🧬Proteomics Unit 7 – Post–Translational Modifications

What Are Post-Translational Modifications?

• Involve covalent modifications to proteins after they have been synthesized by ribosomes
• Expand the functional diversity of the proteome by modifying existing proteins
• Occur on amino acid side chains or at the N- or C-termini of proteins
• Regulate protein function, localization, stability, and interactions with other molecules
• Can be reversible (phosphorylation) or irreversible (proteolytic cleavage)
  • Reversible modifications allow for dynamic control of protein function
  • Irreversible modifications permanently alter protein structure and function
• Mediated by enzymes such as kinases, phosphatases, and transferases
• Respond to various cellular signals and environmental cues (growth factors, stress)

Common Types of PTMs

• Phosphorylation involves the addition of a phosphate group to serine, threonine, or tyrosine residues
  • Catalyzed by protein kinases and reversed by phosphatases
  • Regulates protein activity, interactions, and signaling cascades (MAPK pathway)
• Glycosylation attaches carbohydrate moieties to asparagine (N-linked) or serine/threonine (O-linked) residues
  • Affects protein folding, stability, and cell-cell interactions (cell surface receptors)
• Ubiquitination covalently attaches ubiquitin to lysine residues
  • Targets proteins for degradation by the proteasome or alters their function
• Acetylation adds an acetyl group to lysine residues
  • Modulates protein-DNA interactions and gene expression (histone acetylation)
• Methylation occurs on lysine or arginine residues
  • Regulates gene expression, protein-protein interactions, and signal transduction
• Lipidation attaches lipid moieties to proteins (myristoylation, palmitoylation)
  • Facilitates membrane anchoring and protein trafficking
• Proteolytic cleavage removes specific peptide sequences from proteins
  • Activates or inactivates proteins (prohormone processing, caspase activation)

Mechanisms of PTMs

• Enzymatic catalysis by specific enzymes (kinases, phosphatases, transferases)
  • Enzymes recognize specific consensus sequences or structural motifs on target proteins
  • Catalytic activity is regulated by cellular signals and protein-protein interactions
• Co-translational modifications occur as the protein is being synthesized by the ribosome
  • Examples include N-terminal acetylation and signal peptide cleavage
• Post-translational modifications take place after protein synthesis is complete
  • Occur in various cellular compartments (cytosol, nucleus, endoplasmic reticulum)
• Reversibility of some PTMs allows for dynamic regulation of protein function
  • Phosphorylation is reversible through the action of phosphatases
  • Acetylation is reversed by deacetylases (sirtuins)
• Crosstalk between different PTMs can fine-tune protein function
  • Phosphorylation can regulate the activity of other PTM enzymes (ubiquitin ligases)
• PTMs can create binding sites for specific protein domains
  • Phosphorylated tyrosine residues are recognized by SH2 domains
  • Ubiquitinated lysine residues are bound by ubiquitin-binding domains (UBDs)

PTM Detection Methods

• Mass spectrometry is a powerful tool for identifying and quantifying PTMs
  • Tandem mass spectrometry (MS/MS) allows for peptide sequencing and PTM localization
  • Quantitative approaches (SILAC, TMT) enable comparison of PTM levels between samples
• Antibody-based methods specifically detect modified proteins
  • Western blotting using PTM-specific antibodies (phospho-specific, acetyl-specific)
  • Immunoprecipitation enriches for modified proteins prior to analysis
• Enzymatic assays measure the activity of PTM enzymes (kinase assays)
• Bioinformatic prediction tools identify potential PTM sites based on sequence motifs
  • Scansite predicts kinase and phosphatase substrates
  • NetPhos predicts serine, threonine, and tyrosine phosphorylation sites
• Functional assays assess the biological consequences of PTMs
  • Site-directed mutagenesis of PTM sites
  • Use of PTM enzyme inhibitors or activators
• Imaging techniques visualize the spatial distribution of modified proteins
  • Immunofluorescence microscopy using PTM-specific antibodies
  • Förster resonance energy transfer (FRET) sensors for real-time monitoring of PTMs

Biological Significance of PTMs

• Regulate protein activity, stability, localization, and interactions
  • Phosphorylation can activate or inactivate enzymes (kinases, phosphatases)
  • Ubiquitination targets proteins for degradation by the proteasome
• Modulate signal transduction pathways and cellular responses
  • Phosphorylation cascades amplify and propagate signals (MAPK pathway)
  • Acetylation of transcription factors regulates gene expression (p53)
• Control cell cycle progression and cell division
  • Phosphorylation of cyclin-dependent kinases (CDKs) regulates their activity
  • Ubiquitination of cyclins targets them for degradation at specific cell cycle stages
• Mediate protein-protein interactions and complex formation
  • Phosphorylation creates binding sites for SH2 and PTB domains
  • Acetylation regulates the assembly of transcriptional complexes
• Influence protein folding, stability, and degradation
  • Glycosylation assists in protein folding and enhances stability
  • N-terminal acetylation protects proteins from degradation
• Regulate subcellular localization and trafficking
  • Myristoylation and palmitoylation target proteins to membranes
  • Phosphorylation can induce nuclear translocation of transcription factors
• Coordinate complex biological processes (development, differentiation, apoptosis)
  • Proteolytic cleavage of Notch receptors is essential for cell fate determination
  • Caspase activation by cleavage triggers apoptotic cell death

