Paper Citing NAMD - Abstract
Damas, Joao M.; Filipe, Luis C. S.; Campos, Sara R. R.; Lousa, Diana; Victor, Bruno L.; Baptista, Antonio M.; Soares, Claudio M.
Predicting the Thermodynamics and Kinetics of Helix Formation in a Cyclic Peptide Model
JOURNAL OF CHEMICAL THEORY AND COMPUTATION, 9:5148-5157, NOV 2013
The peptide Ac-(cyclo-2,6)-R[KAAAD]-NH2 (cyc-RKAAAD) is a short cyclic peptide known to adopt a remarkably stable single turn alpha-helix in water. Due to its simplicity and the availability of thermodynamic and kinetic experimental data, cyc-RKAAAD poses as an ideal model for evaluating the aptness of current molecular dynamics (MD) simulation methodologies to accurately sample conformations that reproduce experimentally observed properties. In this work, we extensively sample the conformational space of cyc-RKAAAD using microsecond-timescale MD simulations. We characterize the peptide conformational preferences in terms of secondary structure propensities and, using Cartesian-coordinate principal component analysis (cPCA), construct its free energy landscape, thus obtaining a detailed weighted discrimination between the helical and nonhelical subensembles. The cPCA state discrimination, together with a Markov model built from it, allowed us to estimate the free energy of unfolding (-0.57 kJ/mol) and the relaxation time (similar to 0.435 mu s) at 298.15 K, which are in excellent agreement with the experimentally reported values (-0.22 kJ/mol and 0.42 mu s, Serrano, A. L.; Tucker, M. J.; Gai, F. J. Phys. Chem. B, 2011, 115, 7472-7478.). Additionally, we present simulations conducted using two enhanced sampling methods: replica-exchange molecular dynamics (REMD) and bias-exchange metadynamics (BE-MetaD). We compare the free energy landscape obtained by these two methods with the results from MD simulations and discuss the sampling and computational gains achieved. Overall, the results obtained attest to the suitability of modern simulation methods to explore the conformational behavior of peptide systems with a high level of realism.
