Author

Sebastien Ghent

University of South Florida

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 Biophysics· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Approach:deep learning· 2 Assay:protein structure· 2 Approach:statistical model· 2 Approach:benchmark study· 1 Approach:diffusion model· 1 Assay:protein sequence· 1 Research Focus:protein structure prediction· 1

Frequent Co-Authors

Taseef RahmaniD· 2 shared Vladimir Nikolaevich UverskyiD· 2 shared Juan Velasquez· 1 shared Tuan Minh Dao· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

4 top collaborators · 5 mutual co-author links

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2 shared papersBioinformatics

Taseef RahmanORCID

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2 papers

Recent·Most cited

BioinformaticsProteins Structure Function and BioinformaticsPeer-reviewedOct 12, 2026

✦ In-depth digest

AlphaFold3 and Intrinsically Disordered Proteins: Reliable Monomer Prediction, Unpredictable Multimer Performance

Tuan Minh Dao, Sebastien Ghent, Vladimir Nikolaevich Uversky, Taseef Rahman

AlphaFold3 pLDDT matches AlphaFold2 at calling disordered residues (Matthews correlation 0.693 vs 0.701); on disorder-containing complexes mean DockQ is similar, but interface features explain less variance (42% vs 58%).

5 citationstop 2%

protein structureprotein sequence

BiophysicsbioRxivPreprintJun 8, 2026

Do AI Structure Predictors Capture Bound-State Disorder? A Benchmark on Fuzzy Protein Complexes

Juan Velasquez, Sebastien Ghent, Vladimir Nikolaevich Uversky, Taseef Rahman

This paper benchmarks AI structure predictors on fuzzy protein complexes, finding they consistently violate 30% of NOE restraints and show poor helicity correlation with thermodynamic expectations.

DOI 10.64898/2026.05.30.729023

protein structuredeep learning