Quantitative systems-level determinants of human genes targeted by successful drugs

Abstract

What makes a successful drug target? A target molecule with an appropriate (druggable) tertiary structure is a necessary but not the sufficient condition for success. Here we analyzed specific properties of human genes and proteins targeted by 919 FDA-approved drugs and identified several quantitative measures that distinguish them from other genes and proteins at a highly significant level. Compared to an average gene and its encoded protein(s), successful drug targets are more highly connected (but far from being the most highly connected), have higher betweenness values, lower entropies of tissue expression, and lower ratios of nonsynonymous to synonymous single-nucleotide polymorphisms. Furthermore, we have identified human tissues that are significantly over-or undertargeted relative to the full spectrum of genes that are active in each tissue. Our study provides quantitative guidelines that could aid in the computational screening of new drug targets in human cells.

Protein-Protein Interaction Networks: Structures, Evolution, and Application to Drug Design

“…They found that most drug target genes are middle-degree proteins and some are low-degree, while there are almost no drug targets among highdegree proteins (see Fig 6). The degree distribution is similar to that of disease genes, and, not surprisingly, drug target genes significantly overlap with disease genes (Yao & Rzhetsky 2008). These results indicate that middle-degree proteins are likely to be most advantageous targets for therapeutic drugs.…”

Bottlenecks and Hubs in Inferred Networks Are Important for Virulence in Salmonella typhimurium

“…Recently, a number of approaches analyzed bottlenecks in human protein-protein interaction networks. These studies have identified genes involved in neurodegenerative diseases (Goni et al, 2008), and characterized properties of successful drug targets (Yao and Rzhetsky, 2008) and targets of different pathogens (Dyer et al, 2008). Bottleneck nodes in other types of networks, for example those derived from mining literature, have also been used to identify disease-associated genes (Ozgur et al, 2008).…”

Identifying Network of Drug Mode of Action by Gene Expression Profiling

“…DENTIFYING PATHWAYS THAT MEDIATE a drug mode of action (MOA) is a key challenge in biomedicine (Ambesi-Impiombato and di Bernardo, 2006;di Bernardo et al, 2005;Staunton et al, 2001;Terstappen et al, 2007;Yao and Rzhetsky, 2008). Several chemo-informatics tools to analyze chemical similarities between small-molecules are available (Medina-Franco et al, 2007;Miller, 2002;Rhodes et al, 2007).…”