Author

Dominic A. Rufa

Memorial Sloan Kettering Cancer CenterORCID 0000-0003-0930-9445Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Biophysics· 2

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:benchmarking· 1 Research Focus:drug response / drug discovery· 1 Approach:graph neural network· 1 Assay:protein sequence· 1 Assay:protein structure· 1 Approach:statistical model· 1

Frequent Co-Authors

Amogh SoodiD· 1 shared Andrea BortolatoiD· 1 shared Da TengiD· 1 shared John D. ChoderaiD· 1 shared Josh FassiD· 1 shared Kevin RyczkoiD· 1 shared Mary PitmaniD· 1 shared Pratyush TiwaryiD· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

9 top collaborators · 22 mutual co-author links

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1 shared paperBiophysics

Amogh SoodORCID

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2 papers

Recent·Most cited

BiophysicsbioRxivPreprintJun 12, 2026

MAHLER: Integrating Metadynamics and Inverse Folding to Predict Antibody-Antigen Kinetics

Da Teng, Mary Pitman, Punit K. Jha…·Pratyush Tiwary

MAHLER predicts antibody-antigen dissociation kinetics using a hybrid machine learning and physics approach, achieving screening-grade accuracy and fast computation.

DOI 10.64898/2026.06.10.731383

protein structureprotein sequence

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BiophysicsbioRxivPreprintJan 6, 2025

Fine-tuning molecular mechanics force fields to experimental free energy measurements

Dominic A. Rufa, Josh Fass, John D. Chodera

This study fine-tunes a GNN-based molecular mechanics force field using experimental hydration free energy data to improve predictions of related free energies.

5 citations

deep learninggraph neural network

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