NECA derivatives exploit the paralog-specific properties of the site 3 side pocket of Grp94, the endoplasmic reticulum Hsp90.

The hsp90 chaperones govern the function of essential client proteins critical for normal cell function as well as cancer initiation and progression. Hsp90 activity is driven by ATP, which binds to the N-terminal domain and induces large conformational changes that are required for client maturation. Inhibitors targeting the ATP-binding pocket of the N-terminal domain have anticancer effects, but most bind with similar affinity to cytosolic Hsp90α and Hsp90ß, endoplasmic reticulum Grp94, and mitochondrial Trap1, the four cellular hsp90 paralogs. Paralog-specific inhibitors may lead to drugs with fewer side effects. The ATP-binding pockets of the four paralogs are flanked by three side pockets, termed sites 1, 2, and 3, which differ between the paralogs in their accessibility to inhibitors. Previous insights into the principles governing access to sites 1 and 2 have resulted in development of paralog-selective inhibitors targeting these sites, but the rules for selective targeting of site 3 are less clear. Earlier studies identified 5'N-ethylcarboxamido adenosine (NECA) as a Grp94-selective ligand. Here we use NECA and its derivatives to probe the properties of site 3. We found that derivatives that lengthen the 5' moiety of NECA improve selectivity for Grp94 over Hsp90α. Crystal structures reveal that the derivatives extend further into site 3 of Grp94 compared with their parent compound and that selectivity is due to paralog-specific differences in ligand pose and ligand-induced conformational strain in the protein. These studies provide a structural basis for Grp94-selective inhibition using site 3.

Copper Mediated Coupling of 2-(Piperazine)-pyrimidine Iodides with Aryl Thiols using Cu(I)Thiophene-2-carboxylate.

A copper-mediated synthesis of diaryl sulfides utilizing Cu(I)-thiophene-2-carboxylate (CuTC) is described. We demonstrate the use of CuTC as a soluble, non-basic catalyst in the coupling of aryl iodides and aryl thiols in the synthesis of synthetically advanced diaryl sulfides. This method allows for the successful coupling of challenging substrates including ortho-substituted and heteroaryl iodides and thiols. Additionally, most of the aryl iodide substrates used here contain the privileged piperazine scaffold bound to a pyrimidine, pyridine, or phenyl ring and thus this method allows for the elaboration of complex piperazine scaffolds into molecules of biological interest. The method described here enables the incorporation of late-stage structural diversity into diaryl sulfides containing the piperazine ring, thus enhancing the number and nature of derivatives available for SAR investigation.

Automated Endotracheal Tube Placement Check Using Semantically Embedded Deep Neural Networks.

RATIONALE AND OBJECTIVES: To develop artificial intelligence (AI) system that assists in checking endotracheal tube (ETT) placement on chest X-rays (CXRs) and evaluate whether it can move into clinical validation as a quality improvement tool. MATERIALS AND METHODS: A retrospective data set including 2000 de-identified images from intensive care unit patients was split into 1488 for training and 512 for testing. AI was developed to automatically identify the ETT, trachea, and carina using semantically embedded neural networks that combine a declarative knowledge base with deep neural networks. To check the ETT tip placement, a "safe zone" was computed as the region inside the trachea and 3-7 cm above the carina. Two AI outputs were evaluated: (1) ETT overlay, (2) ETT misplacement alert messages. Clinically relevant performance metrics were compared against prespecified thresholds of >85% overlay accuracy and positive predictive value (PPV) > 30% and negative predictive value NPV > 95% for alerts to move into clinical validation. RESULTS: An ETT was present in 285 of 512 test cases. The AI detected 95% (271/285) of ETTs, 233 (86%) of these with accurate tip localization. The system (correctly) did not generate an ETT overlay in 221/227 CXRs where the tube was absent for an overall overlay accuracy of 89% (454/512). The alert messages indicating that either the ETT was misplaced or not detected had a PPV of 83% (265/320) and NPV of 98% (188/192). CONCLUSION: The chest X-ray AI met prespecified performance thresholds to move into clinical validation.

Integration and evaluation of chest X-ray artificial intelligence in clinical practice.

