Understanding Molecular Recognition by Kinetic Network Models Constructed from Molecular Dynamics Simulations
Molecular recognition, the process by which biological macromolecules selectively bind, plays an important role in many biological processes. Molecular simulations hold great potential to reveal the chemical details of molecular recognition and to complement experiments. However, it is challenging to reconstruct the binding process for two-body systems like protein-ligand complexes because the system’s dynamics occurs on significantly different timescales due to several physical processes involved, such as diffusion, local interactions and conformational changes. In this chapter, we review some recent progress on applying Markov state models (MSMs) to two-body systems. Emphasis is placed on the value of projecting dynamics onto collective reaction coordinates and treating the ligand dynamics with different resolution models depending on the proximity of the protein and ligand. We also discuss some future directions on constructing MSMs to investigate molecular recognition processes.
KeywordsMolecular Recognition Paramagnetic Relaxation Enhancement Periplasmic Binding Protein Encounter Complex Markov State Model
- 15.Huang X, Yao Y, Bowman GR, Sun J, Guibas LJ, Carlsson G, Pande VS (2010) Constructing multi-resolution markov state models (msms) to elucidate RNA hairpin folding mechanisms. Pac Symp Biocomput, 228–239 Google Scholar
- 16.Voelz VA, Bowman GR, Beauchamp K, Pande VS. Molecular simulation of ab initio protein folding for a millisecond folder NTL9(1-39). J Am Chem Soc 132(5):1526–1528 Google Scholar