Author

Yurii Moroz

Taras Shevchenko National University of Kyiv

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 1 Pharmacology & Toxicology· 1

Signature Assays, Organisms & Methods

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Research Focus:drug response / drug discovery· 2 Approach:deep learning· 1 Approach:experimental assay· 1 Assay:proteomics· 1 Approach:statistical model· 1

Frequent Co-Authors

Aashish ManglikiD· 1 shared Alan AshworthiD· 1 shared Alexander Makriyannis· 1 shared Allan I. BasbaumiD· 1 shared Assaf AloniD· 1 shared Brandon Lam· 1 shared Brian K. ShoichetiD· 1 shared Bryan L. RothiD· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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1 shared paperPharmacology & Toxicology

Aashish ManglikORCID

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2 papers

Recent·Most cited

Combinatorial docking and molecular generation to navigate over 100-billion molecules for prospective ligand discovery

Jianxiang Zhang, Chao Yang, Yu Zhang, Xiao Chen, Brandon Lam, Claire Bryant, Shabareesh Pidathala, Yangzhi Wang, Yurii Moroz, Dmytro S. Radchenko, Assaf Alon, Chia‐Hsueh Lee, Zhe Zhang, Jiankun Lyu

The paper introduces CombiDOCK and MINT-Dock to efficiently screen large molecule libraries for ligand discovery, achieving high hit rates and computational efficiency.

bioRxiv · Jun 11, 2026 · PreprintBioinformatics

Toward a Random Background for Ligand Optimization

Xinyu Xu, Olivier Mailhot, G.J. Correy, XP Huang, Joao M. Braz, Da Shi, Karthik Srinivasan, Kara Zielinski, Yuliia Holota, Yuliia Kuziv, Christos Iliopoulos‐Tsoutsouvas, Nathan D. Levinzon, Yagmur Umay Doruk, Moira M. Rachman, Morgan E. Diolaiti, , Brian K. Shoichet

This study systematically evaluates the effectiveness of random small perturbations in ligand optimization, finding 11.2% of analogs improved potency by ≥10-fold but often had worse pharmacokinetics.

bioRxiv · May 13, 2026 · PreprintPharmacology & Toxicology