Author

S. Izadi

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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Biochemistry· 1 Bioinformatics· 1

Signature Assays, Organisms & Methods

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Research Focus:protein folding & dynamics· 2 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Approach:machine learning (classical)· 1 Assay:protein structure· 1 Assay:proteomics· 1 Approach:statistical model· 1

Frequent Co-Authors

A. M. Watkins· 1 shared B. Vani· 1 shared D. Davidson· 1 shared D. Sommer· 1 shared E. Park· 1 shared F. A. Dreyer· 1 shared F. J. Irudayanathan· 1 shared J. H. Lee· 1 shared

Activity by Year

2021-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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1 shared paperBioinformatics

A. M. Watkins

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2 papers

Recent·Most cited

Rapid generation of antibody conformational ensembles using machine learning

Pranav V Rao, D. Sommer, D. Davidson, R. G. Alberstein, J. Ludwiczak, J. Kleinhenz, B. Vani, E. Park, J. H. Lee, S. Izadi, J. R. Kiefer, R. Bonneau, S. P. Mahajan, A. M. Watkins, F. A. Dreyer

This paper introduces Cadense, a machine learning framework that generates antibody conformational ensembles from sequence, capturing dynamic properties and improving docking accuracy.

bioRxiv · Nov 9, 2026 · PreprintBioinformatics

Divining Deamidation and Isomerization in Therapeutic Proteins: Effect of Neighboring Residue

F. J. Irudayanathan, J. Zarzar, J. Lin, S. Izadi

This study identifies key molecular indicators of asparagine deamidation and aspartic acid isomerization in therapeutic antibodies and proposes a physics-based model to predict their propensity.

bioRxiv · Jul 26, 2021 · PreprintBiochemistry