AVS 52nd International Symposium
    Biomaterial Interfaces Monday Sessions
       Session BI-MoP

Paper BI-MoP21
Prediction of Protein-Surface Interactions by All-Atom Molecular Dynamics Simulations Using Implicit Solvation

Monday, October 31, 2005, 5:00 pm, Room Exhibit Hall C&D

Session: Biomaterial Interfaces Poster Session
Presenter: Y. Sun, Clemson University
Authors: Y. Sun, Clemson University
F. Wang, Clemson University
R.A. Latour, Clemson University
Correspondent: Click to Email
The orientations and conformations of adsorbed proteins on biomaterials surfaces have profound influences on their bioactivities. However, it's very difficult to resolve the structures of adsorbed proteins experimentally. Empirical force field-based molecular simulation can be used to complement experimental studies to investigate protein adsorption behavior and potentially provide a more detailed understanding of molecular-level interactions. The predictive power of such an approach is largely dependent on the accuracy of the underlying force field used and the adequacy of sampling in the simulation. The objective of this study is thus to develop an empirical force field method with enhanced sampling to enable protein adsorption to be accurately simulated. We are evaluating the use of a generalized Born-based analytical continuum electrostatics (ACE) implicit solvent model for the purpose of enabling protein adsorption to be simulated with solvation effects treated implicitly. To further enhance sampling, replica-exchange molecular dynamics (REMD) is employed in combination with ACE to predict the equilibrium structures of a model protein (lysozyme) on alkanethiol self-assembled monolayer (SAM) surfaces. We have determined that ACE predicts reasonable energy-distance relationships of mid-chain peptide residues on functionalized SAM surfaces; it also predicts reasonable and stable trajectories of native lysozyme structure and significant surface-induced conformational changes of lysozyme on SAM surfaces. Qualitative agreement between model predictions and experimental observations has been established, and further studies for model validation are planned.