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Understanding Molecular Recognition by Kinetic Network Models Constructed from Molecular Dynamics Simulations

  • Xuhui Huang
  • Gianni De Fabritiis
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 797)

Abstract

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.

Keywords

Molecular Recognition Paramagnetic Relaxation Enhancement Periplasmic Binding Protein Encounter Complex Markov State Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.Department of Chemistry, Division of Biomedical Engineering, Center of Systems Biology and Human Health, Institute for Advance StudyThe Hong Kong University of Science and TechnologyKowloonHong Kong
  2. 2.Computational Biophysics Laboratory (GRIB-IMIM), Universitat Pompeu FabraBarcelona Biomedical Research Park (PRBB)BarcelonaSpain

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