protein-protein interaction

insilico protein structure prediction and and structure analysis and its type which are commonly used in dry lab. docking is a procedure in which two protein,or protein to ligand binding intrection analysis by software tools.

1. PROTEIN-PROTEIN INTERACTIONs By Zeshan Haider,

2. “Protein–protein interactions (PPIs) are the physical contacts of high specificity, established between two or more protein molecules.” These are due to biochemical events steered by electrostatic forces including the hydrophobic effect.” Many are physical contacts with molecular associations between chains that occur in a cell or in a living organism in a specific biomolecular context. Aberrant PPIs are the basis of multiple aggregation-related diseases, such as Creutzfeldt–Jakob, Alzheimer's disease, and may lead to cancer. PPIs have been studied from different perspectives: biochemistry, quantum chemistry, molecular dynamics, signal transduction .

3. Examples of protein-protein interactions Signal Transduction: activity of cells is regulated through this way in form of extracellular signals Transport across cell membrane: a protein may be carrying another protein Cell metabolism: In many metabolic pathways different proteins interact to perform a specific function. Muscles contraction: myosin filaments act as molecular motors and by binding to actin enable filament sliding

4. Protein –Protein interactions in Signal transduction & Transport across cell membrane

5. Protein–Protein interactions in cell metabolism

6. Protein –Protein interactions in Muscles contraction

7. Types of Protein-Protein interactions Hetro-oligomers Homo-oligomers Transient Stable Covalent noncovalent Based on composition Based on bonding Based on time interval

8. PPI based on the composition Homo-oligomers ‘’One type of protein subunits which constitute macromolecular complexes” e.g . PPIs during muscle contraction Several enzymes, carrier proteins, transcriptional regulatory factors carry out their function as homo-oligomers Hetro-oligomers Distinct protein subunits interact in Hetro-oligomers which are essential to control several cellular functions e.g. PPI b/w cytochrome oxidase TRPC3

9. PPI based on duration of interaction Transient interactions: “Interaction that last for a shorter period.” Mostly reversible in manner. e.g. G-protein coupled receptors Stable interactions: “Protein interaction for a longer period” a stable complex of proteins is formed. Mainly structural roles in cells e.g. Cytochrome C

10. PPI based on Bonding Covalent Strongest bond Disulphide bond or electron sharing e.g. Ubiquitination & sumoylation Non-covalent Weak bonds Transient interaction H-bonds Ionic interactions Wander Waal forces Hydrophobic bonds

11. PPIs identification Approaches/Methods. In-Vivo (experimental) Yeast two-hybrid system Split ubiquitin system Split lactamase system In-Vitro (experimental) In-Silico (computational) Co-Immunoprecipitation Tagged fusion proteins X-ray diffraction structured based approach. Sequence based approach

12. In silico method for protein protein interactions

13. History " In silico " was briefly challenged by " in silicium ," which is correct Latin for "in silicon". The Latin term for silicon,  silicium , was created at the beginning of the 19th century by Berzelius. he expression  in silico  was first used in public in 1989 in the workshop in Los Alamos, New Mexico

14. In silico  has been used in white papers written to support the creation of bacterial genome programs by the Commission of the European Community. The first referenced paper where " in silico " appears was written by a French team in 1991.  The first referenced book chapter where " in silico " appears was written by Hans B. Sieburg in 1990 and presented during a Summer School on Complex Systems at the Santa Fe Institute The phrase " in silico " originally applied only to computer simulations that modeled natural or laboratory processes (in all the natural sciences), and did not refer to calculations done by computer generically.

15. IN SILICO Structure-based approaches Gene neighbor hood In silico 2 hybrid (I2H) Phylogenetic tree Phylogenetic profile Gene fusion Gene expression Sequence-Based Prediction Approaches Ortholog-based sequence approach Domain-pairs-based sequence approach

16. Structure-based approaches Structure-based approaches predict protein-protein interaction if two proteins have a similar structure(primary, secondary, or tertiary ) Protein A Protein B + complex Protein A and protein B have similar structure.

17. Sequence-Based Prediction Approaches Predictions of PPIs have been carried out by integrating evidence of known interactions with information regarding sequential homology. This approach is based on the concept that an interaction found in one species can be used to infer the interaction in other species . Ortholog-based sequence approach. Ortholog based sequence approach based on the Homologous nature of the query protein in the annotated protein data bases using pair wise local sequence algorithm. 2. Domain-pairs-based sequence approach. Domain-pairs-based approach predicts protein interactions based on domain-domain interactions .

18. Gene neighbor hood If the gene neighbor hood is conserved across multiple genomes, then there is a potential possibility of the functional linkage among the proteins encoded by the related genes.

19. Gene Fusion Gene fusion, which is often called as Rosetta stone method, is based on the concept that some of the single-domain containing proteins in one organism can fuse to form a multi domain protein in other organisms

20. In Silico Two-Hybrid (I2h) The I2H method is based on the assumption that interacting proteins should undergo coevolution in order to keep the protein function reliable.

