Protein shape sampled by ion mobility mass spectrometry consistently improves protein structure prediction.

ABSTRACT: Ion mobility (IM) mass spectrometry provides structural information about protein shape and size in the form of an orientationally-averaged collision cross-section (CCS_IM). While IM data have been used with various computational methods, they have not yet been utilized to predict monomeric protein structure from sequence. Here, we show that IM data can significantly improve protein structure determination using the modelling suite Rosetta. We develop the Rosetta Projection Approximation using Rough Circular Shapes (PARCS) algorithm that allows for fast and accurate prediction of CCS_IM from structure. Following successful testing of the PARCS algorithm, we use an integrative modelling approach to utilize IM data for protein structure prediction. Additionally, we propos

SUBMITTER: Turzo SMBA 

PROVIDER: S-EPMC9334640 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature