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A NOVEL CLUSTERING ALGORITHM TO EVALUATE THE COMPLETE CANDIDATE STRUCTURE POPULATION

The challenge for structure IM-MS is to design gas-phase experiments that critically evaluate the structural assignments. The research described here is aimed at bridging the gap between the experimental domain of IM-MS and the MD simulations and bioinformatic tools that are essential to interpretation of the data. In this study, we apply a novel clustering algorithm to a model peptide to identify groups of structural elements from a large pool of diverse candidate structures. The clustering algorithm groups the candidate structures based on the similarity of backbone structure and provides estimates of the uncertainty of the cluster membership and the degree of purity of the cluster.

BIOPHY1

 

FREE ENERGY-BASED CONFORMATIONAL ANALYSIS OF ION MOBILITY DATA

The current method for ion structure assignment relies on the comparison of the lowest energy structure from thousands of annealing trial structures with experimental determined collision cross-section. The problem with this method is that single conformation is often selected as the candidate. However, multiple equilibrium conformations might be presented in IM-MS experiment due to the fact the arrival time distributions are often broader than expected for a single conformer. With more sophisticated cluster analysis methods, multiple probable conformation can be found under the given experimental conditions, however, the relative stability of those candidate structure is missing. In collaboration with Dr Gao (Department of chemistry, TAMU), an alternative approach of molecular dynamics is applied for IM-MS structures assignment. For these studies, molecular dynamics simulations are performed with enhanced sampling by utilizing a generalized (non-Boltzmann) distribution functions at multiple temperature.This generalized distribution function, after reweighted correctly, can lead to the desired thermodynamic information.

FREE ENERGY

 

 

 

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