<?xml version="1.0" encoding="UTF-8"?><rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcq="http://purl.org/dc/terms/"><records count="1" morepages="false" start="1" end="1"><record rownumber="1"><dc:product_type>Journal Article</dc:product_type><dc:title>Binding methylarginines and methyllysines as free amino acids: a comparative study of multiple host classes</dc:title><dc:creator>Warmerdam, Zoey; Kamba, Bianca E.; Le, My-Hue; Schrader, Thomas; Isaacs, Lyle; Bayer, Peter; Hof, Fraser</dc:creator><dc:corporate_author/><dc:editor>null</dc:editor><dc:description>Methylated free amino acids are an important class of
targets for host-guest chemistry that have recognition properties
distinct from those of methylated peptides and proteins. We present
comparative binding studies for three different host classes that are
each studied with multiple methylated arginines and lysines to
determine fundamental structure-function relationships. The hosts
studied are all anionic and include three calixarenes, two acyclic
cucurbiturils, and two other cleft-like hosts, a clip and a tweezer. We
determined the binding association constants for a panel of
methylated amino acids using indicator displacement assays. The
acyclic cucurbiturils display stronger binding to the methylated amino
acids, and some unique patterns of selectivity. The two other cleft-like
hosts follow two different trends, shallow host (clip) following similar
trends to the calixarenes, and the other more closed host (tweezer)
binding certain less-methylated amino acids stronger than their
methylated counterparts. Molecular modeling sheds some light on the
different preferences of different hosts. The results identify hosts with
new selectivities and with affinities in a range that could be useful for
biomedical applications. The overall selectivity patterns are explained
by a common framework that considers the geometry, depth of
binding pockets, and functional group participation across all host
classes.</dc:description><dc:publisher/><dc:date>2022-01-01</dc:date><dc:nsf_par_id>10302206</dc:nsf_par_id><dc:journal_name>ChemBioChem</dc:journal_name><dc:journal_volume/><dc:journal_issue/><dc:page_range_or_elocation/><dc:issn>1439-4227</dc:issn><dc:isbn/><dc:doi>https://doi.org/10.1002/cbic.202100502</dc:doi><dcq:identifierAwardId>1807486</dcq:identifierAwardId><dc:subject/><dc:version_number/><dc:location/><dc:rights/><dc:institution/><dc:sponsoring_org>National Science Foundation</dc:sponsoring_org></record></records></rdf:RDF>