Publications

Publications

My research has focused on machine learning, statistical mechanics and data-driven approaches to biomolecular dynamics, particularly the integration of molecular simulations with experimental data.

Earlier publications appear under the name Christopher Kolloff.

ORCID ↗

Peer-reviewed publications

Minimum-Excess-Work Guidance: Score-Based Sampling with Experimental Data or Sparse Restraints

Journal of Chemical Theory and Computation
22(11), 5838–5848, 2026

DOI ↗Publisher ↗

Conformational Quenching in an Engineered Lipocalin Protein Achieves High Affinity Binding to the Toxin Colchicine

Angewandte Chemie International Edition
64(50), e202515950, 2025

DOI ↗Publisher ↗

Machine Learning in Molecular Dynamics Simulations of Biomolecular Systems

Comprehensive Computational Chemistry
Vol. 3, pp. 475–492, 2024

Rescuing Off-Equilibrium Simulation Data through Dynamic Experimental Data with dynAMMo

Machine Learning: Science and Technology
4, 045050, 2023

DOI ↗Publisher ↗

Motional clustering in supra-τc conformational exchange influences NOE cross-relaxation rate

Journal of Magnetic Resonance
338, 107196, 2022

DOI ↗Publisher ↗

Theses

Data-Driven Modeling of Biomolecular Dynamics under Physical and Experimental Constraints

Chalmers University of Technology
Doctoral thesis, 2026

Unsupervised Learning of Biomolecular Dynamics with Multi-Modal Data

Chalmers University of Technology
Licentiate thesis, 2024