Molecular dynamics (MD) simulation is a technique that aids in the understanding of fundamental processes in biology and chemistry, and has important technological applications in pharmacy, biotechnology, and nanotechnology. Many complex molecular processes have cascades of timescales spanning the range from 10-15 s to 1 s, often with no pronounced gap that would permit efficient coarse-grained time integration.
In many applications, the slowest timescales and the associated structural rearrangements are the ones of interest. In this project, we study the challenging process of induced folding of peptides. Such states may be found when peptide ligands bind to proteins and when membrane-associated proteins anchor into the membrane. Here, association and conformational changes occur on physical timescales of nano- to milliseconds, while dissociation events may require seconds or longer.
The long-term aims of this project are to develop efficient modeling and simulation methods for the dominant (slow) timescales of complex biomolecular simulation systems, and apply them to folding-binding problems in biomolecules.
In contrast to previous conformation-dynamics approaches such as Markov state modeling that are driven by a set-based approach, we attempt a paradigm shift and will focus on developing methods to approximate and sample individual timescales and eigenfunctions one by one.