Author

J. Zavadlav

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#artificial intelligence Jun 2026

ConSolv: Solvent-Conditional Machine Learning Implicit Solvent Potential

ConSolv is presented, a solvent-conditional MLP architecture that explicitly incorporates solvent effects on solute interactions through an attention-based solvent embedding block that outperforms classical explicit solvent methods and selected ab initio implicit solvent approaches across multiple solvation free energy...

Lin-Ying Zhang, J. Zavadlav · Journal of Chemical Theory a... · 1 citation

Jul 2026

Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy

The Transferable Water Implicit Network (TWIN) is introduced, an implicit water MLP parametrized entirely by an Equivariant Graph Neural Network and trained solely on ab initio and experimental labels, consistently outperforming previous machine-learning-based implicit solvent or coarse-grained models.

Jan Eckwert, J. Zavadlav · arXiv.org · 0 citations