275741 Enhanced Sampling of Peptide Adsorption and 2D Self-Assembly with Parallel Tempering Metadynamics [Invited Talk]

Tuesday, October 30, 2012: 8:30 AM
411 (Convention Center )
Jim Pfaendtner and Michael Deighan, Chemical Engineering, University of Washington, Seattle, WA

Efficient sampling of the interaction of surfaces with peptides and proteins continues to be a pressing challenge.  Classical molecular dynamics (MD) simulations are frequently insufficient for this task as these systems can become trapped in minima that prevent equilibration of relevant probability distributions.  Monte Carlo also suffers from low efficiency due to well-known challenges with explicit solvation.  In this talk we will present a strategy for efficient simulation of peptide adsorption and 2D self-assembly on surfaces using a new algorithm:  parallel tempering metadynamics in the well-tempered ensemble (PTMetaD-WTE).   This algorithm allows for biasing of a few relevant collective variables (CVs) while using the parallel tempering scheme (PT) to achieve a random walk through temperature space and overcome enthalpic barriers due to “hidden CVs”.  Importantly, the algorithm helps overcome well-known scaling challenges that have plagued PT in explicitly solvated systems by coupling PTMetaD with the well-tempered ensemble (WTE) of Bonomi and Parrinello. 

First we will describe the behavior of model systems based on the alpha and beta LK peptides interacting with a number of different model surfaces including self-assembled monolayers (SAMs) [methyl terminated, carboxyl terminated] and graphene.  The adsorption behavior is compared to experimental measurements from sum frequency generation (SFG) and surface plasmon resonance (SPR). Following this, we will show preliminary results from simulation of the self-assembly of a monolayer of LK peptides in an explicitly solvated environment.


Extended Abstract: File Not Uploaded
See more of this Session: Computational Studies of Self-Assembly I
See more of this Group/Topical: Engineering Sciences and Fundamentals