Pathway and network-based strategies to translate genetic discoveries into effective therapies

Abstract

One way to design a drug is to attempt to phenocopy a genetic variant that is known to have the desired effect. In general, drugs that are supported by genetic associations progress further in the development pipeline. However, the number of associations that are candidates for development into drugs is limited because many associations are in non-coding regions or difficult to target genes. Approaches that overlay information from pathway databases or biological networks can expand the potential target list. In cases where the initial variant is not targetable or there is no variant with the desired effect, this may reveal new means to target a disease. In this review, we discuss recent examples in the domain of pathway and network-based drug repositioning from genetic associations. We highlight important caveats and challenges for the field, and we discuss opportunities for further development.

POLR3-Related Leukodystrophy: Exploring Potential Therapeutic Approaches

“…Limited knowledge of the exact pathophysiological mechanisms underlying POLR3-HLD also poses a challenge for the evaluation of the most effective treatment options. When specific mechanisms are implicated in genetic diseases, it is possible to focus on targeting alternative pathways in treatment approaches, in order to overpass the mechanism containing the defective protein (Greene and Voight, 2016 ). Although the cellular pathophysiological mechanisms associated with POLR3-HLD have yet to be uncovered, studies have shown that mutations in POLR3 subunits can cause disruptions on several molecular levels.…”

Epidrug Repurposing: Discovering New Faces of Old Acquaintances in Cancer Therapy

“…Computational methods include the study of large sets of data (e.g., gene expression, chemical composition, genotype or proteomic data or electronic health records) that lead to the development of reprofiling hypotheses (118). Computational approaches include: signature matching, which results for comparing a drug signature such as its transcriptomic, structural or adverse effect profile to that of another pharmaceutical product or disease phenotype (119); molecular docking, a structural computational strategy focused to predict complementarity of the binding site between a drug and a receptor (120); genetic association, a high throughput analysis of genes associated with a disease which can turn out to be potential targets for drugs (121); pathway mapping, another approach that analyses biological pathways in order to develop networks of drugs or disorders based on patterns in gene expression, disease biology, protein interactions or GWAS data to better classify repurposable candidates (122); retrospective clinical analysis, a systematic review of electronic health records, data from clinical trials and surveillances post-marketing could be useful identifying repurposable drugs; and novel sources, which is the combination of large-scale in-vitro drug screens with genomic data, electronic health records and self-reported patient data represents new ways to repurpose drugs (123,124).…”

Reprogramming of antibiotics to combat antimicrobial resistance

“…[114] Other pathways are also targeted by the blockage of Ca + ion, as it is involved in many signaling pathways and shows in vitro activity against the Ebola virus, [115] encephalitis virus, [116] and Lassa fever. [117] T A B L E 2 Different types of adjuvantbased drugs [78] Also, a network-wide association study (net-WAS) was used by Greene et al [118] to identify diseases and gene relationships more accurately. netWAS is an association of GWAS and tissue-specific functional interaction networks.…”