PTMs in Disease

• Dysregulation of PTMs contributes to various pathological conditions
  • Cancer is associated with aberrant phosphorylation and ubiquitination patterns
  • Neurodegenerative disorders (Alzheimer's, Parkinson's) involve altered protein aggregation and degradation
• Mutations in PTM enzymes or their substrates can lead to disease
  • Mutations in kinases (EGFR, BCR-ABL) are oncogenic drivers in cancer
  • Parkinson's disease is linked to mutations in the E3 ubiquitin ligase Parkin
• PTMs can modulate the activity of disease-associated proteins
  • Hyperphosphorylation of tau protein contributes to neurofibrillary tangles in Alzheimer's
  • Acetylation of the tumor suppressor p53 regulates its stability and function
• Infectious agents exploit host PTM machinery
  • HIV-1 Tat protein is acetylated to enhance viral transcription
  • Influenza virus NS1 protein is phosphorylated to evade host immune responses
• PTMs are potential therapeutic targets for disease intervention
  • Kinase inhibitors (imatinib, erlotinib) are used to treat various cancers
  • Histone deacetylase (HDAC) inhibitors are being explored for cancer and neurological disorders
• Biomarkers based on PTMs can aid in disease diagnosis and prognosis
  • Phosphorylated tau and β-amyloid are biomarkers for Alzheimer's disease
  • Glycosylation patterns of serum proteins are altered in cancer and inflammatory conditions

Computational Tools for PTM Analysis

• Databases curate experimentally validated and predicted PTM sites
  • UniProt provides a comprehensive resource for protein sequences and annotations
  • PhosphoSitePlus catalogs experimentally observed phosphorylation, acetylation, and other PTMs
• Sequence analysis tools predict potential PTM sites based on consensus motifs
  • Scansite identifies kinase, phosphatase, and other enzyme substrates
  • NetPhos and NetAcet predict phosphorylation and acetylation sites, respectively
• Structural bioinformatics tools analyze the impact of PTMs on protein structure and interactions
  • PyMOL and Chimera visualize PTMs in the context of 3D protein structures
  • Molecular dynamics simulations investigate the effects of PTMs on protein dynamics
• Network analysis tools explore the systems-level impact of PTMs
  • Cytoscape enables visualization and analysis of PTM-mediated interaction networks
  • PTMcode investigates the functional associations between PTM sites within proteins
• Data integration platforms combine PTM data from various sources
  • PTMfunc integrates PTM data with functional annotations and protein-protein interactions
  • dbPTM provides a comprehensive database of experimentally verified and predicted PTMs
• Machine learning algorithms predict PTM sites and their functional consequences
  • Support vector machines (SVMs) and neural networks are used for PTM site prediction
  • Deep learning approaches (convolutional neural networks) improve prediction accuracy
• Tools for quantitative analysis of PTM data from mass spectrometry experiments
  • MaxQuant and Perseus enable quantification and statistical analysis of PTM data
  • Skyline facilitates targeted quantification of PTMs using selected reaction monitoring (SRM)

Future Directions in PTM Research

• Develop more sensitive and high-throughput methods for PTM detection
  • Improve mass spectrometry instrumentation and data acquisition strategies
  • Develop novel affinity reagents (aptamers, nanobodies) for PTM enrichment
• Investigate the crosstalk and interplay between different PTMs
  • Study how PTMs influence each other and coordinate protein function
  • Develop computational models to predict PTM crosstalk and its biological consequences
• Characterize the spatio-temporal dynamics of PTMs in living cells
  • Advance live-cell imaging techniques to monitor PTMs in real-time
  • Develop genetically encoded biosensors for specific PTMs (FRET-based sensors)
• Explore the role of PTMs in regulating protein-protein interaction networks
  • Map PTM-dependent protein interaction landscapes using proximity labeling and mass spectrometry
  • Integrate PTM data with protein interaction databases to infer functional consequences
• Elucidate the mechanisms of PTM dysregulation in disease
  • Investigate the molecular basis of altered PTM patterns in cancer, neurodegeneration, and other disorders
  • Identify novel disease-associated PTM sites and their functional impact
• Develop targeted therapies that modulate PTM enzymes or substrates
  • Design small molecule inhibitors or activators of PTM enzymes
  • Exploit PTM-dependent protein interactions as therapeutic targets
• Integrate PTM data with other omics data (genomics, transcriptomics, metabolomics)
  • Develop multi-omics approaches to understand the systems-level impact of PTMs
  • Use machine learning to integrate diverse data types and predict PTM-mediated biological outcomes
• Establish standardized protocols and data formats for PTM research
  • Develop guidelines for PTM data acquisition, analysis, and reporting
  • Create centralized repositories for PTM data sharing and meta-analysis