Proteomics Overview and Structure

Proteomics Overview

• Proteomics is the study of proteins and their interactions, function, composition, and structures.
• It provides a deeper understanding of an organism's structure and function compared to genomics alone.
• Proteomics has applications in disease biomarker identification. It has quickly developed, especially in the therapeutics field.
• Proteomics involves examining protein characterization and interactions, similar to how genomics studies genes.
• The term "proteome" was coined by Marc Wilkins in 1995.

Levels of Protein Structure

• Primary Structure: Determined by the sequence of amino acids.
• Secondary Structure: Forms when amino acids bond through hydrogen bonds (e.g., alpha helix, pleated sheet.).
• Tertiary Structure: 3D shape of a protein, formed by interactions between amino acid side chains.
• Quaternary Structure: The structure of a protein with more than one polypeptide chain.

Types of Proteomics

• Expression proteomics studies the qualitative and quantitative expression levels of proteins under different conditions (e.g., normal vs. diseased cells).
• Structural proteomics aims to understand a protein's 3D shape and structural complexities. It can be determined by amino acid sequences or homology modeling.
• Functional proteomics focuses on protein functions and molecular mechanisms within the cell that rely on interactions between proteins. This is important for evaluating cellular signaling pathways.

Importance of Proteomics

• Proteomics is vital since proteins, not genes, control a cell's traits (phenotypes).
• Understanding diseases, aging, and environmental effects requires studying proteins, not just genes.

Proteomics Tools and Methods

• Conventional Techniques: Chromatography, western blotting, size exclusion, ion exchange, affinity techniques.
• In silico Methods: Computer-based analyses, using databases.
• Advanced Techniques: Mass spectrometry (MS), 2D electrophoresis, protein microarrays, X-ray crystallography, NMR spectroscopy. This includes quantitative techniques like ICAT, SILAC and iTRAQ
• Protein Analysis Techniques: includes techniques like 2D-DIGE, Tandem MS and Edman sequencing
• Quantification Techniques: quantitative mass spectrometry tools such as ICAT, SILAC and iTRAQ
• Purification Techniques: Purification techniques for proteomic analysis may include chromatography based approaches
• Proteomics data analysis requires specialized databases to manage and analyze the high volume of data.

Methods of Proteomics

• Mass spectrometry: Techniques used, including Tandem-MS (MS/MS), and differential in-gel electrophoresis (DIGE).
• High-throughput technologies are important for in-depth proteome investigation and high volumes of data
• Databases: crucial for properly storing and processing data.

2D Gel Electrophoresis

• An established technique for high-resolution protein profiling. It separates proteins based on their isoelectric point (pI).
• 2D gel electrophoresis widely used in proteomics profiling to study changes in protein expression due to diseases or treatments.
• 2DE also helps in identifying and studying post-translational modifications and protein isoforms.

In silico Approach

• EMBL-EBI: Hosts up-to-date databases for proteomics research.
• Databases: UniProtKB, IntAct, Reactome, PRIDE, AlphaFold Protein Structure Database are some of the major databases used for proteomics. These databases rely on and utilize other databases for information like Ensembl and InterPro for annotation and data.

UniProtKB Database

• A key resource for protein sequence and functional information.
• The UniProtKB consists of two sections: UniProtKB/Swiss-Prot (manually curated) and UniProtKB/TrEMBL (computationally analyzed).
• Useful in finding proteins information by searching, searching and retrieving information about genes or proteins from the EMBL-EBI database using search input.

AlphaFold Protein Structure Database

• A deep learning based, artificial intelligence program for protein structure prediction to analyze the structures of proteins

Comparisons between RNA-Seq and Proteomics Data

• RNA-Seq's sample-specific protein databases help approximate real protein pools, improving protein identification.
• Proteomics data confirms the validity and functional relevance of novel findings from RNA-Seq.

Traditional vs RNA-Seq Proteogenomics

• Traditional Proteogenomics focuses on the genome to understand protein expression.
• RNA-Seq-based proteogenomics leverages transcriptome data (RNA-Seq) to gain a clearer picture of the proteomes.