ABSTRACT
We study the differences in folding stability of ß-hairpin peptides, including GB1 hairpin and a point mutant GB1 K10G, as well as tryptophan zippers (TrpZips): TrpZip1, TrpZip2, TrpZip3-1, and TrpZip4. By performing replica-exchange molecular dynamics simulations with Amber03* force field (a modified version of Amber ff03) in explicit solvent, we observe ab initio folding of all the peptides except TrpZip3-1, which is experimentally known to be the least stable among the peptides studied here. By calculating the free energies of unfolding of the peptides at room temperature and folding midpoint temperatures for thermal unfolding of peptides, we find that TrpZip4 and GB1 K10G peptides are the most stable ß-hairpins followed by TrpZip1, GB1, and TrpZip2 in the given order. Hence, the proposed K10G mutation of GB1 peptide results in enhanced stability compared to wild-type GB1. An important goal of our study is to test whether simulations with Amber 03* model can reproduce experimentally predicted folding stability differences between these peptides. While the stabilities of GB1 and TrpZip1 yield close agreement with experiment, TrpZip2 is found to be less stable than predicted by experiment. However, as heterogenous folding of TrpZip2 may yield divergent thermodynamic parameters by different spectroscopic methods, mismatching of results with previous experimental values are not conclusive of model shortcomings. For most of the cases, molecular simulations with Amber03* can successfully reproduce experimentally known differences between the mutated peptides, further highlighting the predictive capabilities of current state-of-the-art all-atom protein force fields.
Subject(s)
Bacterial Proteins/chemistry , Molecular Dynamics Simulation , Peptides/chemistry , Proteins/chemistry , Tryptophan/chemistry , Amino Acid Sequence , Amino Acid Substitution , Hydrogen Bonding , Molecular Sequence Data , Protein Folding , Protein Stability , Protein Structure, Secondary , Protein Structure, Tertiary , Solvents/chemistry , Streptococcus/chemistry , Temperature , ThermodynamicsABSTRACT
Adhesion flow assays are commonly employed to characterize the kinetics and force-dependence of receptor-ligand interactions. As transient cellular adhesion events are often mediated by a small number of receptor-ligand complexes (tether bonds) their durations are highly variable, which in turn presents obstacles to standard methods of analysis. In this paper, we employ the stochastic approach to chemical kinetics to construct the pause time distribution. Using this distribution, we develop a robust maximum likelihood (ML) approach to the robust estimation of rate constants associated with receptor-mediated transient adhesion and their confidence intervals. We then formulate robust estimators of the parameters of models for the force-dependence of the off-rate. Lastly, we develop a robust method of elucidation of the force-dependence of the off-rate using Akaike's information criterion (AIC). Our findings conclusively demonstrate that ML estimators of adhesion kinetics are substantial improvements over more conventional approaches, and when combined with Fisher information, they may be used to objectively and reproducibly distinguish the kinetics of different receptor-ligand complexes. Software for the implementation of these methods with experimental data is publicly available as for download at http://www.laurenzi.net.
