Alexander Zhebrak

Hong Kong Science and Technology Parks Corporation — Hong Kong

Computer Science · Physical Sciences

6h-index616citations6works0.02yr avg
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Research Topics

Computational Drug Discovery Methods(6), Machine Learning in Materials Science(5), vaccines and immunoinformatics approaches(3), Tuberculosis Research and Epidemiology(2), Chromatography in Natural Products(1)

Publications6 total

Potential Non-Covalent SARS-CoV-2 3C-like Protease Inhibitors Designed Using Generative Deep Learning Approaches and Reviewed by Human Medicinal Chemist in Virtual Reality
2020· 44 citedOpen Access
Potential Non-Covalent SARS-CoV-2 3C-like Protease Inhibitors Designed Using Generative Deep Learning Approaches and Reviewed by Human Medicinal Chemist in Virtual Reality
2020· 29 citedOpen Access
Potential COVID-2019 3C-like Protease Inhibitors Designed Using Generative Deep Learning Approaches
2020· 62 citedOpen Access
Potential COVID-2019 3C-like Protease Inhibitors Designed Using Generative Deep Learning Approaches
2020· 97 citedOpen Access
Potential 2019-nCoV 3C-like Protease Inhibitors Designed Using Generative Deep Learning Approaches
2020· 105 citedOpen Access
Entangled Conditional Adversarial Autoencoder for de Novo Drug Discovery
Molecular Pharmaceutics·2018· 279 cited

Frequent Co-authors

Daniil Polykovskiy(6), Yan A. Ivanenkov(6), Vladimir Aladinskiy(6), Alex Zhavoronkov(6), Bogdan Zagribelnyy(5), Victor A. Terentiev(5), Dmitry S. Bezrukov(5), Rim Shayakhmetov(5), Andrey Filimonov(5), Quentin Vanhaelen(5), Alex Aliper(5), Philipp S. Orekhov(3), Yilin Yan(3), О. В. Попова(3), Michael R. Bishop(2), Steve McCloskey(2), Edgardo Leija(2), Deborah Bright(2), Keita Funakawa(2), Yen‐Chu Lin(2)