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Generalized Psychophysiological Interaction (PPI) Analysis of Memory Related Connectivity in Individuals at Genetic Risk for Alzheimer's Disease

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Chemical combination effects predict connectivity in biological systems.

Joseph Lehár¹, Grant R Zimmermann, Andrew S Krueger

¹CombinatoRx, Incorporated, Cambridge, MA 02142, USA.

Molecular Systems Biology

|March 3, 2007

Summary

Cellular responses to chemical combinations reveal biological target connections. This method provides network connectivity constraints and can refine biological models or identify new targets.

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Area of Science:

Systems biology
Chemical biology
Network pharmacology

Background:

Constructing accurate biological models requires extensive data on functional component connections.
Understanding these connections is crucial for developing effective therapeutic strategies.

Purpose of the Study:

To demonstrate that cellular responses to chemical combinations can elucidate the functional connectivity of biological targets.
To establish a method for refining biological network models and identifying novel therapeutic targets.

Main Methods:

Simulating pathway responses to pairs of inhibitors at varying doses to predict distinct response surface shapes.
Experimentally validating predicted response surface shapes using yeast and human tumor cell screens.
Analyzing synergy profiles across multiple chemical combinations to infer target relatedness.

Main Results:

Predicted response surface shapes were accurately reproduced in experimental yeast and human tumor cell screens.
Cellular response morphology provided detailed connectivity constraints between biological targets.
Synergy profiles revealed functional relatedness between targets within the cellular network.

Conclusions:

Chemical combination studies offer a flexible and powerful approach to map biological networks, complementing genetic methods.
Response surface methodology using chemical probes can refine existing network models and identify new therapeutic targets.
This approach has potential applications beyond biological systems for analyzing responses to targeted perturbations.