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Antonia Panescu

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#artificial intelligence Preprint Oct 2026

Zatom-2: Multitask Pretraining on Atomistic Data for Generative Modeling across Domains

Unified atomistic modeling has the potential to accelerate discovery in chemistry, materials science, and biology by bridging data-rich chemical domains and data-scarce biological contexts. However, existing generative approaches to atomistic modeling remain highly specialized to scientific disciplines (chemistry vs. b...

M. Cretu, A. Abrudan, Antonia Panescu et al. · 0 citations
Open access Sep 2026

Improving ABFE Calculations for GPCRs by Addressing Errors in Apo-State Representation

Free energy perturbation (FEP) methods provide a robust computational framework for predicting protein-ligand binding affinities and have seen increased adoption in drug discovery workflows. Among these, absolute binding free energy (ABFE) calculations are especially valuable as they enable affinity prediction for no...

N. M. Anand, Antonia Panescu, Ronald M. A. Knegtel et al. · 0 citations

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