239 citations · 574 across the 9 of their papers we have counts for
4 papers · 1 filter
Navigating protein landscapes with a machine-learned transferable coarse-grained model
Nicholas E. Charron, Felix Musil, Andrea Guljas +18
The most popular and universally predictive protein simulation models employ all-atom molecular dynamics (MD), but they come at extreme computational cost. The development of a uni…
Machine Learning Small Molecule Properties in Drug Discovery
Nikolai Schapin, Maciej Majewski, Alejandro Varela +2
Machine learning (ML) is a promising approach for predicting small molecule properties in drug discovery. Here, we provide a comprehensive overview of various ML methods introduced…
Top-down machine learning of coarse-grained protein force-fields
Carles Navarro, Maciej Majewski, Gianni de Fabritiis
Developing accurate and efficient coarse-grained representations of proteins is crucial for understanding their folding, function, and interactions over extended timescales. Our me…
Machine Learning Coarse-Grained Potentials of Protein Thermodynamics
Maciej Majewski, Adrià Pérez, Philipp Thölke +7
A generalized understanding of protein dynamics is an unsolved scientific problem, the solution of which is critical to the interpretation of the structure-function relationships t…