Structure-activity Relationship Data Research Articles

From mundane to surprising nonadditivity: drivers and impact on ML models.

Nonadditivity (NA) in Structure-Activity and Structure-Property Relationship (SAR) data is a rare but very information rich phenomenon. It can indicate conformational flexibility, structural rearrangements, and errors in assay results and structural assignment. While purely ligand-based conformational causes of NA are rather well understood and mundane, other factors are less so and cause surprising NA that has a huge influence on SAR analysis and ML model performance. We here report a systematic analysis across a wide range of properties (20 on-target biological activities and 4 physicochemical ADME-related properties) to understand the frequency of various different phenomena that may lead to NA. A set of novel descriptors were developed to characterize double transformation cycles and identify trends in NA. Double transformation cycles were classified into "surprising" and "mundane" categories, with the majority being classed as mundane. We also examined commonalities among surprising cycles, finding LogP differences to have the most significant impact on NA. A distinct behavior of NA for on-target sets compared to ADME sets was observed. Finally, we show that machine learning models struggle with highly nonadditive data, indicating that a better understanding of NA is an important future research direction.

Silicon-Rhodamine Functionalized Evocalcet Probes Potently and Selectively Label Calcium Sensing Receptors In Vitro, In Vivo, and Ex Vivo.

The calcium sensing receptor (CaSR) is a ubiquitously expressed G-protein coupled receptor (GPCR) that regulates extracellular calcium signals via the parathyroid glands. CaSR has recently also been implicated in noncalcitropic pathophysiologies like asthma, gut inflammation, and cancer. To date, molecular tools that enable the bioimaging of CaSR in tissues are lacking. Based on in silico analyses of available structure-activity relationship data on CaSR ligands, we designed and prepared silicon-rhodamine (SiR) conjugates of the clinically approved drug evocalcet. The new probes EvoSiR4 and EvoSiR6, with differing linker lengths at the evocalcet carboxyl end, both showed a 6-fold and 3-fold increase in potency toward CaSR (EC50 < 45 nM) compared to evocalcet and the evocalcet-linker conjugate, respectively, in an FLIPR-based cellular functional assay. The specificity of the EvoSiR probes toward CaSR binding and the impact of albumin was evaluated in live cell experiments. Both probes showed strong albumin binding, which facilitated the clearance of nonspecific binding interactions. Accordingly, in zebrafish embryos, EvoSiR4 specifically labeled the high CaSR expressing neuromasts of the lateral line in vivo. EvoSiR4 was also assessed in human parathyroid tissues ex vivo, showing a specific absolute CaSR-associated fluorescence compared to that of parathyroid autofluorescence. In summary, functionalization of evocalcet by SiR led to the preparation of potent and specific fluorescent CaSR probes. EvoSiR4 is a versatile small-molecular probe that can be employed in CaSR-related biomedical analyses where antibodies are not applicable.

KNIME workflows for applications in medicinal and computational chemistry

Artificial intelligence (AI) has huge potential to accelerate drug discovery, but challenges remain in implementing AI algorithms that can be used by the broad scientific community. Identification of molecular features and their subsequent use in training of machine learning models may permit prediction of new molecules with enhanced properties. Predictive modeling is particularly applicable to analysis of structure-activity relationships (SARs) and would be a useful tool in the hands of laboratory medicinal chemists. This requires a software platform that is chemically intuitive while providing the user with access to AI methods. The KNIME platform provides such an environment through inclusion of broad chemical toolsets and a user-friendly approach for utilization of machine learning for analysis of SAR data. Here, we illustrate use of KNIME for this purpose, with a focus on discovery of features of highly potent tau inhibitors from a series of structurally diverse polyphenols. Workflows are described that enable implementation of AI tools in KNIME for diverse SAR projects.

Expanding the Chemical Space of Transforming Growth Factor-β (TGFβ) Receptor Type II Degraders with 3,4-Disubstituted Indole Derivatives.

The TGFβ type II receptor (TβRII) is a central player in all TGFβ signaling downstream events, has been linked to cancer progression, and thus, has emerged as an auspicious anti-TGFβ strategy. Especially its targeted degradation presents an excellent goal for effective TGFβ pathway inhibition. Here, cellular structure-activity relationship (SAR) data from the TβRII degrader chemotype 1 was successfully transformed into predictive ligand-based pharmacophore models that allowed scaffold hopping. Two distinct 3,4-disubstituted indoles were identified from virtual screening: tetrahydro-4-oxo-indole 2 and indole-3-acetate 3. Design, synthesis, and screening of focused amide libraries confirmed 2r and 3n as potent TGFβ inhibitors. They were validated to fully recapitulate the ability of 1 to selectively degrade TβRII, without affecting TβRI. Consequently, 2r and 3n efficiently blocked endothelial-to-mesenchymal transition and cell migration in different cancer cell lines while not perturbing the microtubule network. Hence, 2 and 3 present novel TβRII degrader chemotypes that will (1) aid target deconvolution efforts and (2) accelerate proof-of-concept studies for small-molecule-driven TβRII degradation in vivo.

