Back

Coordination of Anle138b to Silver Results in Selective Reduction of a C-terminal truncated Alpha-synuclein Protein and Increased Aggregate Size

Rue, K. L.; Herrera, S.; Shi, Z.-C.; Chakraborty, I.; Tachiki, J.; Ballesteros, J.; Andersen, J. K.; Lithgow, G. J.; Al Isawi, W. A.; Mezei, G.; Schmidt, M. Y.; Raptis, R. G.

2025-10-03 biochemistry
10.1101/2025.10.01.679869 bioRxiv
Show abstract

Parkinsons disease (PD) is a prevalent age-related neurodegenerative syndrome, partially thought to be caused by a decrease in alpha-synuclein proteostasis. Anle138b = 5-(1,3-benzodioxol-5-yl)-3-(3-bromophenyl)-1H-pyrazole (HL), is undergoing clinical trials as a promising mitigator of alpha-synuclein aggregation. Because complexation to metals is known to modulate the activity of several drugs, we have prepared and characterized: H2L(ClO4), [CuI({micro}-L)]3, and [AgI({micro}-L)]3. To better understand the bioviability of these compounds, we monitored their effects in a cell culture model of alpha-synuclein protein aggregation using human alpha-synuclein pre-formed fibrils (PFFs). Using two different anti-alpha-synuclein antibodies, our data suggests that [AgI({micro}-L)]3 decreases a C-terminal truncated protein that is approximately 12.4 kDa, as well as increases the size and alters the shape of PFF-induced aggregates. This indicates that [AgI({micro}-L)]3 impacts aggregation in a manner different from HL and may serve as a novel tool for studying C-terminal truncation related aggregation chemistry. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=101 SRC="FIGDIR/small/679869v1_ufig1.gif" ALT="Figure 1"> View larger version (18K): org.highwire.dtl.DTLVardef@4bbda5org.highwire.dtl.DTLVardef@8fc0b7org.highwire.dtl.DTLVardef@1b561f5org.highwire.dtl.DTLVardef@1322902_HPS_FORMAT_FIGEXP M_FIG C_FIG

Published in ChemMedChem (predicted rank #8) · training set

Matching journals

The top 11 journals account for 50% of the predicted probability mass.

50% of probability mass above

"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.