network-based Target Ranking for Polypharmacological Therapies

Francesca Vitali, Francesca Mulas, Pietro Marini and Riccardo Bellazzi

NETWORK-BASED TARGET RANKING FOR POLYPHARMACOLOGICAL THERAPIES

University of Pavia, Italy

Angelo Nuzzo IIT@SEMM, Milan, 2011

Drug Discovery

Angelo Nuzzo IIT@SEMM, Milan, 2011

Drug Discovery Today

Decline in:

• Clinical development

• Productivity

Standard approach MAGIC BULLET

SINGLE TARGET DRUGS

Emerging approach POLYPHARMACOLOGY

Angelo Nuzzo IIT@SEMM, Milan, 2011

Polypharmacology

MULTI TARGET DRUGS

• Collective weak interactions vs single strong interaction

• Improve therapeutic efficacy

- Multi-factorial diseases (e.g. cancer)

• Avoid

- Adaptive drug resistance

Drug

Protein

Angelo Nuzzo IIT@SEMM, Milan, 2011

Network-based Polypharmacology

Prior knowledge on complex diseases

DATA SOURCES +

PROTEIN INTERACTION NETWORKS

Protein

Interaction

Angelo Nuzzo IIT@SEMM, Milan, 2011

Method

Disease of interest

Network design

Network targeting

Scoring of target combinations

Ad hoc analysis of drug agents related to the selected targets

Angelo Nuzzo IIT@SEMM, Milan, 2011

Method

Disease of interest

Network design

Network targeting

Scoring of target combinations

Ad hoc analysis of drug agents related to the selected targets

Type 2 Diabetes Mellitus

(T2DM)

Angelo Nuzzo IIT@SEMM, Milan, 2011

Method

Disease of interest

Network design

Network targeting

Scoring of target combinations

Ad hoc analysis of drug agents related to the selected targets

Angelo Nuzzo IIT@SEMM, Milan, 2011

Network design

NODES Proteins

EDGES Interactions

Human proteins involved T2DM

pathways

Network

Protein – Protein Interaction Repository

Angelo Nuzzo IIT@SEMM, Milan, 2011

Biological Network Features

• Interactions

• Experimental evidence

- Not considering:

Literature mining, co-occurence, ecc.

• Confidence Score › 0.7 (high confidence)

NODES 587

EDGES 3683

Angelo Nuzzo IIT@SEMM, Milan, 2011

Disease Network

Network genes

87 disease proteins

Up- and down-regulated genes

Diabetes vs control

Angelo Nuzzo IIT@SEMM, Milan, 2011

Method

Disease of interest

Network design

Network targeting

Scoring of target combinations

Ad hoc analysis of drug agents related to the selected targets

Angelo Nuzzo IIT@SEMM, Milan, 2011

Network Targeting

• Node constraints:

• Druggable

• Not Hub

• High Bridging Centrality

Angelo Nuzzo IIT@SEMM, Milan, 2011

Druggability

LOCALIZATION

DRUG INTERACTIONS

• Cell membrane

• Extracellular space

DRUGGABLE PROTEINS

206 + 108

Chemical – Protein Interaction Repository

Angelo Nuzzo IIT@SEMM, Milan, 2011

Hub

• Hub

1. High # neighbours

2. Located between highly connected regions

Traditional pharmacology

DISCARDED AS POTENTIAL POLYPHARMACOLOGICAL TARGET

• Hub discovery method:

DISCARDED HUB 14

Vallabhajosyula et al. Identifying hubs in protein interaction networks.PLoS ONE, 4(4):e5344, 2009.

Angelo Nuzzo IIT@SEMM, Milan, 2011

Betweenness centrality

• Global bridging properties

• Influence of a node in the spread of information through the network

Bridging Coefficient

• Local bridging properties

• Penalizes hub

Bridging Centrality

Bridging centrality

BC = Bridging Coefficient

RWB = Random-walk Betweenness

Angelo Nuzzo IIT@SEMM, Milan, 2011

Bridging Centrality

Bridging centrality

BC = Bridging Coefficient

RWB = Random-walk Betweenness

Bridge node first 25% of the nodes ordered by bridging centrality

BRIDGING PROTEINS 147

Hwang et al. Bridging centrality: Identifying bridging nodes in scale-free networks.Knowledge Discovery and Data mining, 2006

Angelo Nuzzo IIT@SEMM, Milan, 2011

Target selection

47 target proteins

“Sources ” of pharmacological actions

Druggable

Non hub

Bridge nodes

Angelo Nuzzo IIT@SEMM, Milan, 2011

Method

Disease of interest

Network design

Network targeting

Scoring of target combinations

Ad hoc analysis of drug agents related to the selected targets

Angelo Nuzzo IIT@SEMM, Milan, 2011

Drug Synergy

• Reachability of a single Disease Protein

Wi,ji j

• Reachability of all DPs

Sh = shortest path

w i,j = edge weight between i and j

(i,j) = node pair

Np = # disease proteins

T

Angelo Nuzzo IIT@SEMM, Milan, 2011

Drug Synergy

TRIPLETS

• Low computational cost

• Upper limit to the number of drugs to be jointly delivered

Angelo Nuzzo IIT@SEMM, Milan, 2011

TSDS

• TSDS (Topological Score of Drug Synergy) of a triplet

TSDS

• Null distribution:

TSDS for 50 000 triplets ofproteins randomly selectedfrom the network

Combinationsof 18 targets

88 triplets with

P-Value < 0.01

Angelo Nuzzo IIT@SEMM, Milan, 2011

Method

Disease of interest

Network design

Network targeting

Scoring of target combinations

Ad hoc analysis of drug agents related to the selected targets

Angelo Nuzzo IIT@SEMM, Milan, 2011

Target AnalysisFrequency

Angelo Nuzzo IIT@SEMM, Milan, 2011

Target Analysis

Insulin-like

growth factor

family

Frequency

Angelo Nuzzo IIT@SEMM, Milan, 2011

Target AnalysisFrequency

• EXPERIMENTAL EVIDENCE

• Negative regulator of insulin signalling TO BE INHIBITED

• Extract of Larrea Tridente

1. Decrease

• plasma glucose

• triglyceride concentrations

2. Inhibits IGF1R activity

Angelo Nuzzo IIT@SEMM, Milan, 2011

Target Analysis

Alzheimer

Frequency

Angelo Nuzzo IIT@SEMM, Milan, 2011

• Strongly altered expression of

IGF1R/IGF

Target Analysis

Alzheimer

• Recent Studies

T2DM Alzheimer

• Strongly altered expression of IGF1R/IGF

Frequency

• Patients with T2DM have a 2- to 3-fold increased risk for AD.

Angelo Nuzzo IIT@SEMM, Milan, 2011

Target AnalysisFrequency

Only one standard target

Angelo Nuzzo IIT@SEMM, Milan, 2011

Conclusion

• Network-based method for feasible identification of multi-component synergy

• Data integration

• Topological feature analysis

• Scoring system

Results:

• Disease-causative pathways

• Potential multi-target nodes

• To discover new therapies

• To support the standard therapies

Future steps:

• Testing on other complex diseases

• Application to directed network

Thanks.

NETWORK-BASED TARGET RANKING FOR POLYPHARMACOLOGICAL THERAPIES