Beyond Amyloid: A Machine Learning-Driven Approach Reveals Properties of Potent GSK-3β Inhibitors Targeting Neurofibrillary Tangles.

Current treatments for Alzheimer's disease (AD) focus on slowing memory and cognitive decline, but none offer curative outcomes. This study aims to explore and curate the common properties of active, drug-like molecules that modulate glycogen synthase kinase 3β (GSK-3β), a well-documented kinase with increased activity in tau hyperphosphorylation and neurofibrillary tangles-hallmarks of AD pathology. Leveraging quantitative structure-activity relationship (QSAR) data from the PubChem and ChEMBL databases, we employed seven machine learning models: logistic regression (LogR), k-nearest neighbors (KNN), random forest (RF), support vector machine (SVM), extreme gradient boosting (XGB), neural networks (NNs), and ensemble majority voting. Our goal was to correctly predict active and inactive compounds that inhibit GSK-3β activity and identify their key properties. Among the six individual models, the NN demonstrated the highest performance with a 79% AUC-ROC on unbalanced external validation data, while the SVM model was superior in accurately classifying the compounds. The SVM and RF models surpassed NN in terms of Kappa values, and the ensemble majority voting model demonstrated slightly better accuracy to the NN on the external validation data. Feature importance analysis revealed that hydrogen bonds, phenol groups, and specific electronic characteristics are important features of molecular descriptors that positively correlate with active GSK-3β inhibition. Conversely, structural features like imidazole rings, sulfides, and methoxy groups showed a negative correlation. Our study highlights the significance of structural, electronic, and physicochemical descriptors in screening active candidates against GSK-3β. These predictive features could prove useful in therapeutic strategies to understand the important properties of GSK-3β candidate inhibitors that may potentially benefit non-amyloid-based AD treatments targeting neurofibrillary tangles.

Structural Development of Androgen Receptor Antagonists Using Phenylferrocene Framework as a Hydrophobic Pharmacophore.

We previously identified nitrophenylferrocenes and cyanophenylferrocenes as promising lead structures of novel androgen receptor (AR) antagonists, based on the structural similarity between ferrocene and the steroidal skeleton. In the present research, we explored the structure-activity relationship (SAR) of phenylferrocene derivatives. Introduction of a hydrophobic substituent such as a chlorine atom at the 2-position or 3-position of phenylferrocene derivatives significantly increased the antagonistic activity toward wild-type AR, and among the synthesized compounds, 3-chloro-4-cyanophenylferrocene (29) exhibited the most potent anti-proliferative activity toward the androgen-dependent growth of SC-3 cells expressing wild-type AR (IC50 14 nM). Like conventional antiandrogens such as hydroxyflutamide, the major active metabolite of flutamide, compound 29 exhibited agonistic activity toward T877A-AR, a mutant AR expressed in human prostate cancer cell line LNCaP. Notably, however, the 2-chloro isomer 27 showed potent antagonistic activity toward wild-type AR (IC50 49 nM) and also exhibited antagonistic activity toward T877A-AR. Our SAR data should prove helpful for the development of new-generation AR antagonists based on phenylferrocene as candidate agents to treat drug-resistant prostate cancer.

Generalizability Improvement of Interpretable Symbolic Regression Models for Quantitative Structure-Activity Relationships.

In the pursuit of optimal quantitative structure-activity relationship (QSAR) models, two key factors are paramount: the robustness of predictive ability and the interpretability of the model. Symbolic regression (SR) searches for the mathematical expressions that explain a training data set. Thus, the models provided by SR are globally interpretable. We previously proposed an SR method that can generate interpretable expressions by humans. This study introduces an enhanced symbolic regression method, termed filter-induced genetic programming 2 (FIGP2), as an extension of our previously proposed SR method. FIGP2 is designed to improve the generalizability of SR models and to be applicable to data sets in which cost-intensive descriptors are employed. The FIGP2 method incorporates two major improvements: a modified domain filter to eradicate diverging expressions based on optimal calculation and the introduction of a stability metric to penalize expressions that would lead to overfitting. Our retrospective comparative analysis using 12 structure-activity relationship data sets revealed that FIGP2 surpassed the previously proposed SR method and conventional modeling methods, such as support vector regression and multivariate linear regression in terms of predictive performance. Generated mathematical expressions by FIGP2 were relatively simple and not divergent in the domain of function. Taken together, FIGP2 can be used for making interpretable regression models with predictive ability.

Selective targeting of human TET1 by cyclic peptide inhibitors: Insights from biochemical profiling

Ten-Eleven Translocation (TET) enzymes are Fe(II)/2OG-dependent oxygenases that play important roles in epigenetic regulation, but selective inhibition of the TETs is an unmet challenge. We describe the profiling of previously identified TET1-binding macrocyclic peptides. TiP1 is established as a potent TET1 inhibitor (IC50 = 0.26 µM) with excellent selectivity over other TETs and 2OG oxygenases. TiP1 alanine scanning reveals the critical roles of Trp10 and Glu11 residues for inhibition of TET isoenzymes. The results highlight the utility of the RaPID method to identify potent enzyme inhibitors with selectivity over closely related paralogues. The structure–activity relationship data generated herein may find utility in the development of chemical probes for the TETs.

