Drug repositioning is the identification of the new indications for drugs approved for medical use. The availability of information on the pharmacological and toxicological characteristics of a known drug enables its swift adoption in a new nosology [1]. The need for a rapid response to the COVID-19 pandemic has given the impetus to a large-s cale research into the associated opportunities. A Google search for “COVID-19 AND drug repurposing” returns over six million results. Remdesivir, Favipiravir and Umifenovir (Arbidol) were originally designed for other indications and later repositioned to treat the SARSCoV-2 infection. Same is true about Triazavirin, Nobasit, Nafamostat and a few other drugs that currently are subjects of clinical trials involving COVID-19 patients.

The search for the new pharmacological effects that known drugs may have involves in silico and in vitro studies. Computer- aided investigations rely on models of interaction of the analyzed compounds with molecular targets, identification of analogs based on the structural similarity, analysis of the “structure-a ctivity” relationships using machine learning, and establishing associations by the network pharmacology [2]. The in silico approach can be applied to virtual (not yet synthesized) molecules providing the initial set of “hits”. Next, the predictions delivered by such computer-aided investigations are validated in the in vitro experiments. The in vitro determination of anticoronavirus potency relies on biochemical and cellular assays [3, 4]. Preliminary selection (virtual screening) of the potentially active compounds that is based on the data obtained through in silico investigations significantly increases the chances of success [5].

A number of large-scale experimental studies aimed to screen in vitro 1,400 to 12,000 drugs against one or several targets; the efforts yielded shortlists of candidates for repositioning. In many cases, different test systems gave different results for the same drug [3,4,6]. The reasons behind this inconsistence are lack of generally accepted reference drugs and absence of unifying standards for assays, which are developed independently by different researchers.

As noted by the authors of a recent analytical review published in the Chemical Society Reviews that looked into the computational approaches employed for COVID-19 drug discovery: «… truly impactful computational tools must deliver actionable, experimentally testable hypotheses enabling the discovery of novel drugs and drug combinations, and that open science and rapid sharing of research results are critical to accelerate the development of novel, much needed therapeutics for COVID-19» [2].

In conclusion, it should be noted that current conditions make drug repositioning especially relevant. The reason behind this relevancy is the significant time required to develop innovative drugs in a pandemic, regardless of the advancements of translational medicine. At the same time, to select the most promising drugs for further experimental validation of their effects in the context of repositioning for SARS-CoV-2/COVID-19 (based on the analysis of the available data), it is necessary to integrate and analyze all the available information obtained in silico, in vitro and in vivo studies.