Determination of Novel SARS-CoV-2 Inhibitors by Combination of Deep Learning, 
In silico Analysis and Similarity Search

Güner, Ersin; Özkan, Özgür; Yalçin-Özkat, Gözde; Ölgen, Süreyya

doi:10.2174/0115734064265609231026063624

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Determination of Novel SARS-CoV-2 Inhibitors by Combination of Deep Learning, In silico Analysis and Similarity Search

Güner, E., Özkan, Ö., Yalçin-Özkat, G., & Ölgen, S. (2024). Determination of Novel SARS-CoV-2 Inhibitors by Combination of Deep Learning, In silico Analysis and Similarity Search. Medicinal Chemistry, 20(2), 153-231. doi:10.2174/0115734064265609231026063624.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000E-1ED2-4 Version Permalink: https://hdl.handle.net/21.11116/0000-000E-772D-B

Genre: Journal Article

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Creators:
Güner, Ersin¹, Author
Özkan, Özgür², Author
Yalçin-Özkat, Gözde^{3, 4}, Author
Ölgen, Süreyya¹, Author

Affiliations:
1Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Biruni University, 34010 Topkapı, İstanbul, Turkey, ou_persistent22
2Teknokent Arı, Pinticks Software Company, Istanbul Technical University, Reşitpaşa Mah. Katar Street, No:4/B204 Sarıyer, İstanbul, Turkey , ou_persistent22
3Bioengineering Department, Faculty of Engineering and Architecture, Recep Tayyip Erdogan University, 53100 Rize, Turkey, ou_persistent22
4Molecular Simulations and Design, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society, ou_1738148

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Language(s): eng - English

Dates: Date issued: 2024

Publication Status: Issued

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Rev. Type: Peer

Identifiers: DOI: 10.2174/0115734064265609231026063624

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Title: Medicinal Chemistry

Abbreviation : Med. Chem.

Source Genre: Journal

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Publ. Info: Sharjah : Bentham Sc. Publ.

Pages: - Volume / Issue: 20 (2) Sequence Number: - Start / End Page: 153 - 231 Identifier: ISSN: 1573-4064
CoNE: https://pure.mpg.de/cone/journals/resource/1573-4064