Author

Daniel Santos Perez

University of Michigan

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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Biophysics· 2

Signature Assays, Organisms & Methods

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Research Focus:drug response / drug discovery· 1 Approach:machine learning (classical)· 1 Assay:protein structure· 1 Research Focus:protein structure prediction· 1 Assay:proteomics· 1 Approach:statistical model· 1 Organism:virus· 1

Frequent Co-Authors

Sean McCarty· 2 shared Shu-Hang LiniD· 2 shared Terra SztainiD· 2 shared Grace ArhiniD· 1 shared Marissa DolorfinoiD· 1 shared Matthew J. O’MearaiD· 1 shared Yao FuiD· 1 shared Yao FuiD· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

8 top collaborators · 22 mutual co-author links

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2 shared papersBiophysics

Sean McCarty

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

Mechanism of molecular recognition revealed through dynamic drug binding pathways to SARS-CoV-2 main protease

Daniel Santos Perez, Grace Arhin, Yao Fu, Sean McCarty, Shu-Hang Lin, Terra Sztain

This study reveals the molecular mechanism of nirmatrelvir binding to SARS-CoV-2 main protease using combined NMR titrations and weighted ensemble simulations, identifying two distinct binding pathways and key residues involved in resistance.

bioRxiv · Sep 28, 2026 · PreprintBiophysics

Assessing the Generalizability of Machine Learning and Physics-Based Methods with DNA-Encoded Libraries

Marissa Dolorfino, Daniel Santos Perez, Yao Fu, Shu-Hang Lin, Sean McCarty, Matthew J. O’Meara, Terra Sztain

The paper evaluates ML and physics-based methods for predicting protein-ligand binding using DNA-encoded libraries, finding that no single method consistently generalizes to out-of-distribution chemical space.

Journal of Chemical Information and Modeling · Sep 18, 2026Peer-reviewedBiophysics