Computational prediction of protein-protein interactions Rong Liu 2014-04-22.

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Presentation transcript:

Computational prediction of protein-protein interactions Rong Liu

Quaternary structure

Types of protein-protein interactions Homo-oligomers vs. hetero-oligomers Permanent vs. transient interactions Strong transient Weak transient Covalent vs. non-covalent interactions Classification based on function enzyme-inhibitor antibody-antigen Others (e.g. hormone-receptor, signaling-effector)

Experimental methods to detect PPI Yeast two hybrid (Y2H) Tandem affinity purification coupled to mass spectrometry (TAP-MS) Co-inmunoprecipitation (CoIP) Protein microarrays Phage display Surface plasmon resonance ……

Reliability of high-throughput methods

PPI database

A sample of DIP protein table

List of interacting partners

Graphic representation of interactions Nodes are proteins Edges are PPIs The center node is DIP:1143N Edge width encodes the number of independent experiments identifying the interactions. Green (red) is used to draw core (unverified) interactions. Click on each node (edge) to know more about the protein (interaction).

Techniques to study the protein complex structures X-ray crystallography Nuclear magnetic resonance spectroscopy Electron Microscopy

Header of PDB file

Format of PDB file

Preparation of PPI and non-PPI datasets PPI dataset (Gold standard dataset) Data from multiple database At least two separate publications Each of these publications needs to have a binary evidence code Non-PPI dataset Random selection from all possible protein pairs Proteins come from different sub-localization

The first non-PPI database

PPI prediction based on homology

InParanoid8

Genome context-based methods

Domain association-based method

Domain combination

Machine learning-based method

Feature representation of amino acid sequences

Protein feature server

Validation of the predicted PPIs

Protein-protein binding interface

Hotspots in binding interface (ΔΔG >2kcal/mol)

Definition of binding interface Define surface residue (DSSP, NACCESS) Define interface residue Distance-based method Solvent accessible surface area-based method

Format of DSSP file

Characteristics analysis of binding interface

Features of transient and obligate interactions

Features used to predict PPI binding interface Sequence conservation Propensity of residue types in binding regions Secondary structure Solvent accessibility Protrusion index Side-chain conformational entropy

Position specific scoring matrix and neighborhood

Training and testing Cross-validation and independent test Balanced positive and negative samples Evaluation measures

State-of-the-arts of feature-based prediction

Similarity between binding interfaces

Protein interface conservation across structure space

Performance comparison between different algorithms

Hybrid method

Residue interaction network

Network-based features Degree centrality Closeness centrality Betweenness centrality Clustering coefficient

Protein complexes and small-world networks

Network-based features of other binding sites

Graph-based interface alignment

InterPreTS: protein Interaction Prediction through Tertiary Structure

Structure-based prediction of protein–protein interactions on a genome-wide scale

Protein Docking

Procedure of protein docking

Search of conformations

Scoring function

Docking programs and benchmark

Evaluation measures

Structure visualization tools FeatureRasMolCn3DPyMolSWISS- PDBViewer Chimera ArchitectureStand-AlonePlug-inStand-AloneWeb-enabled Manipulation Power LowHigh Hardware Requirements Low/ModerateHigh ModerateHigh Ease of UseHigh; command line Moderate HighModerate;GUI +command line Special FeaturesSmall Size; easy install Powerful GUI GUI; ray tracing Powerful GUIGUI; collaboration Output QualityModerateVery highHigh Very high DocumentationGood LimitedGoodVery good SupportOnline; Users groups SpeedHighModerate Moderate/Slow OpenGL SupportYes

Pymol

Application of PPI network