Drug Repurposing: A Network-based Approach to Amyotrophic Lateral Sclerosis

Abstract

The continuous adherence to the conventional "one target, one drug" paradigm has failed so far to provide effective therapeutic solutions for heterogeneous and multifactorial diseases as amyotrophic lateral sclerosis (ALS), a rare progressive and chronic, debilitating neurological disease for which no cure is available. The present study is aimed at finding innovative solutions and paradigms for therapy in ALS pathogenesis, by exploiting new insights from Network Medicine and drug repurposing strategies. To identify new drug-ALS disease associations, we exploited SAveRUNNER, a recently developed network-based algorithm for drug repurposing, which quantifies the proximity of disease-associated genes to drug targets in the human interactome. We prioritized 403 SAveRUNNER-predicted drugs according to decreasing values of network similarity with ALS. Among catecholamine, dopamine, serotonin, histamine, and GABA receptor modulators, as well as angiotensin-converting enzymes, cyclooxygenase isozymes, and serotonin transporter inhibitors, we found some interesting no customary ALS drugs, including amoxapine, clomipramine, mianserin, and modafinil. Furthermore, we strengthened the SAveRUNNER predictions by a gene set enrichment analysis that confirmed modafinil as a drug with the highest score among the 121 identified drugs with a score > 0. Our results contribute to gathering further proofs of innovative solutions for therapy in ALS pathogenesis.

Current Drug Repurposing Strategies for Rare Neurodegenerative Disorders

“…An open-label, control study and a placebo-controlled trial with modafinil showed that this drug is safe and well tolerated and may, indeed, decrease fatigue in ALS patients (Carter et al, 2005;Rabkin et al, 2009). These results and the ones from the in silico prediction study (Fiscon et al, 2021) point to modafinil as a promising drug for ALS treatment whose beneficial effect needs to be proved in further clinical trials.…”

“…These strategies that exploit current knowledge on disease-associated genes and disease mechanisms, protein-protein interactions, signaling networks, and drug-target interactions allow to save time and resources on the identification of candidate compounds. Accordingly, Fiscon et al (2021) exploited SAveRUNNER, a recently developed network-based algorithm for drug repurposing, which quantifies the proximity of diseaseassociated genes to drug targets to identify drug candidates for ALS. This approach allowed to identify 403 repurposable drugs that were strongly associated with the disease.…”

“…This approach allowed to identify 403 repurposable drugs that were strongly associated with the disease. Most of these compounds belonged to drug families already identified as having disease-modifying potential, but some were non-customary ALS drugs (Fiscon et al, 2021). Among the latter, modafinil, a compound that elevates histamine levels in the neocortex and the hypothalamus and which is currently indicated for the treatment of hypersomnolence and narcolepsy (Ishizuka et al, 2010), was identified as the drug with the highest predictive score for ALS alone or combined with other drugs that are currently being tested in clinical trials (Fiscon et al, 2021).…”

Protein Network Analysis Reveals a Functional Connectivity of Dysregulated Processes in ALS and SMA

“…Moreover, network biology supports researchers to identify potential new treatment strategies for neurodegenerative diseases. 9 , 47 Here, we performed a network analysis on published studies that focus on fatty acid metabolism in SMA patients and mouse models, 10 KLF15 overexpression in an SMA mouse model 23 and B-Raf signaling in SMA. 22 Moreover, further proteins were added that are involved in actin and stress granules dynamics as well as the most common ALS-associated proteins ( Table 1 ).…”

A Comparison of Network-Based Methods for Drug Repurposing along with an Application to Human Complex Diseases

“…Following the Network Medicine perspective, even the action of a drug can be interpreted as a local perturbation of the interactome, and thus, for a drug to be on-target effective against a specific disease or to cause off-target adverse effects, its target proteins should be within or in the immediate vicinity of the corresponding disease module. In recent years, several network-based approaches marrying this philosophy have been developed to aid the identification of the specific interactome neighborhood that is perturbed in a certain disease [ 12 , 13 , 14 , 15 , 16 ] and/or for the effect of a certain drug, and guide the search for therapeutic targets, identify comorbidities, as well as rapidly detect drug repurposing candidates [ 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 ]. In order to quantify the interplay between drug targets and disease-specific proteins in the human interactome, in [ 17 ], the authors used a network-based drug-disease proximity measure, which prioritized associations between drugs and diseases located in the same network neighborhoods based on the average shortest paths.…”