21. Phylogenetic tree The phylogenetic tree method predicts the protein-protein interaction based on the evolution history of the protein.  Calculate genetic distance between the new Hop and established subgroups Phylogenetic tree by MEGA

22. Phylogenetic Profile The phylogenetic profile predicts the interaction between two proteins if they share the same phylogenetic profile. Two proteins Sharing functional linkage. Construction of phylogenetic profile Align all protein against all Calculate best-hit profile Joined similar species by PCA Calculate the PC distance Calibrate against KEGG

23. Gene Expression The gene expression predicts interaction based on the idea that proteins from the genes belonging to the common expression-profiling clusters are more likely to interact with each other than proteins from the genes belonging to different clusters Quantification of the level at which a particular gene is expressed within a cell, tissue or organism under different experimental conditions and time intervals Clustering algorithm

24. Mechanisms for Protein modeling and analysis DNA SEQUENCE FILE Open the data base (ENSEMBLE) Search gene Copy nucleotide sequence Make a text file in your computer https://www.ensembl.org/index.html

25. Protein sequence file Copy nucleotide sequence Open EXPASY translate tool Paste nucleotide sequence Translate Copy the best open reading frame Make new text file on your computer Select best ORF https://web.expasy.org/translate/

26. 3D tertiary structure prediction Homology modeling Open Swiss model Press start modeling Paste or upload file Enter project tittle and email address Build model Result Save zip file https://swissmodel.expasy.org/

27. Different shape of 3D myoglobin visualized by Ras- Mol Myoglobin in ribbons shape Myoglobin in ball & stick shape Myoglobin in Spacefill CPK colour Myoglobin in Spacefil shape Myoglobin in wireframe shape Myoglobin in strands shape

28. 3D tertiary structure prediction AB-initio modeling Open I-Tasers server Enter email (Edu.) Register and get password Paste you protein sequence Enter protein id Submit Check email for result https://zhanglab.ccmb.med.umich.edu/I-TASSER/ Iterative Threading Assembly Refinement tool for protein to protein structure and function prediction by threading based approach . LOMETS,,,SPICKER

29. 3.D structure of haptoglobin predict by I- Tasseer . C-score = 0.8 TM score = 0.60 ± 0.14 RMS score =  8.8 ± 4.6Å 

30. Macromolecular Docking Macromolecular docking is the computational modelling of the quaternary structure of complexes formed by two or more interacting biological macromolecules Protein to protein docking Protein to ligand docking

31. Protein to protein docking play a central role in various aspects of the structural and functional organization of the cell A better understanding of processes such as metabolic control, signal transduction, and gene regulation. Genome-wide proteomics studies. Thus  docking methods that can elucidate the details of specific interactions at the atomic level. Protein to protein docking software There are many software for protein to protein docking such as Z Dock server ( http://zdock.umassmed.edu/ ) )  Patch Dock ( https://bioinfo3d.cs.tau.ac.il/PatchDock/ ) Auto Dock ( http://autodock.scripps.edu/ HEX server( http://hexserver.loria.fr )

32. Protein to protein docking by Z Dock server ZDOCK is Fast Fourier Transform based protein docking program. ZDOCK searches all possible binding modes in the translational and rotational space between the two proteins and evaluates each pose using an energy-based scoring function Submitting Jobs Input PDB Files Email Address Blocking Residues Contacting Residues Job out put

33. 3D xylanase capsid p24 complex complex

34. Complex of myoglobin with haptoglobin by Z-Dock server

35. DATABASES.  Protein–protein interactions are only the raw material for networks. To build a network, researchers typically combine interaction data sets with other sources of data. Primary databases that contain protein–protein interactions include DIP (http://dip.doe-mbi.ucla.edu), BioGRID , IntAct (http://www.ebi.ac.uk/intact) and MINT ( http://mint.bio.uniroma2.it ). These databases have committed to making records available through a common language called PSICQUIC, to maximize access.

36. CONCLUSION  The predictive power of the interactome model allows us to examine the organization and coordination of multiple complex cellular processes and determine how they are organized into pathways. The interactome model can be used to predict poorly characterized proteins into their functional context according to their interacting partners within a module. One-to-many relationship can be used for pathway discovery.

37. REFERENCES Protein-Protein Interaction Detection: Methods and AnalysisV.SrinivasaRao,1 K.Srinivas,1 G.N.Sujini,2 andG.N.SunandKumar1 1 DepartmentofCSE,VRSiddharthaEngineeringCollege,Vijayawada520007,India 2DepartmentofCSE,MahatmaGandhiInstituteofTechnology,Hyderabad500075,India CorrespondenceshouldbeaddressedtoV.SrinivasaRao;[email protected] 2. https://www.slideshare.net/Prianca12/protein-protein-interactions-29100706 3. https://youtu.be/mvo_xL1LESM 4. https://youtu.be/kl2SU6gTRDI