Predicting NMR Relaxation Using a First-Principles Brownian Dynamics Approach
Mirco Zerbetto, Sergio Rampino, Antonino Polimeno
TL;DR
This paper introduces a new method using Brownian dynamics to predict NMR relaxation, combining efficiency with atomistic detail for studying slow molecular motions.
Contribution
A first-principles Brownian dynamics approach is proposed for NMR relaxation prediction, merging stochastic modeling with atomistic simulations.
Findings
The method enables long-time dynamics analysis of semiflexible molecules with reduced computational cost.
GPU acceleration and natural internal coordinates enhance the efficiency and accuracy of the simulations.
The approach provides a rigorous framework for interpreting NMR relaxation data from molecular dynamics.
Abstract
Interpreting time-resolved magnetic resonance experiments, sensitive to slow motions in molecules, requires access to at least the microsecond time scale. Today, all-atom classical molecular dynamics simulations allow exploration of such a long time scale; however, this comes at the price of a considerable computational effort. Stochastic models, based on a hierarchical distinction of the coordinates into relevant (treated explicitly) and irrelevant (treated as generators of fluctuation and dissipation), offer a relatively low-cost solution to this problem. In the past, ad hoc but essentially phenomenological approaches based on Langevin or Fokker–Planck equations have been employed, which are good in catching relevant differences among (even complex) molecular systems, but lack of predictive power since a map between such parameters and atomistic details is not always clear or defined.…
Genes, proteins, chemicals, diseases, species, mutations and cell lines named across the full text — each resolved to its canonical identifier and authoritative record.
Click any figure to enlarge with its caption.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
Figure 11
Figure 12
Figure 13
Figure 14
Figure 15
Figure 16
Figure 17
Figure 18
Figure 19
Figure 20
Figure 21
Figure 22
Figure 23
Figure 24
Figure 25
Figure 26
Figure 27
Figure 28
Figure 29
Figure 30
Figure 31
Figure 32
Figure 33
Figure 34
Figure 35
Figure 36
Figure 37
Figure 38
Figure 39
Figure 40
Figure 41Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced NMR Techniques and Applications · Protein Structure and Dynamics · NMR spectroscopy and applications