Computational and Practical Aspects of Drug Repositioning

Abstract

The concept of the hypothesis-driven or observational-based expansion of the therapeutic application of drugs is very seductive. This is due to a number of factors, such as lower cost of development, higher probability of success, near-term clinical potential, patient and societal benefit, and also the ability to apply the approach to rare, orphan, and underresearched diseases. Another highly attractive aspect is that the ''barrier to entry'' is low, at least in comparison to a full drug discovery operation. The availability of high-performance computing, and databases of various forms have also enhanced the ability to pose reasonable and testable hypotheses for drug repurposing, rescue, and repositioning. In this article we discuss several factors that are currently underdeveloped, or could benefit from clearer definition in articles presenting such work. We propose a classification scheme-drug repositioning evidence level (DREL)-for all drug repositioning projects, according to the level of scientific evidence. DREL ranges from zero, which refers to predictions that lack any experimental support, to four, which refers to drugs approved for the new indication. We also present a set of simple concepts that can allow rapid and effective filtering of hypotheses, leading to a focus on those that are most likely to lead to practical safe applications of an existing drug. Some promising repurposing leads for malaria (DREL-1) and amoebic dysentery (DREL-2) are discussed.

DrugCentral: online drug compendium

“…Drugs withdrawn due to other than safety reasons will be flagged and annotated with indication/pharmacology/MoA to create a comprehensive list of drugs with potential for drug repurposing (28,29). Drug adverse events from FDA AERS database (https://open.fda.gov/) and SIDER (21) will be used to enhance the drug safety profile of existing drug reports.…”

Exploring the new horizons of drug repurposing: A vital tool for turning hard work into smart work

“…The information helps in development of various computational approaches rapidly which are cost effective and have much less barriers [109]. In silico approaches are based on merging and analysing a plethora of information regarding drug-disease relationship [110].…”

From gene networks to drugs: systems pharmacology approaches for AUD

“…Beyond the sign (+/−) and magnitude of the connectivity score, there are additional practical considerations for prioritizing candidate compounds (Oprea and Overington 2015). For example, any identified high-priority candidate drugs for AUD treatment would also benefit from having 1) known oral dosing data available, 2) have little or no safety warnings (especially regarding liver toxicity), 3) have low abuse liability, 4) low drug-drug interaction potential, 5) negligible cytotoxic actions 6) high brain penetrability, among others.…”

“…However, this is not the case. Meeting the ideal practical considerations outlined above could eliminate virtually all candidate compounds (Oprea and Overington 2015). In that case, medicinal chemistry approaches could be used to modify the chemical structure to suit the desired product profile.…”