Evaluating Molecular Mechanical Potentials for Helical Peptides and Proteins

Multiple variants of the AMBER all-atom force field were quantitatively evaluated with respect to their ability to accurately characterize helix-coil equilibria in explicit solvent simulations. Using a global distributed computing network, absolute conformational convergence was achieved for large ensembles of the capped A21 and Fs helical peptides. Further assessment of these AMBER variants was conducted via simulations of a flexible 164-residue five-helix-bundle protein, apolipophorin-III, on the 100 ns timescale. Of the contemporary potentials that had not been assessed previously, the AMBER-99SB force field showed significant helix-destabilizing tendencies, with beta bridge formation occurring in helical peptides, and unfolding of apolipophorin-III occurring on the tens of nanoseconds timescale. The AMBER-03 force field, while showing adequate helical propensities for both peptides and stabilizing apolipophorin-III, (i) predicts an unexpected decrease in helicity with ALA→ARG+ substitution, (ii) lacks experimentally observed 310 helical content, and (iii) deviates strongly from average apolipophorin-III NMR structural properties. As is observed for AMBER-99SB, AMBER-03 significantly overweighs the contribution of extended and polyproline backbone configurations to the conformational equilibrium. In contrast, the AMBER-99φ force field, which was previously shown to best reproduce experimental measurements of the helix-coil transition in model helical peptides, adequately stabilizes apolipophorin-III and yields both an average gyration radius and polar solvent exposed surface area that are in excellent agreement with the NMR ensemble

Free energy landscapes projected onto the Ramachandran map.

<p>These maps represent equilibrium sampling of the F_s peptide in the AMBER force fields evaluated, which have been ordered to match <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0010056#pone-0010056-g001" target="_blank">Figure 1</a> in (a) through (d). Each map consists of backbone torsional values binned in 3° intervals for all residues, and contours represent <i>k</i>T units at 305 K, the midpoint temperature of the helical peptide.</p

Ensemble averaged equilibrium structural properties for the F_s and A₂₁ peptides.

<p>RMSD (all-atom root-mean-square deviation), R_g (radius of gyration), N_helix (number of α-helical residues), N₃₁₀ (number of 3₁₀-helical residues), N_seg (number of helical segments), and N_cont (length of helical segments).</p

Ribbon views of the NMR model of apolipophorin-III.

<p>NMR model 1 of this 164-residue, five-helix-bundle protein (PDB 1LS4) was used to start our simulations in the noted AMBER force fields. Bright green and black unstructured regions represent turn and random coil regions, respectively. Helices are colored from blue (helix 1) to green (helix 5). The bottom view is rotated toward the reader to provide an axial view down the helical bundle central core region.</p

Structural sampling of apolipophorin-III per residue.

<p>Probabilities of sampling helix (H), turn (T), random coil (C), and polyproline type II (P) states when simulated using the AMBER-94, AMBER-99φ, AMBER-03, and AMBER-99SB force fields are shown. The schematic at the top represents the NMR model that was used to initiate all simulations, with turns shown in green and coil regions shown in pink to match the color coded state sampling plots below, which show probability ranges from 0.0 (black) to 1.0 (color).</p

Simulated ensemble statistics for the F_s and A₂₁ peptides.

<p>*Each force field was sampled using 1,000 trajectories starting in the fully helical state (H) and 1,000 trajectories starting in the random coil state (C) with no structured residues.</p><p>Max (longest individual trajectory), Total time (total ensemble simulation time), and >EQ (total equilibrium simulation time) are shown for each data set.</p

Mean SASA^* for apolipophorin-III simulations.

<p>*SASA (solvent-accessible surface area) is in Ų and was calculated using VEGA (<a href="http://nova.colombo58.unimi.it" target="_blank">http://nova.colombo58.unimi.it</a>).</p>‡<p>All 21 NMR models were used to generate these means and standard deviations.</p

Convergence of mean helical content for the (a) F_s and (b) A₂₁ ensembles.

<p>The AMBER-03 (red), AMBER-99SB (green), and AMBER-99φ (blue) potentials are shown, where helix> represents the number of helical residues averaged across all runs in a given ensemble of 1,000 simulations. Dotted and solid lines represent simulation ensembles initiated from the fully random coil and fully helical states, respectively. Other structural properties listed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0010056#pone-0010056-t002" target="_blank">Table 2</a> show similar convergence. Noise near the 100 ns regime is the result of a limited number of simulations reaching those times following the ensemble convergence that occurs prior to the 40 ns timepoint.</p

FcRn: From Molecular Interactions to Regulation of IgG Pharmacokinetics and Functions

The neonatal Fc receptor, FcRn, is related to MHC class I with respect to its structure and association with β2microglobulin (β2m). However, by contrast with MHC class I molecules, FcRn does not bind to peptides, but interacts with the Fc portion of IgGs and belongs to the Fc receptor family. Unlike the 'classical' Fc receptors, however, the primary functions of FcRn include salvage of IgG (and albumin) from lysosomal degradation through the recycling and transcytosis of IgG within cells. The characteristic feature of FcRn is pH-dependent binding to IgG, with relatively strong binding at acidic pH (&lt;6.5) and negligible binding at physiological pH (7.3-7.4). FcRn is expressed in many different cell types, and endothelial and hematopoietic cells are the dominant cell types involved in IgG homeostasis in vivo. FcRn also delivers IgG across cellular barriers to sites of pathogen encounter and consequently plays a role in protection against infections, in addition to regulating renal filtration and immune complex-mediated antigen presentation. Further, FcRn has been targeted to develop both IgGs with extended half-lives and FcRn inhibitors that can lower endogenous antibody levels. These approaches have implications for the development of longer lived therapeutics and the removal of pathogenic or deleterious antibodies.</p