Machine intelligence design of 2019-nCoV drugs

Wuhan coronavirus, called 2019-nCoV, is a newly emerged virus that infected more than 9692 people and leads to more than 213 fatalities by January 30, 2020. Currently, there is no effective treatment for this epidemic. However, the viral protease of a coronavirus is well-known to be essential for its replication and thus is an effective drug target. Fortunately, the sequence identity of the 2019-nCoV protease and that of severe-acute respiratory syndrome virus (SARS-CoV) is as high as 96.1%. We show that the protease inhibitor binding sites of 2019-nCoV and SARS-CoV are almost identical, which means all potential anti-SARS-CoV chemotherapies are also potential 2019-nCoV drugs. Here, we report a family of potential 2019-nCoV drugs generated by a machine intelligence-based generative network complex (GNC). The potential effectiveness of treating 2019-nCoV by using some existing HIV drugs is also analyzed.

Medienart:

E-Artikel

Erscheinungsjahr:

2020

Erschienen:

2020

Enthalten in:

Zur Gesamtaufnahme - year:2020

Enthalten in:

bioRxiv : the preprint server for biology - (2020) vom: 04. Feb.

Sprache:

Englisch

Beteiligte Personen:

Gao, Kaifu [VerfasserIn]
Nguyen, Duc Duy [VerfasserIn]
Wang, Rui [VerfasserIn]
Wei, Guo-Wei [VerfasserIn]

Links:

Volltext

Themen:

2019-nCoV
Deep learning
Preprint
SARS-CoV

Anmerkungen:

Date Revised 30.03.2024

published: Electronic

Citation Status PubMed-not-MEDLINE

doi:

10.1101/2020.01.30.927889

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM310907780