Purpose: To integrate and evaluate an artificial intelligence (AI) system that assists in checking endotracheal tube (ETT) placement on chest x-rays (CXRs) in clinical practice. Approach: In clinical use over 17 months, 214 CXR images were ordered to check ETT placement with AI assistance by intensive care unit (ICU) physicians. The system was built on the SimpleMind Cognitive AI platform and integrated into a clinical workflow. It automatically identified the ETT and checked its placement relative to the trachea and carina. The ETT overlay and misplacement alert messages generated by the AI system were compared with radiology reports as the reference. A survey study was also conducted to evaluate usefulness of the AI system in clinical practice. Results: The alert messages indicating that either the ETT was misplaced or not detected had a positive predictive value of 42% (21/50) and negative predictive value of 98% (161/164) based on the radiology reports. In the survey, radiologist and ICU physician users indicated that they agreed with the AI outputs and that they were useful. Conclusions: The AI system performance in real-world clinical use was comparable to that seen in previous experiments. Based on this and physician survey results, the system can be deployed more widely at our institution, using insights gained from this evaluation to make further algorithm improvements and quality assurance of the AI system.

Systems-level analyses of protein-protein interaction network dysfunctions via epichaperomics identify cancer-specific mechanisms of stress adaptation.

Systems-level assessments of protein-protein interaction (PPI) network dysfunctions are currently out-of-reach because approaches enabling proteome-wide identification, analysis, and modulation of context-specific PPI changes in native (unengineered) cells and tissues are lacking. Herein, we take advantage of chemical binders of maladaptive scaffolding structures termed epichaperomes and develop an epichaperome-based 'omics platform, epichaperomics, to identify PPI alterations in disease. We provide multiple lines of evidence, at both biochemical and functional levels, demonstrating the importance of these probes to identify and study PPI network dysfunctions and provide mechanistically and therapeutically relevant proteome-wide insights. As proof-of-principle, we derive systems-level insight into PPI dysfunctions of cancer cells which enabled the discovery of a context-dependent mechanism by which cancer cells enhance the fitness of mitotic protein networks. Importantly, our systems levels analyses support the use of epichaperome chemical binders as therapeutic strategies aimed at normalizing PPI networks.

Evaluation of substrate and inhibitor binding to yeast and human isoprenylcysteine carboxyl methyltransferases (Icmts) using biotinylated benzophenone-containing photoaffinity probes.

Isoprenylcysteine carboxyl methyltransferases (Icmts) are a class of integral membrane protein methyltransferases localized to the endoplasmic reticulum (ER) membrane in eukaryotes. The Icmts from human (hIcmt) and Saccharomyces cerevisiae (Ste14p) catalyze the α-carboxyl methyl esterification step in the post-translational processing of CaaX proteins, including the yeast a-factor mating pheromones and both human and yeast Ras proteins. Herein, we evaluated synthetic analogs of two well-characterized Icmt substrates, N-acetyl-S-farnesyl-L-cysteine (AFC) and the yeast a-factor peptide mating pheromone, that contain photoactive benzophenone moieties in either the lipid or peptide portion of the molecule. The AFC based-compounds were substrates for both hIcmt and Ste14p, whereas the a-factor analogs were only substrates for Ste14p. However, the a-factor analogs were found to be micromolar inhibitors of hIcmt. Together, these data suggest that the Icmt substrate binding site is dependent upon features in both the isoprenyl moiety and upstream amino acid composition. Furthermore, these data suggest that hIcmt and Ste14p have overlapping, yet distinct, substrate specificities. Photocrosslinking and neutravidin-agarose capture experiments with these analogs revealed that both hIcmt and Ste14p were specifically photolabeled to varying degrees with all of the compounds tested. Our data suggest that these analogs will be useful for the future identification of the Icmt substrate binding sites.

Amide-modified prenylcysteine based Icmt inhibitors: Structure-activity relationships, kinetic analysis and cellular characterization.

Human protein isoprenylcysteine carboxyl methyltransferase (hIcmt) is the enzyme responsible for the α-carboxyl methylation of the C-terminal isoprenylated cysteine of CaaX proteins, including Ras proteins. This specific posttranslational methylation event has been shown to be important for cellular transformation by oncogenic Ras isoforms. This finding led to interest in hIcmt inhibitors as potential anti-cancer agents. Previous analog studies based on N-acetyl-S-farnesylcysteine identified two prenylcysteine-based low micromolar inhibitors (1a and 1b) of hIcmt, each bearing a phenoxyphenyl amide modification. In this study, a focused library of analogs of 1a and 1b was synthesized and screened versus hIcmt, delineating structural features important for inhibition. Kinetic characterization of the most potent analogs 1a and 1b established that both inhibitors exhibited mixed-mode inhibition and that the competitive component predominated. Using the Cheng-Prusoff method, the K(i) values were determined from the IC(50) values. Analog 1a has a K(IC) of 1.4±0.2µM and a K(IU) of 4.8±0.5µM while 1b has a K(IC) of 0.5±0.07µM and a K(IU) of 1.9±0.2µM. Cellular evaluation of 1b revealed that it alters the subcellular localization of GFP-KRas, and also inhibits both Ras activation and Erk phosphorylation in Jurkat cells.

