phosphorylation of serine (Ser) and threonine (Thr) residues, relatively few protein Ser/Thr phosphatases control the specific dephosphorylation of numerous substrates, in contrast with Ser/Thr kinases. Recently, protein Ser/Thr phosphatases were reported to have rigid substrate recognition and exert various biological functions. Therefore, identification of targeted proteins by individual protein Ser/Thr phosphatases is crucial to clarify their own biological functions. However, to date, information on the development of methods for identification of the substrates of protein Ser/Thr phosphatases remains scarce. In turn, substrate-trapping mutants are powerful tools to search the individual substrates of protein tyrosine (Tyr) phosphatases. This review focuses on the development of novel methods for the identification of Ser/Thr phosphatases, especially small C-terminal domain phosphatase 1 (Scp1), using peptide-displayed phage library with AlF4−/BeF3−, and discusses the identification of putative inhibitors.

Single and Combined Methods to Specifically or Bulk-Purify RNA–Protein Complexes

The ribonome interconnects the proteome and the transcriptome. Specific biology is situated at this interface, which can be studied in bulk using omics approaches or specifically by targeting an individual protein or RNA species. In this review, we focus on both RNA- and ribonucleoprotein-(RNP) centric methods. These methods can be used to study the dynamics of the ribonome in response to a stimulus or to identify the proteins that interact with a specific RNA species. The purpose of this review is to provide and discuss an overview of strategies to cross-link RNA to proteins and the currently available RNA- and RNP-centric approaches to study RNPs. We elaborate on some major challenges common to most methods, involving RNP yield, purity and experimental cost. We identify the origin of these difficulties and propose to combine existing approaches to overcome these challenges. The solutions provided build on the recently developed organic phase separation protocols, such as Cross-Linked RNA eXtraction (XRNAX), orthogonal organic phase separation (OOPS) and Phenol-Toluol extraction (PTex).