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Comprehensive Peptide Ion Structure Studies Using Ion Mobility Techniques: Part 1. An Advanced Protocol for Molecular Dynamics Simulations and Collision Cross-Section Calculation.

Samaneh Ghassabi KondalajiMahdiar KhakinejadAmirmahdi TafreshianStephen J Valentine
Published in: Journal of the American Society for Mass Spectrometry (2017)
Collision cross-section (CCS) measurements with a linear drift tube have been utilized to study the gas-phase conformers of a model peptide (acetyl-PAAAAKAAAAKAAAAKAAAAK). Extensive molecular dynamics (MD) simulations have been conducted to derive an advanced protocol for the generation of a comprehensive pool of in-silico structures; both higher energy and more thermodynamically stable structures are included to provide an unbiased sampling of conformational space. MD simulations at 300 K are applied to the in-silico structures to more accurately describe the gas-phase transport properties of the ion conformers including their dynamics. Different methods used previously for trajectory method (TM) CCS calculation employing the Mobcal software [1] are evaluated. A new method for accurate CCS calculation is proposed based on clustering and data mining techniques. CCS values are calculated for all in-silico structures, and those with matching CCS values are chosen as candidate structures. With this approach, more than 300 candidate structures with significant structural variation are produced; although no final gas-phase structure is proposed here, in a second installment of this work, gas-phase hydrogen deuterium exchange data will be utilized as a second criterion to select among these structures as well as to propose relative populations for these ion conformers. Here the need to increase conformer diversity and accurate CCS calculation is demonstrated and the advanced methods are discussed. Graphical Abstract ᅟ.
Keyphrases
  • molecular dynamics
  • high resolution
  • molecular dynamics simulations
  • molecular docking
  • density functional theory
  • monte carlo
  • electronic health record
  • big data
  • machine learning
  • single cell