Your browser doesn't support javascript.
COVIDrugNet: a network-based web tool to investigate the drugs currently in clinical trial to contrast COVID-19.
Menestrina, Luca; Cabrelle, Chiara; Recanatini, Maurizio.
  • Menestrina L; Department of Pharmacy and Biotechnology, Alma Mater Studiorum - University of Bologna, 40126, Bologna, Italy.
  • Cabrelle C; Department of Pharmacy and Biotechnology, Alma Mater Studiorum - University of Bologna, 40126, Bologna, Italy.
  • Recanatini M; Department of Pharmacy and Biotechnology, Alma Mater Studiorum - University of Bologna, 40126, Bologna, Italy. maurizio.recanatini@unibo.it.
Sci Rep ; 11(1): 19426, 2021 09 30.
Article in English | MEDLINE | ID: covidwho-1447322
Preprint
This scientific journal article is probably based on a previously available preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
See preprint
ABSTRACT
The COVID-19 pandemic poses a huge problem of public health that requires the implementation of all available means to contrast it, and drugs are one of them. In this context, we observed an unmet need of depicting the continuously evolving scenario of the ongoing drug clinical trials through an easy-to-use, freely accessible online tool. Starting from this consideration, we developed COVIDrugNet ( http//compmedchem.unibo.it/covidrugnet ), a web application that allows users to capture a holistic view and keep up to date on how the clinical drug research is responding to the SARS-CoV-2 infection. Here, we describe the web app and show through some examples how one can explore the whole landscape of medicines in clinical trial for the treatment of COVID-19 and try to probe the consistency of the current approaches with the available biological and pharmacological evidence. We conclude that careful analyses of the COVID-19 drug-target system based on COVIDrugNet can help to understand the biological implications of the proposed drug options, and eventually improve the search for more effective therapies.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: Computational Biology / COVID-19 Drug Treatment Type of study: Prognostic study / Randomized controlled trials Limits: Humans Language: English Journal: Sci Rep Year: 2021 Document Type: Article Affiliation country: S41598-021-98812-0

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Main subject: Computational Biology / COVID-19 Drug Treatment Type of study: Prognostic study / Randomized controlled trials Limits: Humans Language: English Journal: Sci Rep Year: 2021 Document Type: Article Affiliation country: S41598-021-98812-0