Network pharmacology: curing causal mechanisms instead of treating symptoms

For complex diseases, most drugs are highly ineffective, and the success rate of drug discovery is in constant decline. While low quality, reproducibility issues, and translational irrelevance of most basic and preclinical research have contributed to this, the current organ-centricity of medicine and the 'one disease-one target-one drug' dogma obstruct innovation in the most profound manner. Systems and network medicine and their therapeutic arm, network pharmacology, revolutionize how we define, diagnose, treat, and, ideally, cure diseases. Descriptive disease phenotypes are replaced by endotypes defined by causal, multitarget signaling modules that also explain respective comorbidities. Precise and effective therapeutic intervention is achieved by synergistic multicompound network pharmacology and drug repurposing, obviating the need for drug discovery and speeding up clinical translation.

Combining Gene-Disease Associations with Single-Cell Gene Expression Data Provides Anatomy-Specific Subnetworks in Age-Related Macular Degeneration

Background: Age-related macular degeneration (AMD) is the most common cause of visual impairment in the developed world. Despite some treatment options for late AMD, there is no intervention that blocks early AMD proceeding to the late and blinding forms. This is partly due to the lack of precise drug targets, despite great advances in genetics, epidemiology, and protein-protein interaction (PPI) networks proposed to be driving the disease pathology. A systems approach to narrow down PPI networks to specific protein drug targets would provide new therapeutic options. Materials and Methods: In this study we analyzed single cell RNAseq (RNA sequencing) datasets of 17 cell types present in choroidal, retinal pigment epithelium (RPE), and neural retina (NR) tissues to explore if a more granular analysis incorporating different cell types exposes more specific pathways and relationships. Furthermore, we developed a novel and systematic gene ontology database (SysGO) to explore if a subcellular classification of processes will further enhance the understanding of the pathogenesis of this complex disorder and its comorbidities with other age-related diseases. Results: We found that 57% of the AMD (risk) genes are among the top 25% expressed genes in ∼1 of the 17 choroidal/RPE/NR cell types, and 9% were among the top 1% of expressed genes. Using SysGO, we identified an enrichment of AMD genes in cell membrane and extracellular anatomical locations, and we found both functional enrichments (e.g., cell adhesion) and cell types (e.g., fibroblasts, microglia) not previously associated with AMD pathogenesis. We reconstructed PPI networks among the top expressed AMD genes for all 17 choroidal/RPE/NR cell types, which provides molecular and anatomical definitions of AMD phenotypes that can guide therapeutic approaches to target this complex disease. Conclusion: We provide mechanism-based AMD endophenotypes that can be exploited in vitro, using computational models and for drug discovery/repurposing.

Repository of proposed pathways and protein-protein interaction networks in age-related macular degeneration

Age-related macular degeneration (AMD) is one of the commonest causes of sight loss in the elderly population and to date there is no intervention that slows or prevents early AMD disease progressing to blinding neovascularization or geographic atrophy. AMD is a complex disease and factors proposed to contribute to the development and progression of disease include aging, genetics, epigenetics, oxidative stress, pro-inflammatory state, and life-style factors such as smoking, alcohol, and high fat diet. Here, we generate a knowledge repository of pathways and protein–protein interaction (PPI) networks likely to be implicated in AMD pathogenesis, such as complement activation, lipid trafficking and metabolism, vitamin A cycle, oxidative stress, proteostasis, bioenergetics, autophagy/mitophagy, extracellular matrix (ECM) turnover, and choroidal vascular dropout. Two disctinct clusters ermerged from the networks for parainflamation and ECM homeostasis, which may represent two different disease modules underlying AMD pathology. Our analyses also suggest that the disease manifests primarily in RPE/choroid and less in neural retina. The use of standardized syntax when generating maps of these biological processes (SBGN standard) and networks (PSI standard) enables visualization of complex information in graphical programs such as CellDesigner and Cytoscape and enhances reusability and extension of data. The ability to focus onto subnetworks, multiple visualizations and simulation options will enable the AMD research community to computationally model subnetworks or to test experimentally new hypotheses arising from connectivities in the AMD pathway map.