Author

Andrew L. Ferguson

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Preprint Sep 2026

Quantum-accurate atomistic modeling of enzyme catalysis using a machine learned potential

This work demonstrates quantum-accurate treatment of all-atom, complete enzymes in explicit solvent comprising up to 54k atoms and 1 microsecond of total simulation time using the machine-learned interatomic potential (MLIP) eSEN-omol, establishing MLIPs as a practical route to QM-accurate simulations of enzyme catalys...

Meng Gao, Armin Shayesteh Zadeh, Aniruddha Seal et al. · 1 citation · ⚡1

Preprint Sep 2026

Quantum-accurate atomistic modeling of enzyme catalysis using a machine learned potential

Electronic rearrangements associated with bond forming/breaking in catalytic enzymes require quantum mechanical (QM) treatment beyond classical molecular mechanics (MM). Hybrid QM/MM methods enable tractable simulations but require system-specific setup and are sensitive to the QM region choice and treatment of the QM/...

Meng Gao, Armin Shayesteh Zadeh, Aniruddha Seal et al. · 0 citations

Preprint Aug 2026

Data-driven reconstruction of dynamical systems using Takens'Theorem, manifold learning, and universal function approximators

An algorithmic framework, TAkens Reconstruction (TAR), to analyze and reconstruct arbitrary dynamical systems from low-dimensional time series using an integration of Takens'Delay Embedding Theorem, manifold learning techniques, and universal function approximators is developed.

Maximilian Topel, Andrew L. Ferguson · 0 citations