Abstract

Atomic force microscopy-based single-molecule force spectroscopy (SMFS) is a powerfultool for studying the mechanical properties, intermolecular and intramolecularinteractions, unfolding pathways, and energy landscapes of membrane proteins. Onelimiting factor for the large-scale applicability of SMFS on membrane proteinsis its low efficiency in data acquisition. We have developed a semi-automatedhigh-throughput SMFS (HT-SMFS) procedure for efficient data acquisition. In addition, wepresent a coarse filter to efficiently extract protein unfolding events from large datasets. The HT-SMFS procedure and the coarse filter were validated using theproton pump bacteriorhodopsin (BR) from Halobacterium salinarum and theL-arginine/agmatine antiporter AdiC from the bacterium Escherichia coli. To screen formolecular interactions between AdiC and its substrates, we recorded data sets in theabsence and in the presence of L-arginine, D-arginine, and agmatine. Altogether∼400 000 force–distance curves were recorded. Application of coarse filtering to this wealth of data yielded six datasets with ∼200 (AdiC) and ∼400 (BR) force–distance spectra in each. Importantly, the raw data for most of these data setswere acquired in one to two days, opening new perspectives for HT-SMFS applications.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.