Antonia S. J. S. Mey

Orcid: 0000-0001-7512-5252

According to our database1, Antonia S. J. S. Mey authored at least 14 papers between 2016 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
A Computational Community Blind Challenge on Pan-Coronavirus Drug Discovery Data.
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J. Chem. Inf. Model., 2026

2025
Learning Binding Affinities via Fine-Tuning of Protein and Ligand Language Models.
J. Chem. Inf. Model., 2025

2024
From Proteins to Ligands: Decoding Deep Learning Methods for Binding Affinity Prediction.
J. Chem. Inf. Model., 2024

Benchmarking Active Learning Protocols for Ligand-Binding Affinity Prediction.
J. Chem. Inf. Model., 2024

Dirac–Bianconi Graph Neural Networks – Enabling Non-Diffusive Long-Range Graph Predictions.
Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM) at ICML 2024, 2024

2023
SILVR: Guided Diffusion for Molecule Generation.
J. Chem. Inf. Model., October, 2023

2021
Implementation of the QUBE Force Field in SOMD for High-Throughput Alchemical Free-Energy Calculations.
J. Chem. Inf. Model., 2021

Dynamic Profiling of β-Coronavirus 3CL Mpro Protease Ligand-Binding Sites.
J. Chem. Inf. Model., 2021

2020
Hybrid Alchemical Free Energy/Machine-Learning Methodology for the Computation of Hydration Free Energies.
J. Chem. Inf. Model., 2020

Assessment of Binding Affinity via Alchemical Free-Energy Calculations.
J. Chem. Inf. Model., 2020

2019
BioSimSpace: An interoperable Python framework for biomolecular simulation.
J. Open Source Softw., 2019

2018
Impact of domain knowledge on blinded predictions of binding energies by alchemical free energy calculations.
J. Comput. Aided Mol. Des., 2018

2017
Blinded predictions of host-guest standard free energies of binding in the SAMPL5 challenge.
J. Comput. Aided Mol. Des., 2017

2016
Blinded predictions of distribution coefficients in the SAMPL5 challenge.
J. Comput. Aided Mol. Des., 2016


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