Chemical tools for epichaperome-mediated interactome dysfunctions of the central nervous system.

Diseases are a manifestation of how thousands of proteins interact. In several diseases, such as cancer and Alzheimer's disease, proteome-wide disturbances in protein-protein interactions are caused by alterations to chaperome scaffolds termed epichaperomes. Epichaperome-directed chemical probes may be useful for detecting and reversing defective chaperomes. Here we provide structural, biochemical, and functional insights into the discovery of epichaperome probes, with a focus on their use in central nervous system diseases. We demonstrate on-target activity and kinetic selectivity of a radiolabeled epichaperome probe in both cells and mice, together with a proof-of-principle in human patients in an exploratory single group assignment diagnostic study (ClinicalTrials.gov Identifier: NCT03371420). The clinical study is designed to determine the pharmacokinetic parameters and the incidence of adverse events in patients receiving a single microdose of the radiolabeled probe administered by intravenous injection. In sum, we introduce a discovery platform for brain-directed chemical probes that specifically modulate epichaperomes and provide proof-of-principle applications in their use in the detection, quantification, and modulation of the target in complex biological systems.

Oncogenic hijacking of the stress response machinery in T cell acute lymphoblastic leukemia.

Cellular transformation is accompanied by extensive rewiring of many biological processes leading to augmented levels of distinct types of cellular stress, including proteotoxic stress. Cancer cells critically depend on stress-relief pathways for their survival. However, the mechanisms underlying the transcriptional initiation and maintenance of the oncogenic stress response remain elusive. Here, we show that the expression of heat shock transcription factor 1 (HSF1) and the downstream mediators of the heat shock response is transcriptionally upregulated in T cell acute lymphoblastic leukemia (T-ALL). Hsf1 ablation suppresses the growth of human T-ALL and eradicates leukemia in mouse models of T-ALL, while sparing normal hematopoiesis. HSF1 drives a compact transcriptional program and among the direct HSF1 targets, specific chaperones and co-chaperones mediate its critical role in T-ALL. Notably, we demonstrate that the central T-ALL oncogene NOTCH1 hijacks the cellular stress response machinery by inducing the expression of HSF1 and its downstream effectors. The NOTCH1 signaling status controls the levels of chaperone/co-chaperone complexes and predicts the response of T-ALL patient samples to HSP90 inhibition. Our data demonstrate an integral crosstalk between mediators of oncogene and non-oncogene addiction and reveal critical nodes of the heat shock response pathway that can be targeted therapeutically.

Function and Chemotypes of Human Hsp70 Chaperones.

In humans, Hsp70 chaperones are ubiquitously expressed in the cytosol, endoplasmic reticulum and mitochondria. They fulfill important roles in protein folding and the protection of cells from stress. Different forms of Hsp70 have also been found to regulate specific signaling pathways, many related to cell death. Cancer cells are notably abnormally dependent on Hsp70 chaperones for their survival. The importance of Hsp70s as drug targets is increasingly being recognized, particularly as potential cancer therapeutics. This review surveys recent advances in understanding Hsp70 mechanisms and then moves to provide an overview of current efforts directed at inhibiting Hsp70s as a target in diseases such as cancer and neurodegenerative disease.

Heat Shock Protein (HSP) Drug Discovery and Development: Targeting Heat Shock Proteins in Disease.

Heat shock proteins (HSPs) present as a double edged sword. While they play an important role in maintaining protein homeostasis in a normal cell, cancer cells have evolved to co-opt HSP function to promote their own survival. As a result, HSPs such as HSP90 have attracted a great deal of interest as a potential anticancer target. These efforts have resulted in over 20 distinct compounds entering clinical evaluation for the treatment of cancer. However, despite the potent anticancer activity demonstrated in preclinical models, to date no HSP90 inhibitor has obtained regulatory approval. In this review we discuss the unique challenges faced in targeting HSPs that have likely contributed to their lack of progress in the clinic and suggest ways to overcome these so that the enormous potential of these compounds to benefit patients can finally be realized. We also provide a guideline for the future development of HSP-targeted agents based on the many lessons learned during the last two decades in developing HSP90 inhibitors.

