Using Peptide Arrays To Discover the Sequence-Specific Acetylation of the Histidine-Tyrosine Dyad

Hist-i-fy-a multiple histidine post-translational-modification (PTM) prediction server based on protein sequences using convolution neural network: a case study on mass spectroscopy data

Computational characterization of multiple Histidine (His) post-translational-modifications (PTM) at enzyme active sites complements tedious experimental characterization in proteins-of-unknown-functions (PUFs) and domain-of-unknown-functions (DUFs). There are only a handful of Histidine-PTM-prediction-tools and those also annotate only a single function. Here, we addressed the problem using artificial neural networks on functional histidine dataset curated from enzyme (protein) sequences available in UniProt database (sample size n = 1584). The convolution-neural-network (CNN) model ('Hist-i-fy') performed the best with 75% overall accuracy/F1-score. A case study was performed on histidine-phosphorylation (n = 34) obtained from mass spectroscopy data. For the first time, we report multiple His-PTM-prediction-tool (https://histify.streamlit.app/& https://github.com/dibyansu24-maker/Histify), with optimal performance. The inputs to the tool are (i) protein sequence containing histidine, and (ii) the histidine residue number. Prediction output is one out of the eight histidine functions-acetylation, ribosylation, glycosylation, hydroxylation, methylation, oxidation, phosphorylation, and protein splicing.Communicated by Ramaswamy H. Sarma.

Comprehensive Epitope Analysis of Monoclonal Antibodies Binding to Hen Egg Ovalbumin Using a Peptide Array

Food allergies are a significant health issue worldwide. In many countries, labeling of primary allergens in food products has been made mandatory to ensure consumer safety. In food manufacturing settings, the lateral flow immunoassay (LFI)-based on antigen-antibody reactions-is a rapid and accurate method for allergen testing and is widely used. Peptide arrays are tools that enable the synthesis of peptides of any sequence on a substrate and high-throughput analysis of their interactions with chemicals. This study aimed to investigate a new application of peptide arrays in the field of food technology, particularly in the development of antibodies for food allergen testing. First, monoclonal antibodies against hen egg ovalbumin, a major food allergen, were produced. Then, using a peptide array, the epitope and specificity of the antibodies were comprehensively and precisely analyzed. Finally, an LFI kit incorporating the antibodies demonstrated both high specificity and detection sensitivity for food allergen testing. These findings indicate that peptide arrays are valuable tools in the development of antibodies for food allergen testing, ensuring reliability and accuracy at the molecular level.

Mass tag-encoded nanointerfaces for multiplexed mass spectrometric analysis and imaging of biomolecules

Revealing multiple biomolecules in the physiopathological environment simultaneously is crucial in biological and biomedical research. Mass spectrometry (MS) features unique technical advantages in multiplexed and label-free analyses. However, owing to comparably low abundance and poor ionization efficiency of target biomolecules, direct MS profiling of these biological species in vitro or in situ remains a challenge. An emerging route to solve this issue is to devise mass tag (MT)-encoded nanointerfaces which specifically convert the abundance or activity of biomolecules into amplified ion signals of mass tags, offering an ideal strategy for synchronous MS assaying and mapping of multiple targets in biofluids, cells and tissues. This review provides a thorough and organized overview of recent advances in MT-encoded nanointerfaces elaborately tailored for several practical applications in multiplexed MS bioanalysis and biomedical research. First, we start with elucidation of the structural characteristics and working principle of MT-encoded nanointerfaces in specific labeling and sensing of multiple biological targets. In addition, we further discuss the application scenarios of MT-encoded nanointerfaces particularly in multiplexed biomarker assays, cell analysis, and tissue imaging. Finally, the current challenges are pointed out and future prospects of these nanointerfaces in MS analysis are forecast.

Efficient Enzymatic Incorporation of Dehydroalanine Based on SAMDI-Assisted Identification of Optimized Tags for OspF/SpvC

Site-specific modification of proteins has important applications in biological research and drug development. Reactive tags such as azide, alkyne, and tetrazine have been used extensively to achieve the abovementioned goal. However, bulky side-chain "ligation scars" are often left after the labeling and may hinder the biological application of such engineered protein products. Conjugation chemistry via dehydroalanine (Dha) may provide an opportunity for "traceless" ligation because the activated alkene moiety on Dha can then serve as an electrophile to react with radicalophile, thiol/amine nucleophile, and reactive phosphine probe to introduce a minimal linker in the protein post-translational modifications. In this report, we present a mild and highly efficient enzymatic approach to incorporate Dha with phosphothreonine/serine lyases, OspF and SpvC. These lyases originally catalyze an irreversible elimination reaction that converts a doubly phosphorylated substrate with phosphothreonine (pT) or phosphoserine (pS) to dehydrobutyrine (Dhb) or Dha. To generate a simple monophosphorylated tag for these lyases, we conducted a systematic approach to profile the substrate specificity of OspF and SpvC using peptide arrays and self-assembled monolayers for matrix-assisted laser desorption/ionization mass spectrometry. The optimized tag, [F/Y/W]-pT/pS-[F/Y/W] (where [F/Y/W] indicates an aromatic residue), results in a ∼10-fold enhancement of the overall peptide labeling efficiency via Dha chemistry and enables the first demonstration of protein labeling as well as live cell labeling with a minimal ligation linker via enzyme-mediated incorporation of Dha.

