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Drug–Target N etwork

Drug–Target N etwork. Hussein Hijazi Fall 2012 Michigan State University. Motivation. Proteins rarely function in isolation in and outside the cell. Goal : To understand drug targets in the context of cellular and disease networks Analyze properties of drug-target networks

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Drug–Target N etwork

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  1. Drug–Target Network Hussein Hijazi Fall 2012 Michigan State University

  2. Motivation • Proteins rarely function in isolation in and outside the cell. • Goal: To understand drug targets in the context of cellular and disease networks • Analyze properties of drug-target networks • Assess network-based relationship between drugs and their targets • Quantify interrelationships between drug targets and disease-gene products.

  3. Distribution of Drugs and Drug Targets • DrugBank- 4,252 drugs • 1,178 - FDA approved drugs • 3074 - Experimental drugs • FDA approved drugstarget 394 human proteins • Average number of target proteins per drug ~ 1.8 • The pharmaceutical industry shows a tendency to target already validated target proteins, causing an abundance of ‘follow-on’ drugs.

  4. Generating a Drug-Target Network • Generate a bipartite graph of drug-protein interactions. • From the bipartite graph, generate two biologically relevant networks: • Drug Network • Target-Protein Network

  5. Drug-Target Network Rectangles => Target Proteins Circles => Drugs

  6. Drug Network • The network displays many connections between different drugs and drug classes (788 drugs have at least one link to other drugs). • 476 drugs are in the largest connected component • The actual size of the largest connected component of the drug network (476) is significantly smaller than the average giant component ofrandomized networks (788 ± 9; p< )

  7. Target-Protein Network • 305 out of 394 target proteins are connected to other target proteins. • The actual size of the largest connected component of the Target-Protein network (122) is significantly smaller than the average giant component of randomized networks (302 ± 8; p < ) • The industry seems to be shifting towards drugs with multiple targets (polypharmacology).

  8. Experimental Drugs • Inclusion of experimental drugs increases the size of the TP network giant component to 725,still significantly smaller than the average size of the giant component of randomly generated graphs (782 ± 11). • In contrast, the network formed by protein targets that are targeted by experimental drugs has a giant component size of 596, which is significantly larger than randomized networks (551 ± 10; P < 10−4).

  9. Drug Targets & Essentiality • Overlay the TP network onto a network of physical PPIs. • 262 target proteins are present in the PPI network. • The drug-target proteins have 42% more interacting proteins (degree) on average than any protein in the PPI network. • Compare the degree of drug targets to the predicted human essential proteins.

  10. Drug Targets & Essentiality • Essential proteins tend to coordinate the activity of diverse biological processes or ‘modules’ • Assess co-expression using expression data from 36 different human tissue microarray experiments. Genes encoding drug-target proteins show less co-expression with other genes compared with essential genes Average number of different tissues in which each class is expressed.

  11. Drug Targets & Human Disease Genes • Agene-centered human disease-gene (HDG) network was generated from the human disease map. • 166 genes encodes drug target proteins with 71 genes (43%) associated with two or more diseases. • Experimental drugs target 210 proteins in the HDG network, only 54 (26%) of which are involved in multiple diseases • Drug targets have significantly lower degreescompared with the network average. a: The Human Disease Network b: Average degree of several gene classes in the human disease gene network

  12. Drug Targets & Human Disease Genes Fractionof target proteins while applying a breadth-first search starting from either a target protein or a random protein in the HDG network with respect to distance

  13. Cellular Network-based relationships between drug targets and disease genes • Drugs act by exploiting two principal mechanisms: • Etiology-specific drugs target the actual cause of the disease. • Palliative drugs target proteins that are not the actual cause of the disease.

  14. Conclusion • What are the industry trends? • What are the properties of drug targets in the context of cellular networks? • How do drug targets relate to disease-gene products?

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