Chemical Tools to Investigate Mechanisms Associated with HSP90 and HSP70 in Disease.

The chaperome is a large and diverse protein machinery composed of chaperone proteins and a variety of helpers, such as the co-chaperones, folding enzymes, and scaffolding and adapter proteins. Heat shock protein 90s and 70s (HSP90s and HSP70s), the most abundant chaperome members in human cells, are also the most complex. As we have learned to appreciate, their functions are context dependent and manifested through a variety of conformations that each recruit a subset of co-chaperone, scaffolding, and folding proteins and which are further diversified by the posttranslational modifications each carry, making their study through classic genetic and biochemical techniques quite a challenge. Chemical biology tools and techniques have been developed over the years to help decipher the complexities of the HSPs and this review provides an overview of such efforts with focus on HSP90 and HSP70.

Structure-activity relationship in a purine-scaffold compound series with selectivity for the endoplasmic reticulum Hsp90 paralog Grp94.

Grp94 is involved in the regulation of a restricted number of proteins and represents a potential target in a host of diseases, including cancer, septic shock, autoimmune diseases, chronic inflammatory conditions, diabetes, coronary thrombosis, and stroke. We have recently identified a novel allosteric pocket located in the Grp94 N-terminal binding site that can be used to design ligands with a 2-log selectivity over the other Hsp90 paralogs. Here we perform extensive SAR investigations in this ligand series and rationalize the affinity and paralog selectivity of choice derivatives by molecular modeling. We then use this to design 18c, a derivative with good potency for Grp94 (IC50 = 0.22 µM) and selectivity over other paralogs (>100- and 33-fold for Hsp90α/ß and Trap-1, respectively). The paralog selectivity and target-mediated activity of 18c was confirmed in cells through several functional readouts. Compound 18c was also inert when tested against a large panel of kinases. We show that 18c has biological activity in several cellular models of inflammation and cancer and also present here for the first time the in vivo profile of a Grp94 inhibitor.

From medical images to flow computations without user-generated meshes.

Biomedical flow computations in patient-specific geometries require integrating image acquisition and processing with fluid flow solvers. Typically, image-based modeling processes involve several steps, such as image segmentation, surface mesh generation, volumetric flow mesh generation, and finally, computational simulation. These steps are performed separately, often using separate pieces of software, and each step requires considerable expertise and investment of time on the part of the user. In this paper, an alternative framework is presented in which the entire image-based modeling process is performed on a Cartesian domain where the image is embedded within the domain as an implicit surface. Thus, the framework circumvents the need for generating surface meshes to fit complex geometries and subsequent creation of body-fitted flow meshes. Cartesian mesh pruning, local mesh refinement, and massive parallelization provide computational efficiency; the image-to-computation techniques adopted are chosen to be suitable for distributed memory architectures. The complete framework is demonstrated with flow calculations computed in two 3D image reconstructions of geometrically dissimilar intracranial aneurysms. The flow calculations are performed on multiprocessor computer architectures and are compared against calculations performed with a standard multistep route.

Affinity purification probes of potential use to investigate the endogenous Hsp70 interactome in cancer.

Heat shock protein 70 (Hsp70) is a family of proteins with key roles in regulating malignancy. Cancer cells rely on Hsp70 to inhibit apoptosis, regulate senescence and autophagy, and maintain the stability of numerous onco-proteins. Despite these important biological functions in cancer, robust chemical tools that enable the analysis of the Hsp70-regulated proteome in a tumor-by-tumor manner are yet unavailable. Here we take advantage of a recently reported Hsp70 ligand to design and develop an affinity purification chemical toolset for potential use in the investigation of the endogenous Hsp70-interacting proteome in cancer. We demonstrate that these tools lock Hsp70 in complex with onco-client proteins and effectively isolate Hsp70 complexes for identification through biochemical techniques. Using these tools we provide proof-of-concept analyses that glimpse into the complex roles played by Hsp70 in maintaining a multitude of cell-specific malignancy-driving proteins.