The apparently paradoxical lack of correlation between the huge increase in the discovery of new potential drug targets made possible by the post-genomic sciences and new drugs development has stimulated many different interpretations. Here we illustrate the general principle of redundancy of biological pathways on hand of simplified mathematical approaches applied to different models of biological regulation. The simulation was based on the analysis of the 'degree of autonomy' of network architectures in which the possibility for an external stimulus (e.g. a drug) impinging into a specific node to be sensed by the entire network, and eventually amplified up to a macroscopic consequence, was demonstrated to be limited to strictly linear pathways. The implications of such a result for poly-pharmacology and computational approaches to drug development are described as well.

Why so Few Drug Targets: A Mathematical Explanation? / K., Thun; Menghini, Marta; Lina, D'Andrea; Pawan, Dhar; Hiroshi, Tanaka; Alessandro, Giuliani. - In: CURRENT COMPUTER-AIDED DRUG DESIGN. - ISSN 1573-4099. - STAMPA. - 7:3(2011), pp. 206-213. [10.2174/157340911796504297]

Why so Few Drug Targets: A Mathematical Explanation?

MENGHINI, Marta;
2011

Abstract

The apparently paradoxical lack of correlation between the huge increase in the discovery of new potential drug targets made possible by the post-genomic sciences and new drugs development has stimulated many different interpretations. Here we illustrate the general principle of redundancy of biological pathways on hand of simplified mathematical approaches applied to different models of biological regulation. The simulation was based on the analysis of the 'degree of autonomy' of network architectures in which the possibility for an external stimulus (e.g. a drug) impinging into a specific node to be sensed by the entire network, and eventually amplified up to a macroscopic consequence, was demonstrated to be limited to strictly linear pathways. The implications of such a result for poly-pharmacology and computational approaches to drug development are described as well.
2011
networks; drug development; systems biology; multiple targets; pharmacology
01 Pubblicazione su rivista::01a Articolo in rivista
Why so Few Drug Targets: A Mathematical Explanation? / K., Thun; Menghini, Marta; Lina, D'Andrea; Pawan, Dhar; Hiroshi, Tanaka; Alessandro, Giuliani. - In: CURRENT COMPUTER-AIDED DRUG DESIGN. - ISSN 1573-4099. - STAMPA. - 7:3(2011), pp. 206-213. [10.2174/157340911796504297]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/83851
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