In silico prediction of chemical mechanism of action via an improved network-based inference method.

ABSTRACT:

Background and purpose

Deciphering chemical mechanism of action (MoA) enables the development of novel therapeutics (e.g. drug repositioning) and evaluation of drug side effects. Development of novel computational methods for chemical MoA assessment under a systems pharmacology framework would accelerate drug discovery and development with greater efficiency and low cost.

Experimental approach

In this study, we proposed an improved network-based inference method, balanced substructure-drug-target network-based inference (bSDTNBI), to predict MoA for old drugs, clinically failed drugs and new chemical entities. Specifically, three parameters were introduced into network-based resource diffusion processes to adjust the initial resource allocation of different node types, the w

SUBMITTER: Wu Z 

PROVIDER: S-EPMC5738663 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature