English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

COVID-19 has fast-paced drug re-positioning for its treatment. This workbuilds computational models for the same. The aim is to assist clinicians witha tool for selecting prospective antiviral treatments. Since the virus is knownto mutate fast, the tool is likely to help clinicians in selecting the rightset of antivirals for the mutated isolate.  The main contribution of this work is a manually curated database publiclyshared, comprising of existing associations between viruses and theircorresponding antivirals. The database gathers similarity information using thechemical structure of drugs and the genomic structure of viruses. Along withthis database, we make available a set of state-of-the-art computational drugre-positioning tools based on matrix completion. The tools are first analysedon a standard set of experimental protocols for drug target interactions. Thebest performing ones are applied for the task of re-positioning antivirals forCOVID-19. These tools select six drugs out of which four are currently undervarious stages of trial, namely Remdesivir (as a cure), Ribavarin (incombination with others for cure), Umifenovir (as a prophylactic and cure) andSofosbuvir (as a cure). Another unanimous prediction is Tenofovir alafenamide,which is a novel tenofovir prodrug developed in order to improve renal safetywhen compared to the counterpart tenofovir disoproxil. Both are under trail,the former as a cure and the latter as a prophylactic. These results establishthat the computational methods are in sync with the state-of-practice. We alsodemonstrate how the selected drugs change as the SARS-Cov-2 mutates over time,suggesting the importance of such a tool in drug prediction.  The dataset and software is available publicly athttps://github.com/aanchalMongia/DVA and the prediction tool with auser-friendly interface is available at http://dva.salsa.iiitd.edu.in.

A computational approach to aid clinicians in selecting anti-viral drugs for COVID-19 trials