Biology subjects

Reker, D.

Publications and source records attributed to Reker, D..

3 recordsLinked to original sources

bioRxiv2026

Identification of 4,5,6,7-Tetrabromo-1H-benzotriazole (TBB) as a Small Molecule MESH1 Inhibitor that Suppresses Ferroptosis

Ferroptosis is a regulated form of cell death driven by iron-dependent lipid peroxidation and contributes to diverse pathologies including ischemia-reperfusion injury and neurodegenerative disorders. Current ferroptosis inhibitors largely function as nonspecific radical-trapping antioxidants, limiting their clinical utility. We previously identified MESH1 as a key regulator of ferroptosis through its NADPH phosphatase activity. Here, we identify 4,5,6,7-tetrabromo-1H-benzotriazole (TBB) as a small molecule inhibitor of MESH1 with an IC50 value of 4.7 {+/-} 0.3 {micro}M. X-ray crystallography revealed the molecular determinants of TBB recognition which are corroborated through structure-activity relationships of TBB analogs. TBB protected multiple cell lines against ferroptosis in vitro, and this effect was mitigated by MESH1 knockdown, consistent with on-target activity. Furthermore, TBB reduced neuronal death in an ex vivo brain slice model of Alzheimers disease. Collectively, these findings establish TBB as a bona fide small-molecule MESH1 inhibitor that suppresses ferroptosis and establishes MESH1 as a promising therapeutic target. Graphical AbstractDepicting mechanism of TBB suppressing ferroptosis through the inhibition of MESH1. Figure Created with Biorender.com O_FIG O_LINKSMALLFIG WIDTH=131 HEIGHT=200 SRC="FIGDIR/small/706832v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@1fd60e9org.highwire.dtl.DTLVardef@1e56518org.highwire.dtl.DTLVardef@15010c2org.highwire.dtl.DTLVardef@17c313a_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2022

A machine learning liver-on-a-chip system for safer drug formulation

Drug metabolism leads to biotransformations of pharmaceutical substances that alter drug efficacy, toxicity, as well as drug interactions. Modeling these processes ex vivo stands to greatly accelerate our capacity to develop safe and efficacious drugs and formulations. Recognizing the liver as the primary site of drug metabolism, here we report a novel whole-tissue ex vivo liver screening platform that enabled modeling of hepatic metabolism and tracking of hepatotoxic drug metabolites. We applied the system for the characterization of acetaminophen (APAP) metabolism and identified interactions that can mitigate the generation of toxic metabolites ex vivo. Combining our experimental platform with state-of-the-art machine learning, we validated two novel functional excipients that can prevent APAP hepatotoxicity in vivo in mice. To assess translational potential, we prototyped a novel solid dosage form with controlled release of both APAP and our functional excipients. Our this platform provides innovative potential access to actionable data on drug metabolism to support the development of new therapeutic approaches.

bioengineering↗

bioRxiv2019

Computationally guided high-throughput design of self-assembling drug nanoparticles

Nanoformulations are transforming our capacity to effectively deliver and treat a myriad of conditions. However, many nanoformulation approaches still suffer from high production complexity and low drug loading. One potential solution relies on harnessing co-assembly of drugs and small molecular excipients to facilitate nanoparticle formation through solvent exchange without the need for chemical synthesis, generating nanoparticles with up to 95% drug loading. However, there is currently no understanding which of the millions of possible combinations of small molecules can result in the formation of these nanoparticles. Here we report the development of a high-throughput screening platform coupled to machine learning to enable the rapid evaluation of such nanoformulations. Our platform identified 101 novel self-assembling drug nanoparticles from 2.1 million pairings derived from 788 candidate drugs with one of 2686 excipients, spanning treatments for multiple diseases and often harnessing well-known food additives, vitamins, or approved drugs as carrier materials - with potential for accelerated approval and translation. Given their long-term stability and potential for clinical impact, we further characterize novel sorafenib-glycyrrhizin and terbinafine-taurocholic acid nanoparticles ex vivo and in vivo. We anticipate that this platform could accelerate the development of safer and more efficacious nanoformulations with high drug loadings for a wide range of therapeutics.

bioengineering↗