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SAMFF - A Refined Empirical Force Field to Model
Protein-SAM Interactions Based on AMBER14
and GAFF
Understanding protein interaction
with material surfaces such as self-assembled monolayers (SAM) is
important for the development of nanotechnological devices. The
structures and dynamics of proteins can be studied via molecular
dynamics (MD) if the protein-surface interactions can be accurately
modeled. Based on AMBER14 and GAFF, we systematically tuned the
Lennard-Jones parameters of selected amino acid sidechains and the
functional group of SAM with repeated metadynamics and umbrella
sampling simulations. The final parameter set has yielded a significant
improvement in the free energy values with R = 0.83 and MSE = 0.65
kcal/mol. We applied the refined force field to predict the adsorption
orientation of lysozyme on CH3-SAM.
About SAMFF
This is our first attempt to improve force field parameters for modeling protein-SAM interactions. SAMs, the self-asssembled monolayers, are important coating materials used in nanotechnological devices such as biosensors, nanoparticles, and implanted materials. They are cruical to maintain the proper function of devices by proper attaching and orienting desired molecules on the surface or prevent non-wanted substances to foul the surface. To aid rational design of SAM surfaces, we need to understand how molecules interact with them in molecular level of detail. Molecular Dynamics (MD) simulation is a powerful tool for this purpose. However, an accurate picture from simulations cannot be obtained without an accurate force field. We previously tested a number of protein and lipid force fields and found that GAFF are the best in modeling SAMs.Therefore, taking GAFF for CH3-SAM and AMBER14 for proteins (a natural combination from the AMBER family), we have attempted to refine the interaction parameters between the SAM and protein atoms to reproduce the experimental free energies of adsorption of 11 model peptides. By series of systematic adjustment with extensive free energy simulations, we have achieved a high pearson correlation of 0.83 and low mean squared error of 0.32 kcal/mol in free energy prediction.
On the basis of our results, we believe that this force field, SAMFF, will generate more accurate molecular structures and dynamics in the protein-SAM simulations.
Availability
sam19.zip - The force field files in GROMACS format is freely available at SourceForge. This version includes the C12 SAM ligand with methyl (CH3) functional group. Sample MD system setups:
- Hydrophobic C12-SAM with a water slab (Lysozyme-NAG3_DDT_MD.zip)
- Hydrophobic C12-SAM with a Lysozyme-NAG3 complex (DDT_water_MD.zip)
Citation
Please cite our paper(s) if you have used SAMFF.Main paper
Pratiti Bhadra and Shirley W. I. Siu*
A Refined Empirical Force Field to Model Protein-SAM Interactions Based on AMBER14 and GAFF
(2019, submitted)
Force field comparison paper
Pratiti Bhadra and Shirley W. I. Siu*
Comparison of Biomolecular Force Fields for Alkanethiol Self-Assembled Monolayer Simulations.
Journal of Physical Chemistry C, 121, 47, 26340-26349, 2017
Pratiti Bhadra and Shirley W. I. Siu*
A Refined Empirical Force Field to Model Protein-SAM Interactions Based on AMBER14 and GAFF
(2019, submitted)
Force field comparison paper
Pratiti Bhadra and Shirley W. I. Siu*
Comparison of Biomolecular Force Fields for Alkanethiol Self-Assembled Monolayer Simulations.
Journal of Physical Chemistry C, 121, 47, 26340-26349, 2017
Contact Us
| Developer: | Pratiti Bhadra | pratiti.bhadra_[at]_gmail_[dot]_com |
| Project P.I.: | Shirley W. I. Siu | shirley_siu_[at]_um_[dot]_mo_[dot]_edu |