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Learning Objectives
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Learning Objectives
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Now · 1. Experimental Methods
Learning Objectives
- Understand PPI networks construction
- Know experimental methods (Y2H, Co-IP, AP-MS)
- Analyze PPI for functional insights
1. Experimental Methods
Yeast Two-Hybrid (Y2H): Test interaction between two proteins. High-throughput, high false positives. Co-immunoprecipitation (Co-IP): Pull down complex with antibody, identify partners by MS. Lower throughput, higher confidence. TAP-Tag / AP-MS: Tag expressed protein, purify complex, identify members. Good for stable complexes.
2. PPI Databases
STRING (known + predicted), BioGRID (curated), IntAct, DIP.
3. Analyzing PPI Networks
Protein Complexes: Dense subgraphs (MCODE algorithm). Hub Types: Party hubs (simultaneous interactions in complexes), Date hubs (different times/locations). Guilt-by-Association: Unknown protein interacting with known process proteins likely functions in same process.
Q1: Y2H vs Co-IP?Y2H: binary interactions in yeast cells, high throughput, false positives. Co-IP: native complexes, lower throughput, higher confidence. Q2: Party hubs vs date hubs?Party: interact simultaneously (complexes), high co-expression with partners. Date: interact at different times (coordination), modular expression. Q3: How does guilt-by-association work?If uncharacterized protein interacts with proteins functioning in process X, the new protein likely also functions in X. Network neighbors share functions. Q4: What is STRING?Database integrating PPIs from: experiments, curated databases, text mining, co-expression, genomic context. Scores combined into confidence score per interaction. Q5: How do PPI networks help understand disease?Mutations often disrupt interactions. Disease proteins cluster in network modules (disease modules). Proximity helps identify new disease genes and drug targets. Join Discord PreviousNetwork Properties & MetricsNextGene Regulatory Networks