raheleh salari sfu
Download
Skip this Video
Download Presentation
Potential Drug Target Discovery on PPI Networks

Loading in 2 Seconds...

play fullscreen
1 / 18

Potential Drug Target Discovery on PPI Networks - PowerPoint PPT Presentation


  • 216 Views
  • Uploaded on

Raheleh Salari SFU. Potential Drug Target Discovery on PPI Networks. Pathogens becoming more drug resilient; infectious diseases on the rise. Emerging diseases (e.g. avian flu) may result in a global pandemic! Rational drug design - search for magic bullets is failing.

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'Potential Drug Target Discovery on PPI Networks' - bessie


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
slide2
Pathogens becoming more drug resilient; infectious diseases on the rise.
  • Emerging diseases (e.g. avian flu) may result in a global pandemic!
  • Rational drug design - search for magic bullets is failing.
  • Combinatorial therapies needed – multiple drug targets.
computational identification of drug targets
Computational identification of drug targets
  • Protein protein interaction (PPI) networks: edges-interactions, nodes-proteins.
  • Goal: Identify protein targets on PPI networks whose “removal” disrupts several “essential” pathways/complexes and their possible “backup” paths on the PPI network.
  • Targets should have no human orthologs.
example
Example

Associated PPI subnetwork

H.Pylori Chemotaxis pathway

ppi networks pathways
PPI networks + pathways
  • Strategy: aim to disrupt all the possible communication paths between “endpoint” pairs of essential pathogenic pathways (multicut).
  • Weighted node sparsest cut:
    • Input: Node weights (large for human orthologs - small for essential proteins, surface proteins, easy targets), Essentiality of source/sink pairs (quantify how important a pathway is to survival)
    • Output: minimize W(C) / ecc(C)
      • W(C) = total weight of nodes on C
      • ecc(C) = total essentiality of the pathways disrupted
approximation algorithms
Approximation algorithms
  • DSC: # endpoint pairs = O(log n)

O(log n) approximation by trivial generalization of multi-cut algorithms (Check every subset of source sink pairs)

O(n3 log2 n) [Goldberg & Tarjan 88]

  • LP: # source/sink pairs unbounded

O(n1/2 ) approximation

polynomial rounding algorithm[Hajiaghayi & Raecke 07]

  • Identical results on H.pylori PPI network,

slight differences on E.coli PPI network

input e coli signaling pathways
Pathway

Source

Sink

Target(s)

Method(s)

OmpR Family

PhoR

PhoA

OmpR Family

TorS

TorA

NarL Family

NarG

NarI

NarL Family

NarQ

FrdA

dnaK*

DSC, LP

DNA polymerase

dnaE

holA

DNA polymerase

dnaE

holD

ABC Transporter

CysP

CysA

Bacterial Chemotaxis

Tar

MotA

cheW*

DSC, LP

Bacterial Chemotaxis

DPPA

MotA

mtlD

DSC

Input: E.coli Signaling Pathways
input e coli essential complexes
Complex

Source

Sink

Target(s)

Method(s)

RNA Polymerase

infB

rpoN

RNA Polymerase

hepA

greB

rpoA*+, rpoB*+, rplC*, rpoC*, rpsB*, rpsE*

DSC, LP

ACP

Ffh

aidB

IscS

hscA

fdhD

lpdA*, IysU, aceF*, aceE, iscS*, rpsE*

DSC, LP

DNA polymerase

sbcB

priA

Ribosome associated

hlpA

uvrC

Ribosome associated

cafA

kdsA

Input: E.coli essential complexes
input h pylori signaling pathways
Pathway

Source

Sink

Target(s)

Method(s)

Ribosomal Proteins

rplD

rplP

Ribosomal Proteins

rplI

rpsF

HP1223

DSC, LP

Protein Export

SecD

YidC

Type III Secretion Sys.

FliF

FlhA

Type IV Secretion Sys.

cag12

trbI

HP0933

DSC, LP

Two component Sys.

