9 citations · 30 across the 9 of their papers we have counts for
10 papers
Looking Under the Streetlight: Evaluation in Generative Molecular Dynamics
Simon Olsson, Frank Noé, Grant M. Rotskoff +1
This position paper argues that the generative molecular dynamics (GenMD) community is not properly evaluating its progress: current evaluations let a model match what is reported…
Integrative modelling of biomolecular dynamics
Daria Gusew, Carl G. Henning Hansen, Kresten Lindorff-Larsen
Much of our mechanistic understanding of the functions of biological macromolecules is based on static structural experiments, which can be modelled either as single structures or…
Computational design of intrinsically disordered proteins
Giulio Tesei, Francesco Pesce, Kresten Lindorff-Larsen
Protein design has the potential to revolutionize biotechnology and medicine. While most efforts have focused on proteins with well-defined structures, increased recognition of the…
How to use quantum computers for biomolecular free energies
Jakob Günther, Thomas Weymuth, Moritz Bensberg +18
Free energy calculations are at the heart of physics-based analyses of biochemical processes. They allow us to quantify molecular recognition mechanisms, which determine a wide ran…
Zero-shot protein stability prediction by inverse folding models: a free energy interpretation
Jes Frellsen, Maher M. Kassem, Tone Bengtsen +4
Inverse folding models have proven to be highly effective zero-shot predictors of protein stability. Despite this success, the link between the amino acid preferences of an inverse…
Software package for simulations using the coarse-grained CALVADOS model
Sören von Bülow, Ikki Yasuda, Fan Cao +6
We present the CALVADOS package for performing simulations of biomolecules using OpenMM and the coarse-grained CALVADOS model. The package makes it easy to run simulations using th…
Towards a Unified Framework for Determining Conformational Ensembles of Disordered Proteins
Hamidreza Ghafouri, Pavel Kadeřávek, Ana M Melo +23
Disordered proteins play essential roles in myriad cellular processes, yet their structural characterization remains a major challenge due to their dynamic and heterogeneous nature…
Machine Learning Enhanced Calculation of Quantum-Classical Binding Free Energies
Moritz Bensberg, Marco Eckhoff, F. Emil Thomasen +10
Binding free energies are a key element in understanding and predicting the strength of protein--drug interactions. While classical free energy simulations yield good results for m…
Hierarchical quantum embedding by machine learning for large molecular assemblies
Moritz Bensberg, Marco Eckhoff, Raphael T. Husistein +9
We present a quantum-in-quantum embedding strategy coupled to machine learning potentials to improve on the accuracy of quantum-classical hybrid models for the description of large…
Structure-Based Experimental Datasets for Benchmarking Protein Simulation Force Fields
Chapin E. Cavender, David A. Case, Julian C. -H. Chen +11
This review article provides an overview of structurally oriented experimental datasets that can be used to benchmark protein force fields, focusing on data generated by nuclear ma…