We demonstrate using nanohole arrays of mixed designs and a microwriting process based on dip-pen nanolithography to monitor multiple, different protein binding events simultaneously in real-time based on the intensity of Extraordinary Optical Transmission of nanohole arrays.
Nck utilizes the specificity of its individual SH3 domains to facilitate multiple interactions with different binding partners.
Differential expression of multiple isoforms with different binding specificities produces a "neural code" of downstream gene expression, in which phenotypes can be specified by either a single isoform or a combination of isoforms.
It should be noted that the use of multiple measurement antibodies with different binding epitopes and multiple control antibodies are both relatively straightforward.
If the duplicated gene has multiple splice variants with different binding interactions and knockouts of different splice sites between the two duplicates occur, then the result would be subfunctionalization of the duplicates with the ultimate retention of both.
We identified 143 high-confidence motifs, 69 medium-confidence motifs, and 37 low-confidence motifs; in some cases the same protein was associated with multiple motifs to represent different binding modes (e.g., monomeric vs. dimeric).
This is consistent with data comparing binding of multiple different SIMs to both SUMO1 and SUMO2, which suggests that negatively charged amino acids surrounding the hydrophobic core contribute to SUMO1 binding, but much less so to binding of SUMO2 [24].
The precise reason for this observed biphasic kinetics for fatty acid cannot be discerned at present, although, several plausible reasons for such kinetic behavior could involve the presence of multiple substrate binding sites with different binding affinities or binding of substrate in more than one orientation with different affinities [44], [45].
Accordingly, the advantage of using multiple restrictive pharmacophore models representing different binding modes for one target compared to using one quite general model covering most active ligands is a way to avoid a high number of false positive hits.
However, the simple trend of reduced GATA2 and increased GATA1 binding disguises multiple different behaviors.
