VDA-RWLRLS: An anti-SARS-CoV-2 drug prioritizing framework combining an unbalanced bi-random walk and Laplacian regularized least squares.

Shen, Ling; Liu, Fuxing; Huang, Li; Liu, Guangyi; Zhou, Liqian; Peng, Lihong

Shen, Ling; Liu, Fuxing; Huang, Li; Liu, Guangyi; Zhou, Liqian; Peng, Lihong.

Afiliação

Shen L; School of Computer Science, Hunan University of Technology, Zhuzhou, 412 007, Hunan, China.
Liu F; School of Computer Science, Hunan University of Technology, Zhuzhou, 412 007, Hunan, China.
Huang L; Academy of Arts and Design, Tsinghua University, Beijing, 10 084, Beijing, China; The Future Laboratory, Tsinghua University, Beijing, 10 084, Beijing, China.
Liu G; School of Computer Science, Hunan University of Technology, Zhuzhou, 412 007, Hunan, China.
Zhou L; School of Computer Science, Hunan University of Technology, Zhuzhou, 412 007, Hunan, China. Electronic address: zhoulq11@163.com.
Peng L; School of Computer Science, Hunan University of Technology, Zhuzhou, 412 007, Hunan, China; College of Life Sciences and Chemistry, Hunan University of Technology, Zhuzhou, 412 007, Hunan, China. Electronic address: plhhnu@163.com.

Comput Biol Med ; 140: 105119, 2021 Dec 07.

Article em En | MEDLINE | ID: mdl-34902608

Palavras-chave

Antiviral drug; Laplacian regularized least squares; Molecular docking; Molecular dynamics simulation; SARS-CoV-2; Unbalanced bi-random walk; Virus-drug association

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Clinical_trials / Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article

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