An in silico drug repositioning workflow for host-based antivirals

Abstract

Summary Drug repositioning represents a cost- and time-efficient strategy for drug development. Artificial intelligence-based algorithms have been applied in drug repositioning by predicting drug-target interactions in an efficient and high throughput manner. Here, we present a workflow of in silico drug repositioning for host-based antivirals using specially defined targets, a refined list of drug candidates, and an easily implemented computational framework. The workflow described here can also apply to more general purposes, especially when given a user-defined druggable target gene set. For complete details on the use and execution of this protocol, please refer to Li et al. (2021) .

A deep learning-based drug repurposing screening and validation for anti-SARS-CoV-2 compounds by targeting the cell entry mechanism

“…We described the detailed drug repositioning protocol in our previously studies [10,11]. To specifically target cell entry mechanism of SARS-CoV-2, here we used a cohort of reported cell entry factors and viral S proteins (Supplementary Table 2) as the target gene set.…”

“…Thus, it is worthwhile to explore additional or complementary drug repurposing strategies for anti-SARS-CoV-2 agents. We previously developed a computational framework that integrates independent machine learning algorithms for predicting drug-target interaction (DTI) to efficiently repurpose existing marketed drugs and natural compounds in a high throughput manner against a given disease or mechanism by appropriately defining the target gene set [10,11]. Given the urgent and longlasting detrimental effects of COVID-19, it is tentative to apply these approaches to continually explore repurposed drug candidates for anti-SARS-CoV-2 purpose.…”

New Opportunities and Challenges for Health Professionals in the era of Artificial Intelligence – Review

“…The application of artificial intelligence-based algorithms in drug repositioning may be crucial for predicting drug-target interactions, allowing to eliminate the need of extensive, resourceconsuming in-vitro research [9]. Furthermore, another vital application of AI is creating a disease transmission model.…”