TrpB

TrpE

HP0452

DSC, LP

Two component Sys.

AtoS

AtoB

HP0149

DSC, LP

Flagellar Assembly

FliG

FliN

HP0823

DSC, LP

Flagellar Assembly

FliD

FlhA

FabE

DSC, LP

Bacterial Chemotaxis

CheW

MotB

ABC Transporters

OppA

OppF

msrAB

DSC, LP

DNA Polymerase

dnaE

dnaN

HP0241

DSC, LP

Input: H.pylori signaling pathways
ppi networks only
PPI networks only
  • Strategy: aim to disrupt as many “potential” pathways as possible (balanced cut).
  • Minimum weighted node separator problem:

C is a -balanced separator if C partitions V to V’ and V’’ s.t. min{|V’|,|V’’|} > .|V|

    • Input: Node weights (small node weights indicate essentiality, targetability etc., human orthologs have large weight)
    • Output: find C with minimum total weight
approximation algorithms heuristics
Approximation algorithms, heuristics
  • O(log n) approximation [Leighton & Rao 99] performs poorly in practice .
  • O(log1/2 n) approximation [Arora & Kale 07] is only slightly better.
  • Greedy heuristics targeting nodes with maximum degree (GDeg), betweenness (GBet) perform relatively poorly.
  • Heuristics motivated by several combinatorial observations devised (HMWS).
e coli pathways disrupted cut size 28 0 15
1

Ribosome

2

Pyruvate metabolism

3

Butanoate metabolism

4

Citrate cycle (TCA cycle)

5

Glycolysis/Gluconeogenesis

6

Alanine and asparate metabolism

7

Glycine, serine and threonine metabolism

8

Valine, leucine and isoleucine degradation

9

Pyrimidine metabolism

10

Purine metabolism

11

RNA polymerase

12

Lysine biosynthesis

13

Aminoacyl-tRNA biosynthesis

14

Two Component (NarL family) *

15

Bacterial Chemotaxis *

16

ABC transporters (Iron complex) *

E.Coli pathways disrupted (cut size 28, β=0.15)
e coli known drug targets re discovered cut size 28 0 15
Gene Name

Drug

rpoA

Rifabutin

rpoB

Rifampin, Rifaximin

rpsJ

Nitrofurantoin

rpsD

Clomocycline, Demeclocycline, Doxycycline, Lymecycline, Minocycline, Oxytertracycline, Tetracycline, Tigecycline

E.coli known drug targets (re)discovered(cut size 28 β=0.15)
h pylori disrupted pathways cut size 17 0 15
1

Purine metabolism

2

Pyrimidine metabolism

3

RNA polymerase

4

Caprolactam degradation

5

Flagellar assembly

6

Urease complex

7

Ribosomal proteins *

8

Oxidative phosphorylation (F-type ATPase) *

9

Epithelial cell signaling in H. pylori infection *

10

DNA polymerases *

11

Bacterial chemotaxis *

12

Oxidative phosphorylation (f-type ATPase) *

13

Protein export (Sec dependent pathway) *

14

Two-component system – NtrC family *

15

ABC transporters(Iron complex) *

16

Flagellar assembly *

17

Tyep IV secretion system *

H.Pylori disrupted pathways (cut size 17, β=0.15)
acknowledgements
Acknowledgements
  • Cenk Sahinalp (SFU, CompBio)
  • Fereydoun Hormozdiari (SFU, CompBio)
  • Vineet Bafna (UCSD)
  • Phuong Dao (SFU, CopmBio)
  • SFU CTEF: Bioinformatics for combating infectious diseases program
  • NSERC, CRC program, MSFHR
slide17
HMWS
  • RWB: compute Random Walk Betweenness for all nodes – in O(n3) time on a sparse graph
  • Split: returns an initial cut s.t. every connected component < (1n nodes
  • Merge: partitions the components into two each with > n nodes
  • Cut: do it all over again
ad