Pharmacophore-driven antibody discovery on the yeast surface
Huang, M.; Williams, S. J.; Trivedi, V. D.; Nair, N. U.; Van Deventer, J. A.
Show abstract
Protein-small molecule hybrids are structures capable of combining the inhibitory properties of small molecules and the specificities of binding proteins. However, discovery of such synergistic conjugates is a substantial engineering challenge. Here, we describe pharmacophore-driven antibody discovery as a high throughput approach to hybrid discovery. In this approach, we use a yeast display antibody library containing reactive noncanonical amino acids (ncAAs) and further diversify it by conjugating the library to four sulfonamide pharmacophores. Yeast display binding screens with each of the resulting billion-member hybrid collections against bovine carbonic anhydrase (bCA) yielded diverse collections of hybrids. Individual hybrids exhibited double digit nanomolar binding affinities, and frequently exhibited inhibitory properties in solution, despite the fact that the screens were based solely on binding phenotypes. Deep sequencing of sorted populations revealed that enrichments were strongly pharmacophore-dependent. In particular, screens with a potent pharmacophore led to collections of hybrids varying substantially in pharmacophore attachment point and antibody sequence features, while screens with moderate or weak pharmacophores led to collections with much narrower sets of enriched attachment points and antibody sequence features. Identification of the most frequently isolated CDR-H3 sequences and clustering CDR-H3 sequences by similarity within enriched populations provided further evidence for pharmacophore-dependent sorting outcomes. Experimental binding assays in which the pharmacophore warhead used during screening was replaced by another warhead indicated that isolated clones can tolerate alternative pharmacophores, but tend to prefer the warhead used during screening. Overall, these efforts demonstrate the utility of introducing pharmacophores into antibody libraries along with several lines of evidence that screening outcomes are pharmacophore-driven. These findings advance our understanding of hybrid discovery and highlight opportunities to pursue hybrids as research tools and potential therapeutic leads. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=68 SRC="FIGDIR/small/682880v1_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@11c2a65org.highwire.dtl.DTLVardef@237055org.highwire.dtl.DTLVardef@a3fb4borg.highwire.dtl.DTLVardef@1c71700_HPS_FORMAT_FIGEXP M_FIG C_FIG
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Characterization of a nanobody-epitope tag interaction and its application for receptor engineering 96%
- Systematic profiling of peptide substrate specificity in N-terminal processing by methionine aminopeptidase using mRNA display and an unnatural methionine analogue 95%
- A Novel Regioselective Approach to Cyclize Phage-Displayed Peptides in Combination with Epitope-Directed Selection to Identify a Potent Neutralizing Macrocyclic Peptide for SARS-CoV-2 94%
Similar papers in this journal
Similar papers in this journal
Similar papers in this journal
- In vitro selection of cyclized, glycosylated peptide antigens that tightly bind HIV high mannose patch antibodies 95%
- A High-Throughput Screen Reveals the Structure-Activity Relationship of the Antimicrobial Lasso Peptide Ubonodin 94%
- Enhanced Sequence-Activity Mapping and Evolution of Artificial Metalloenzymes by Active Learning 93%
Similar papers in this journal
- Engineered protein-small molecule conjugates empower selective enzyme inhibition 97%
- Tracking the PROTAC degradation pathway in living cells highlights the importance of ternary complex measurement for PROTAC optimization 93%
- Structure-aided development of small molecule inhibitors of ENPP1, the extracellular phosphodiesterase of the immunotransmitter cGAMP 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.