Abstract
Systems biology is in an exponential development stage in recent years and has been widely utilized in biomedicine to better understand the molecular basis of human disease and the mechanism of drug action. Here, we discuss the fundamental concept of systems biology and its two computational methods that have been commonly used, that is, network analysis and dynamical modeling. The applications of systems biology in elucidating human disease are highlighted, consisting of human disease networks, treatment response prediction, investigation of disease mechanisms, and disease-associated gene prediction. In addition, important advances in drug discovery, to which systems biology makes significant contributions, are discussed, including drug-target networks, prediction of drug-target interactions, investigation of drug adverse effects, drug repositioning, and drug combination prediction. The systems biology methods and applications covered in this review provide a framework for addressing disease mechanism and approaching drug discovery, which will facilitate the translation of research findings into clinical benefits such as novel biomarkers and promising therapies.
Highlights
Advances in biological sciences over the past several decades have led to the generation of a large amount of omics molecular data at the level of genome, transcriptome, proteome, and metabolome
Remaining in its infancy in many ways, systems biology is in an exponential development stage in recent years and has been widely used in pharmacology to better understand molecular basis of disease and mechanism of drug action [1]
By considering the biological context of drug target, systems biology provides new opportunities to address disease mechanisms and approach drug discovery, which will facilitate the translation of preclinical discoveries into clinic benefits such as novel biomarkers and therapies [4]
Summary
Advances in biological sciences over the past several decades have led to the generation of a large amount of omics molecular data at the level of genome, transcriptome, proteome, and metabolome. While identifying all the genes and proteins provides a catalog of individual molecular components, it is not sufficient by itself to understand the complexity inherent in biological systems. Many drug candidates failed clinical phases because the mechanisms of the cellular pathways they target are incompletely understood. These have significant implications in the drug discovery process because the molecular components that need to be targeted must change from single proteins to entire cellular pathways [3]. By considering the biological context of drug target, systems biology provides new opportunities to address disease mechanisms and approach drug discovery, which will facilitate the translation of preclinical discoveries into clinic benefits such as novel biomarkers and therapies [4]. We will first describe systems biology methods that have become commonplace; we will examine their various applications in drug discovery and translation medicine; brief discussions on future directions are given
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