Author

Shengyu Zhang

University of CambridgeORCID 0000-0001-6901-5874Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Bioinformatics· 1 Biophysics· 1 Molecular Biology· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:deep learning· 3 Research Focus:drug response / drug discovery· 2 Assay:protein structure· 2 Research Focus:protein structure prediction· 2 Organism:human· 1 Approach:mechanistic / dynamical model· 1 Approach:transformer / foundation model· 1

Frequent Co-Authors

Michele VendruscoloiD· 3 shared Sebastian Pujalte OjedaiD· 2 shared Adelie Auriane Berenice LouetiD· 1 shared Aixia YaniD· 1 shared Donghui Huo· 1 shared Ellis BakeriD· 1 shared Hilbert Yuen In LamiD· 1 shared Josef HankeiD· 1 shared

Activity by Year

2023-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 27 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

3 shared papersMolecular Biology

Michele VendruscoloORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

OmniBind: Proteome-Wide Promiscuity Predictions for Early-Stage Drug Screening

Josef Hanke, Sebastian Pujalte Ojeda, Ruoh Wen Cheong, Logan M. Glasstetter, Ellis Baker, Hilbert Yuen In Lam, Michaela Brezinova, Adelie Auriane Berenice Louet, Shengyu Zhang, Michele Vendruscolo

OmniBind predicts small-molecule promiscuity across the human proteome using a neural network, enabling faster early-stage drug screening with improved specificity over affinity alone.

bioRxiv · Mar 18, 2026 · PreprintMolecular Biology

AlphaFold-Metainference: Prediction of Structural Ensembles of Disordered Proteins

Z. Faidon Brotzakis, Shengyu Zhang, Mhd Hussein Murtada, Michele Vendruscolo

This paper introduces AlphaFold-Metainference to predict structural ensembles of disordered proteins using AlphaFold-derived distances in molecular dynamics simulations.

bioRxiv · Nov 9, 2024 · PreprintBiophysics

Sequence-based drug design using transformers

Shengyu Zhang, Donghui Huo, Robert I. Horne, Yumeng Qi, Sebastian Pujalte Ojeda, Aixia Yan, Michele Vendruscolo

This paper introduces Ligand-Transformer, a deep learning framework for predicting protein-ligand interactions, and demonstrates its application in identifying inhibitors for specific targets and studying disordered proteins.

bioRxiv · Nov 27, 2023 · PreprintBioinformatics