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Neuhaus, R.

Publications and source records attributed to Neuhaus, R..

2 recordsLinked to original sources

Targeting a Therapy-Resistant Cancer Cell State Using Masked Electrophiles as GPX4 Inhibitors

We recently discovered that inhibition of the lipid peroxidase GPX4 can selectively kill cancer cells in a therapy-resistant state through induction of ferroptosis. Although GPX4 lacks a conventional druggable pocket, covalent small-molecule inhibitors are able to overcome this challenge by reacting with the GPX4 catalytic selenocysteine residue to eliminate enzymatic activity. Unfortunately, all currently-reported GPX4 inhibitors achieve their activity through reactive chloroacetamide groups. We demonstrate that such chloroacetamide-containing compounds are poor starting points for further advancement given their promiscuity, instability, and low bioavailability. Development of improved GPX4 inhibitors, including those with therapeutic potential, requires the identification of new electrophilic chemotypes and mechanisms of action that do not suffer these shortcomings. Here, we report our discovery that nitrile oxide electrophiles, and a set of remarkable chemical transformations that generates them in cells from masked precursors, provide an effective strategy for selective targeting of GPX4. Our results, which include structural insights, target engagement assays, and diverse GPX4-inhibitor tool compounds, provide critical insights that may galvanize development of improved compounds that illuminate the basic biology of GPX4 and therapeutic potential of ferroptosis induction. In addition, our discovery that nitrile oxide electrophiles engage in highly selective cellular interactions and are bioavailable in their masked forms may be relevant for targeting other currently undruggable proteins, such as those revealed by recent proteome-wide ligandability studies.

biochemistry

The Healthy Brain Network Biobank: An open resource for transdiagnostic research in pediatric mental health and learning disorders

Technological and methodological innovations are equipping researchers with unprecedented capabilities for detecting and characterizing pathologic processes in the developing human brain. As a result, ambitions to achieve clinically useful tools to assist in the diagnosis and management of mental health and learning disorders are gaining momentum. To this end, it is critical to accrue large-scale multimodal datasets that capture a broad range of commonly encountered clinical psychopathology. The Child Mind Institute has launched the Healthy Brain Network (HBN), an ongoing initiative focused on creating and sharing a biobank of data from 10,000 New York area participants (ages 5-21). The HBN Biobank houses data about psychiatric, behavioral, cognitive, and lifestyle phenotypes, as well as multimodal brain imaging (resting and naturalistic viewing fMRI, diffusion MRI, morphometric MRI), electroencephalography, eye-tracking, voice and video recordings, genetics, and actigraphy. Here, we present the rationale, design and implementation of HBN protocols. We describe the first data release (n = 664) and the potential of the biobank to advance related areas (e.g., biophysical modeling, voice analysis).

neuroscience