The accuracy of the CHARMM22/CMAP and AMBER ff99SB force fields for modelling the antimicrobial peptide cecropin P1

Abstract

Secondary structures of antimicrobial peptides (AMPs) play an important role in their activity. The AMP cecropin P1, like most other anti-microbial peptides, is known to form a helix at the interface of bacterial cell membranes. This structure is fundamental to its activity and its ability to destroy the membrane. In contrast, as reported in experimental measurements, this peptide unfolds in bulk water. We analysed this behaviour using two different force fields, CHARMM22/CMAP and AMBER ff99SB. Although these two force fields are commonly used in molecular dynamics (MD) and have been extensively validated, we observed two sharply different results. A sodium dodecyl sulphate (SDS) micelle was used to model the bacterial membrane using MD simulations. CHARMM22 resulted in a peptide that stays mostly folded in both environments (bulk water and SDS), while AMBER correctly predicted the unfolding in bulk water and produced results that closely match the available experimental data. We further computed the free energy of folding and unfolding, using the adaptive biasing force method, to get a complete picture of the energy barriers and the different metastable states. To get further insights into the interaction of the peptide with its environment, we computed the average number of hydrogen bonds between different components versus the folding reaction coordinate.

Keywords::

• molecular dynamics simulation
• free energy
• adaptive biasing force method
• secondary structure
• force field

Acknowledgements

The authors acknowledge the following award for providing computing resources that have contributed to the research results reported within this paper: MRI-R2: Acquisition of a Hybrid CPU/GPU and Visualization Cluster for Multidisciplinary Studies in Transport Physics with Uncertainty Quantification, http://www.nsf.gov/awardsearch/showAward.do?AwardNumber = 0960306. This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).

Notes

^1. Email: [email protected]

^2.http://meta.bioinfo.pl

^3. Secondary structure prediction method servers: psipred. Sequence-only method servers: ESyPred3D, FFAS03, GRDB, PFAM-Basic and PFAM-MetaBasic; threading method servers: 3D-PSSM, FUGUE, INUB, mGenThreader, Sam-T02 and samt06.