Deconvoluting complex protein interaction networks through reductionist strategies in peptide biochemistry: Modern approaches and research questions

Following the decoding of the first human genome, researchers have vastly improved their understanding of cell biology and its regulation. As a result, it has become clear that it is not merely genetic information, but the aberrant changes in the functionality and connectivity of its encoded proteins that drive cell response to periods of stress and external cues. Therefore, proper utilization of refined methods that help to describe protein signalling or regulatory networks (i.e., functional connectivity), can help us understand how change in the signalling landscape effects the cell. However, given the vast complexity in 'how and when' proteins communicate or interact with each other, it is extremely difficult to define, characterize, and understand these interaction networks in a tangible manner. Herein lies the challenge of tackling the functional proteome; its regulation is encoded in multiple layers of interaction, chemical modification and cell compartmentalization. To address and refine simple research questions, modern reductionist strategies in protein biochemistry have successfully used peptide-based experiments; their summation helping to simplify the overall complexity of these protein interaction networks. In this way, peptides are powerful tools used in fundamental research that can be readily applied to comparative biochemical research. Understanding and defining how proteins interact is one of the key aspects towards understanding how the proteome functions. To date, reductionist peptide-based research has helped to address a wide range of proteome-related research questions, including the prediction of enzymes substrates, identification of posttranslational modifications, and the annotation of protein interaction partners. Peptide arrays have been used to identify the binding specificity of reader domains, which are able to recognise the posttranslational modifications; forming dynamic protein interactions that are dependent on modification state. Finally, representing one of the fastest growing classes of inhibitor molecules, peptides are now begin explored as "disruptors" of protein-protein interactions or enzyme activity. Collectively, this review will discuss the use of peptides, peptide arrays, peptide-oriented computational biochemistry as modern reductionist strategies in deconvoluting the functional proteome.

Exploring the Ligand Preferences of the PHD1 Domain of Histone Demethylase KDM5A Reveals Tolerance for Modifications of the Q5 Residue of Histone 3

Understanding the ligand preferences of epigenetic reader domains enables identification of modification states of chromatin with which these domains associate and can yield insight into recruitment and catalysis of chromatin-acting complexes. However, thorough exploration of the ligand preferences of reader domains is hindered by the limitations of traditional protein-ligand binding assays. Here, we evaluate the binding preferences of the PHD1 domain of histone demethylase KDM5A using the protein interaction by SAMDI (PI-SAMDI) assay, which measures protein-ligand binding in a high-throughput and sensitive manner via binding-induced enhancement in the activity of a reporter enzyme, in combination with fluorescence polarization. The PI-SAMDI assay was validated by confirming its ability to accurately profile the relative binding affinity of a set of well-characterized histone 3 (H3) ligands of PHD1. The assay was then used to assess the affinity of PHD1 for 361 H3 mutant ligands, a select number of which were further characterized by fluorescence polarization. Together, these experiments revealed PHD1's tolerance for H3Q5 mutations, including an unexpected tolerance for aromatic residues in this position. Motivated by this finding, we further demonstrate a high-affinity interaction between PHD1 and recently identified Q5-serotonylated H3. This work yields interesting insights into permissible PHD1-H3 interactions and demonstrates the value of interfacing PI-SAMDI and fluorescence polarization in investigations of protein-ligand binding.

A high-throughput SAMDI-mass spectrometry assay for isocitrate dehydrogenase 1

The enzyme isocitrate dehydrogenase 1 (IDH1) catalyzes the conversion of isocitrate to alpha-ketoglutarate (αKG) and has emerged as an important therapeutic target for glioblastoma multiforme (GBM). Current methods for assaying IDH1 remain poorly suited for high-throughput screening of IDH1 antagonists. This paper describes a high-throughput and quantitative assay for IDH1 that is based on the self-assembled monolayers for matrix-assisted laser desorption/ionization-mass spectrometry (SAMDI-MS) method. The assay uses a self-assembled monolayer presenting a hydrazide group that covalently captures the αKG product of IDH1, where it can then be detected by MALDI-TOF mass spectrometry. Co-capture of an isotopically-labeled αKG internal standard allows the αKG concentration to be quantitated. The assay was used to analyze a series of standard αKG solutions and produced minimal error in measured αKG concentration values. The suitability of the assay for high-throughput analysis was evaluated in a 384-sample biochemical IDH1 screen. Cells expressing IDH1 were lysed and the lysate was applied to the monolayer to capture αKG, which was then quantitated using the SAMDI-MS assay. Cells in which IDH1 expression was reduced by small-interfering RNA exhibited a corresponding decrease in αKG concentration as measured by the assay. Application of the assay toward the high-throughput screening of IDH1 inhibitors or knockdown agents may facilitate the discovery of treatments for GBM.