Comprehensive mutagenesis identifies the peptide repertoire of a p53 T-cell receptor mimic antibody that displays no toxicity in mice transgenic for human HLA-A*0201

T-cell receptor mimic (TCRm) antibodies have expanded the repertoire of antigens targetable by monoclonal antibodies, to include peptides derived from intracellular proteins that are presented by major histocompatibility complex class I (MHC-I) molecules on the cell surface. We have previously used this approach to target p53, which represents a valuable target for cancer immunotherapy because of the high frequency of its deregulation by mutation or other mechanisms. The T1-116C TCRm antibody targets the wild type p5365-73 peptide (RMPEAAPPV) presented by HLA-A*0201 (HLA-A2) and exhibited in vivo efficacy against triple receptor negative breast cancer xenografts. Here we report a comprehensive mutational analysis of the p53 RMPEAAPPV peptide to assess the T1-116C epitope and its peptide specificity. Antibody binding absolutely required the N-terminal arginine residue, while amino acids in the center of the peptide contributed little to specificity. Data mining the immune epitope database with the T1-116C binding consensus and validation of peptide recognition using the T2 stabilization assay identified additional tumor antigens targeted by T1-116C, including WT1, gp100, Tyrosinase and NY-ESO-1. Most peptides recognized by T1-116C were conserved in mice and human HLA-A2 transgenic mice showed no toxicity when treated with T1-116C in vivo. We conclude that comprehensive validation of TCRm antibody target specificity is critical for assessing their safety profile.

Context contribution to the intermolecular recognition of human ACE2-derived peptides by SARS-CoV-2 spike protein: implications for improving the peptide affinity but not altering the peptide specificity by optimizing indirect readout

Disrupting the intermolecular interaction of SARS-CoV-2 S protein with its cell surface receptor hACE2 is a therapeutic strategy against COVID-19. The protein context plays an essential role in hACE α1-helix recognition by viral S protein.

AGC kinase members phosphorylate ubiquitin

The posttranslational modification of proteins with ubiquitin controls most cellular processes, such as protein degradation or transport, cell signaling, or transcription1–5. Ubiquitin can be phosphorylated at multiple sites, which likely further modulates the function of protein ubiquitination6,7. However, except for PINK18–10, the kinases involved in ubiquitin phosphorylation remain unknown, which hampers our understanding of phospho-ubiquitin signaling. In this study, we performed genome-wide in vitro kinase screenings and discovered that AGC kinases phosphorylate ubiquitin. Ubiquitin phosphorylation by members of the PKA, PKC, PKG and RSK families as well as by less well-characterized kinases, such as SGK2, was not solely dependent on peptide specificity but required additional kinase recruitment to ubiquitin. The stabilization of the kinase interaction with ubiquitin resulted in phosphorylation of suboptimal kinase motifs on ubiquitin, suggesting that ubiquitin phosphorylation is dictated primarily through the recruitment of kinases to the ubiquitinated proteins. Hence, we identify AGC kinase members as enzymes that can phosphorylate ubiquitin in a mechanism regulated by protein interactions outside of the catalytic kinase domain and are only applicable to specific subsets of ubiquitinated proteins.

PeSA: A Software Tool for Peptide Specificity Analysis

ABSTRACTThe discovery of molecular interactions is crucial towards a better understanding of complex biological functions. Particularly protein-protein interactions (i.e., PPIs), which are responsible for a variety of cellular functions from epigenetic modifications to enzyme-substrate specificity, have been studied extensively over the past decades. Position-specific scoring matrices (PSSM) in particular are used extensively to help determine interaction specificity or candidate interaction motifs. However, not all studies successfully report their results as a candidate interaction motif. In many cases, this is the result of a lack of analysis tools for simple analysis and motif generation. Peptide Specificity Analyst (PeSA) is developed with the goal of filling this gap and providing an analysis software to aid peptide array analysis and subsequent motif generation. PeSA utilizes two models of motif creation: (1) frequency-based using a peptide list, and (2) weight-based using a quantified matrix. The ability to generate motifs effortlessly will make analyzing, interpreting and sharing peptide specificity study results in a simple and straightforward process.GRAPHICAL ABSTRACTHIGHLIGHTSBiological motifs are widely used representations for peptide specificity analysis.PeSA populates a list of peptides matching a set threshold from a quantified matrix.Frequency-based motif using a peptide list to spot residue patterns.Use of quantified matrices to create weight-based motifs using residue positions.

A bacterial display system for effective selection of protein-biotin ligase BirA variants with novel peptide specificity

Biotinylation creates a sensitive and specific tag for purification and detection of target proteins. TheE. coliprotein-biotin ligase BirA biotinylates a lysine within a synthetic biotin acceptor peptide (AP) and allow for specific tagging of proteins fused to the AP. The approach is not applicable to unmodified proteins, and we sought to develop an effective selection system that could form the basis for directed evolution of novel BirA variants with specificity towards unmodified proteins. The system was based on bacterial display of a target peptide sequence, which could be biotinylated by cytosolic BirA variants before being displayed on the surface. In a model selection, the bacterial display system accomplished >1.000.000 enrichment in a single selection step. A randomly mutated BirA library was used to identify novel variants. Bacteria displaying peptide sequences from 13 out of 14 tested proteins were strongly enriched after 3–5 selection rounds. Moreover, a clone selected for biotinylation of a C-terminal peptide from red-fluorescent protein TagRFP showed site-specific biotinylation. Thus, active BirA variants with novel specificity are effectively isolated with our bacterial display system and provides a basis for the development of BirA variants for site-selective biotinylation.

Affinity Purification and Comparative Biosensor Analysis of Citrulline-Peptide Specific Antibodies in Rheumatoid Arthritis

Background: In rheumatoid arthritis (RA), anti-citrullinated protein/peptide antibodies (ACPAs) are responsible for disease onset and progression, however, our knowledge is limited on ligand binding affinities of autoantibodies with different citrulline-peptide specificity. Methods: Citrulline-peptide specific ACPA IgGs were affinity purified and tested by ELISA. Binding affinities of ACPA IgGs and serum antibodies were compared by surface plasmon resonance (SPR) analysis. Bifunctional nanoparticles harboring a multi-epitope citrulline-peptide and a complement activating peptide were used to induce selective depletion of ACPA producing B cells. Results: KD values of affinity purified ACPA IgGs varies between 10-6-10-8 M and inversely correlate with disease activity. Based on their cross-reaction with citrulline-peptides we designed a novel multi-epitope peptide, containing Cit-Gly and Ala-Cit motifs in two-two copies, separated with a short, neutral spacer. This peptide detects antibodies in RA sera with 66 % sensitivity and 98 % specificity in ELISA and is recognized by 90% of RA sera, while none of the healthy samples in SPR. When coupled to nanoparticles, the multi-epitope peptide specifically targets and depletes ACPA producing B cells ex vivo. Conclusions: The unique multi-epitope peptide designed on the basis of ACPA cross-reactivity might be suitable to develop better diagnostics and novel therapies for RA.