期刊
INTERDISCIPLINARY SCIENCES-COMPUTATIONAL LIFE SCIENCES
卷 12, 期 3, 页码 368-376出版社
SPRINGER HEIDELBERG
DOI: 10.1007/s12539-020-00376-6
关键词
Coronavirus; Deep learning; Drug screening; Homology modeling; 3C-like protease
资金
- National Key Research and Development Program of China [2018YFB0204403, 2016YFB0201305]
- National Science Foundation of China [U1813203, 61433012]
- National Natural Youth Science Foundation of China [31601028]
- Shenzhen Basic Research Fund [JCYJ20180507182818013, GGFW2017073114031767, JCYJ20170413093358429]
- China Postdoctoral Science Foundation [2019M653132]
- CAS Key Lab [2011DP173015]
- Shenzhen Discipline Construction Project for Urban Computing and Data Intelligence, Youth Innovation Promotion Association, CAS
A novel coronavirus, called 2019-nCoV, was recently found in Wuhan, Hubei Province of China, and now is spreading across China and other parts of the world. Although there are some drugs to treat 2019-nCoV, there is no proper scientific evidence about its activity on the virus. It is of high significance to develop a drug that can combat the virus effectively to save valuable human lives. It usually takes a much longer time to develop a drug using traditional methods. For 2019-nCoV, it is now better to rely on some alternative methods such as deep learning to develop drugs that can combat such a disease effectively since 2019-nCoV is highly homologous to SARS-CoV. In the present work, we first collected virus RNA sequences of 18 patients reported to have 2019-nCoV from the public domain database, translated the RNA into protein sequences, and performed multiple sequence alignment. After a careful literature survey and sequence analysis, 3C-like protease is considered to be a major therapeutic target and we built a protein 3D model of 3C-like protease using homology modeling. Relying on the structural model, we used a pipeline to perform large scale virtual screening by using a deep learning based method to accurately rank/identify protein-ligand interacting pairs developed recently in our group. Our model identified potential drugs for 2019-nCoV 3C-like protease by performing drug screening against four chemical compound databases (Chimdiv, Targetmol-Approved_Drug_Library, Targetmol-Natural_Compound_Library, and Targetmol-Bioactive_Compound_Library) and a database of tripeptides. Through this paper, we provided the list of possible chemical ligands (Meglumine, Vidarabine, Adenosine, d-Sorbitol, d-Mannitol, Sodium_gluconate, Ganciclovir and Chlorobutanol) and peptide drugs (combination of isoleucine, lysine and proline) from the databases to guide the experimental scientists and validate the molecules which can combat the virus in a shorter time.
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