International Journal of Integrative Biology IJIB, 2008, Vol. 4, No. 1, 1 © IJIB, All rights reserved Networks of drugs and their targets INTRODUCTION Genomic and post-genomic technology is producing a huge amount of heterogeneous data available for investigating the functions of proteins. The challenge now is to exploit these raw data and extract useful knowledge from them. Concurrently, drug target identification, being the first phase in drug discovery, is becoming an overly time consuming process and in many cases produces inefficient results due to failure of conventional approaches (non context sensitive analysis) to investigate large scale data. An efficient way to perform this task involves exploring the biological relationships between various kinds of biological data by viewing and exploring the genomic world using a complex network of biological objects and their relationships (Durand et al., 2006). Pharmacological activity depends on the binding of drugs to their targets (Copeland, et al., 2006). Estimations of the total number of drug targets are presently dominated by analyses of the human genome, which are limited for various reasons, including the inability to infer the existence of splice variants, interactions between the encoded proteins from gene sequences alone, and the fact that the function of most of the DNA in the genome remains unclear (Imming et al., 2006). This is further confounded by the inability to annotate a significant proportion of genes (Sakharkar et al., 2005). Nonetheless, drug development strategies have been influenced profoundly by the wealth of potential targets offered by genome projects. Concurrently, advances in genomics (Janssens et al., 2008; Peltonen et al., 2001), Proteomics (Chung et al., 2008), and understanding on molecular mechanisms of diseases (Zhan 2007) enable the search for new targets, and facilitate the study of existing targets for finding clues to new target identification (Sakharkar et al., 2007; Sakharkar et al., 2007, Evan et al., 2001). These advances also facilitate probing the molecular mechanisms of drug actions, adverse drug reactions, and the pharmacogenetic implications of variations in gene sequences, and the profiles of gene expression and post-transcriptional processing [Cotsarelis et al., 2001; Nicholls, 2003; Roden et al., 2006; Morphy et al., 2005; Roth et al., 2004). Though, the conventional ‘one drug, one target, one disease’ approach continues to dominate pharmaceutical thinking, and has led to the discovery of many successful drugs and drug target, it has been challenged (Law et al., 2003; Keith et al., 2005; Goh et al., 2007; Lamb et al., 2007). Several diseases like cancer, cardiovascular disease, and depression tend to result from multiple molecular abnormalities i.e. not from a single target/gene defect. Recently, Goh et al., elaborated on the human disease gene networks (Goh et al., 2007) and demonstrated that in many, the clinical effect is caused by patterns of target interactions. Concurrently, Nacher and Schwartz, Perspective International Journal of Integrative Biology A journal for biology beyond borders ISSN 0973-8363 Genetic and Pharmacological Interaction network of targets and drugs Meena K Sakharkar 1,2 , Kishore R Sakharkar 2,3,* 1 Advanced Design and Modeling Lab, School of MAE, Nanyang Technological University, Singapore 2 Bimolecular Engineering Research Centre, Nanyang Technological University, Singapore 3 OmicsVista, Singapore Submitted: 24 Sep. 2008; Accepted: 5 Nov. 2008 Abstract Accumulated knowledge on genomic information, systems biology, and disease mechanisms provide an unprecedented opportunity to elucidate the genetic basis of diseases, and to discover novel therapeutic targets from genomic data. With hundreds to a few thousand potential targets available in the human genome alone, and the rise in the role of multi-drug therapies for complex diseases, there is an urgent need to understand the relationships between diseases and genes, and drugs and targets. These data will help inform and guide future drug discovery processes. Here, we present an update on targets with drugs available - their number, nature and interactions. We further elaborate on the network based approach for understanding the human ‘disease ‘ome’ and the human ‘druggome’ taking diabetes as a case study. Keywords: Targets, FDA, drug, network, disease, diabetes. * Corresponding author: Kishore Sakharkar, Ph.D. OmicsVista, Singapore Email: ksakharkar@gmail.com