Systems Biology Approaches and Tools for Analysis of Interactomes and Multi-target Drugs

Abstract

Systems biology is essentially a proteomic and epigenetic exercise because the relatively condensed information of genomes unfolds on the level of proteins. The flexibility of cellular architectures is not only mediated by a dazzling number of proteinaceous species but moreover by the kinetics of their molecular changes: The time scales of posttranslational modifications range from milliseconds to years. The genetic framework of an organism only provides the blue print of protein embodiments which are constantly shaped by external input. Indeed, posttranslational modifications of proteins represent the scope and velocity of these inputs and fulfil the requirements of integration of external spatiotemporal signal transduction inside an organism. The optimization of biochemical networks for this type of information processing and storage results in chemically extremely fine tuned molecular entities. The huge dynamic range of concentrations, the chemical diversity and the necessity of synchronisation of complex protein expression patterns pose the major challenge of systemic analysis of biological models. One further message is that many of the key reactions in living systems are essentially based on interactions of moderate affinities and moderate selectivities. This principle is responsible for the enormous flexibility and redundancy of cellular circuitries. In complex disorders such as cancer or neurodegenerative diseases, which initially appear to be rooted in relatively subtle dysfunctions of multimodal physiologic pathways, drug discovery programs based on the concept of high affinity/high specificity compounds ("one-target, one-disease"), which has been dominating the pharmaceutical industry for a long time, increasingly turn out to be unsuccessful. Despite improvements in rational drug design and high throughput screening methods, the number of novel, single-target drugs fell much behind expectations during the past decade, and the treatment of "complex diseases" remains a most pressing medical need. Currently, a change of paradigm can be observed with regard to a new interest in agents that modulate multiple targets simultaneously, essentially "dirty drugs." Targeting cellular function as a system rather than on the level of the single target, significantly increases the size of the drugable proteome and is expected to introduce novel classes of multi-target drugs with fewer adverse effects and toxicity. Multiple target approaches have recently been used to design medications against atherosclerosis, cancer, depression, psychosis and neurodegenerative diseases. A focussed approach towards "systemic" drugs will certainly require the development of novel computational and mathematical concepts for appropriate modelling of complex data. But the key is the extraction of relevant molecular information from biological systems by implementing rigid statistical procedures to differential proteomic analytics.

The use of multi-target drugs in the treatment of neurodegenerative diseases

“…These obstacles require that design approaches should be capable of identifying protein targets (receptors or enzymes) independently of global sequence or structural homology [22,23,28]. Molecular biology and genomics approaches, combined with computational resources and robotic instrumentation applied to genetic analyses and biological data, have united to accelerate the pace of discovery of credible drug targets in the design of DMLs for neurodegenerative diseases [29,30].…”

Advocating the need of a systems biology approach for personalised prognosis and treatment of B-CLL patients

“…To generate a computational model for prognosis of B-CLL patients in silico, one has to overcome a number of challenges such as working with a large number of chemically diverse molecules that are often rapidly changing their concentrations in terms of their expression and regulation [68]. In order to overcome these challenges, various sensitive detection systems or gene reporter systems should be implemented to detect the optimal expression in vivo [69] before its execution in building a model.…”

“…Each pathway is subject to an intensive study by the computational systems biology approach: modelling of the cell cycle [65][66][67][68][69][70][71][72][73], apoptosis [74][75][76], MAPK and PI3K/AKT pathways [77,78]. As these pathways are involved in cell proliferation, survival and cell death, computational models of these pathways are considered promising tools in cancer research for prediction of cancer disease progression, development of biomarkers, and drug therapy efficacy [79][80][81][82].…”

Neuroblastoma therapy: what is in the pipeline?

“…In contrast to conventional chemotherapy, targeted drugs give the possibility to specifically hit subpopulations of cells, thereby reducing the toxic effects (Petrelli & Giordano 2008). Therefore, the high-affinity/high-specificity compounds have been of high interest (Schrattenholz et al 2010). However, despite the initial enthusiasm for the efficacy of these treatments, some disappointing results have been obtained (Modak & Cheung 2010).…”