Identification of potential SARS-CoV-2 inhibitors from South African medicinal plant extracts using molecular modelling approaches.

Dwarka, Depika; Agoni, Clement; Mellem, John Jason; Soliman, Mahmoud E; Baijnath, Himansu

Dwarka, Depika; Agoni, Clement; Mellem, John Jason; Soliman, Mahmoud E; Baijnath, Himansu.

Afiliação

Dwarka D; Department of Biotechnology and Food Technology, Durban University of Technology, KwaZulu-Natal, South Africa.
Agoni C; Molecular Bio-Computation and Drug Design Laboratory, School of Health Sciences, Discipline of Pharmaceutical Sciences, University of KwaZulu-Natal, KwaZulu-Natal, South Africa.
Mellem JJ; Dream Laboratory Consult, Ghana, West Africa.
Soliman ME; Department of Biotechnology and Food Technology, Durban University of Technology, KwaZulu-Natal, South Africa.
Baijnath H; Molecular Bio-Computation and Drug Design Laboratory, School of Health Sciences, Discipline of Pharmaceutical Sciences, University of KwaZulu-Natal, KwaZulu-Natal, South Africa.

S Afr J Bot ; 133: 273-284, 2020 Sep.

Article em En | MEDLINE | ID: mdl-32839635

Palavras-chave

COVID-19; Molecular dynamics simulations; SARS-CoV-2 3C-like main protease; SARS-CoV-2 RNA-dependent polymerase; SARS-CoV-2 receptor binding domain

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Revista: S Afr J Bot Ano de publicação: 2020 Tipo de documento: Article País de afiliação: África do Sul País de publicação: África do Sul

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