Statistical Analysis of Ion Mobility Spectrometry. II. Adaptively Biased Methods and Shape Correlations

Abstract

Following a recent effort [J. Am. Soc. Mass Spectrom. 23, 386-396 (2012)], we continue to explore computational methodologies for generating molecular conformations to support collisional cross sections suggested by ion mobility measurements. Here, adaptively biased molecular dynamics (ABMD) simulations are used to sample the configuration space and to achieve flat-histogram sampling along the reaction coordinates of the first two moments of the gyration tensor. The method is tested and compared with replica-exchange simulations on triplyprotonated bradykinin and on a larger 25-residue peptide. It is found to have a much higher efficiency for producing large sets of conformations in a broad range of diffusion cross-sections, whereas it does not compete with conventional replica-exchange molecular dynamics in locating the lowest-energy structure. Nevertheless, the broad sampling obtained from the ABMD method allows to quantitatively correlate the diffusion cross-section Ω with other geometric order parameters that have simpler interpretation. The strong correlations found between the diffusion cross-section and the radius of gyration, the surface area and the volume of the convex hull suggest an optimal template for accurately mimicking the variations of Ω in a broad range of conformations, using only geometrical information and doing so at a very moderate computational cost. The existence of such a correlation is confirmed on the much larger protein α-lactalbumin.

Linking molecular models with ion mobility experiments. Illustration with a rigid nucleic acid structure

“…Several enhanced sampling techniques allow the species to overcome energetic barriers and explore other conformational 5À on the Synapt G1 and (C) Reconstructed collision cross section distributions for the ion [(dTG 4 T) basins, for example simulated annealing molecular dynamics, [57][58][59][60] replica-exchange molecular dynamics [61][62][63] and adaptively biased molecular dynamics. [64,65] On the other hand, when the molecular system taken into account is too big, as for instance large multiprotein complexes (>500 kDa), all the aforementioned atomistic methods are still too computationally expensive, but some qualitative models can be built instead, such as (bead-type) coarse grained models. [37,[66][67][68][69] Force fields A possible pitfall intrinsic in classical MD simulations in gas phase is related to the use of force fields (FFs) that are presently parameterized based on high-level quantum calculations, but eventually tested and tuned in aqueous phase (with either explicit or implicit water models).…”

Contribution of the empirical dispersion correction on the conformation of short alanine peptides obtained by gas-phase QM calculations

“…3,4 However, common protein force fields have been validated principally in terms of their ability to reproduce solution phase properties of proteins. To assess the accuracy of existing protein force fields for predicting the conformational properties of peptides in the gas-phase, it is first necessary to establish a gas-phase structural and energetic reference set for polypeptides.…”

Adding a new separation dimension to MS and LC–MS: What is the utility of ion mobility spectrometry?

“…To disclose the conformation and shape adopted by the ions in the gas-phase, the experimentally derived CCS needs to be compared with computationally derived CCS values obtained from atomistic models. Nowadays, this approach is the goldstandard if using IM-MS as analytical technique for "conformation analysis" [2,4,5,[31][32][33][34][35][36][37][38][39][40][41]].…”