Author

Tetiana Khakhula

University of GenevaORCID 0009-0001-2551-3254Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Assay:multiome· 1 Research Focus:protein folding & dynamics· 1 Approach:statistical model· 1

Frequent Co-Authors

Francesco Luigi GervasioiD· 1 shared Marc SchulzeiD· 1 shared Nicola PiasentiniD· 1 shared Simone AureliiD· 1 shared Valerio RizziiD· 1 shared

Activity by Year

2025-2025 · peak 1/yr

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5 top collaborators · 10 mutual co-author links

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1 shared paperBiophysics

Francesco Luigi GervasioORCID

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1 paper

Recent·Most cited

BiophysicsThe Journal of Chemical PhysicsPeer-reviewedOct 23, 2025

All You Need Is Water: Converging Ligand Binding Simulations with Hydration Collective Variables

Marc Schulze, Tetiana Khakhula, Nicola Piasentin…·Francesco Luigi Gervasio

This paper introduces a data-driven method to construct solvation-based collective variables for molecular dynamics simulations, achieving accurate binding free energy landscapes with improved efficiency.

2 citations

multiomedeep learning

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