Discovery of Potential Prolyl-tRNA Synthetase Allosteric Inhibitor Through Virtual Screening and In Vitro Assay against Plasmodium falciparum

Objectives: This study aimed to identify novel antimalarial compounds based on allosteric inhibitor of prolyl-tRNA synthetase using hierarchical virtual screening. Materials and Methods: Pharmacophore model was designed initially, based on the structure-activity relationships data between several pyrazole-urea analogues and their IC50 enzymatic value. The model obtained was applied to screen ZINC15 database, after which followed by drug-likeness, toxicophore, and PAINS filter. The hit compounds were docked against P. falciparum prolyl-tRNA synthetase enzyme, using validated docking method. The resulting docking poses were ranked based on the docking score and re-evaluated based on the pharmacophore criteria. Top five compounds were obtained from this step and then evaluated using molecular dynamics simulation to verify its stability and hydrogen bond dynamics over 50 nanoseconds. MM-PBSA analysis was also performed to estimate their binding free energy. Ultimately, their potential bioactivity as antimalarial candidates have been verified against 3D7 strain. Results: The results showed that all five compounds obtained from virtual screening possess micromolar potency in vitro. Two compounds (ZINC 1029449 and ZINC1029453), yield high antimalarial activity (0.44 and 0.72 μM, respectively) Conclusions: Overall, the virtual screening approach has successfully produced lead compounds which can be further optimized to be antimalarial agents.

Consensus docking aid to model the activity of an inhibitor of DNA methyltransferase 1 inspired by de novo design

The structure-activity relationships data available in public databases of inhibitors of DNA methyltransferases (DNMTs), families of epigenetic targets, plus the structural information of DNMT1, enables the development of a robust structure-based drug design strategy to study, at the molecular level, the activity of DNMTs inhibitors. In this study, we discuss a consensus molecular docking strategy to aid in explaining the activity of small molecules tested as inhibitors of DNMT1. The consensus docking approach, which was based on three validated docking algorithms of different designs, had an overall good agreement with the experimental enzymatic inhibition assays reported in the literature. The docking protocol was used to explain, at the molecular level, the activity profile of a novel DNMT1 inhibitor with a distinct chemical scaffold whose identification was inspired by de novo design and complemented with similarity searching.

Drug-Induced Conformational Dynamics of P-Glycoprotein Underlies the Transport of Camptothecin Analogs.

P-glycoprotein (Pgp) plays a pivotal role in drug bioavailability and multi-drug resistance development. Understanding the protein's activity and designing effective drugs require insight into the mechanisms underlying Pgp-mediated transport of xenobiotics. In this study, we investigated the drug-induced conformational changes in Pgp and adopted a conformationally-gated model to elucidate the Pgp-mediated transport of camptothecin analogs (CPTs). While Pgp displays a wide range of conformations, we simplified it into three model states: 'open-inward', 'open-outward', and 'intermediate'. Utilizing acrylamide quenching of Pgp fluorescence as a tool to examine the protein's tertiary structure, we observed that topotecan (TPT), SN-38, and irinotecan (IRT) induced distinct conformational shifts in the protein. TPT caused a substantial shift akin to AMPPNP, suggesting ATP-independent 'open-outward' conformation. IRT and SN-38 had relatively moderate effects on the conformation of Pgp. Experimental atomic force microscopy (AFM) imaging supports these findings. Further, the rate of ATPase hydrolysis was correlated with ligand-induced Pgp conformational changes. We hypothesize that the separation between the nucleotide-binding domains (NBDs) creates a conformational barrier for substrate transport. Substrates that reduce the conformational barrier, like TPT, are better transported. The affinity for ATP extracted from Pgp-mediated ATP hydrolysis kinetics curves for TPT was about 2-fold and 3-fold higher than SN-38 and IRT, respectively. On the contrary, the dissociation constants (KD) determined by fluorescence quenching for these drugs were not significantly different. Saturation transfer double difference (STDD) NMR of TPT and IRT with Pgp revealed that similar functional groups of the CPTs are accountable for Pgp-CPTs interactions. Efforts aimed at modifying these functional groups, guided by available structure-activity relationship data for CPTs and DNA-Topoisomerase-I complexes, could pave the way for the development of more potent next-generation CPTs.

Optimization of pyridylpiperazine-based inhibitors of the Escherichia coli AcrAB-TolC efflux pump

Multidrug–resistant Escherichia coli is a continuously growing worldwide public health problem, in which the well-known AcrAB-TolC tripartite RND efflux pump is a critical driver. We have previously described pyridylpiperazines as a novel class of allosteric inhibitors of E. coli AcrB which bind to a unique site in the protein transmembrane domain, allowing for the potentiation of antibiotic activity. Here, we show a rational optimization of pyridylpiperazines by modifying three specific derivatization points of the pyridine core to improve the potency and the pharmacokinetic properties of this chemical series. In particular, this work found that the introduction of a primary amine to the pyridine through ester (29, BDM91270) or oxadiazole (44, BDM91514) based linkers allowed for analogues with improved antibiotic boosting potency through AcrB inhibition. In vitro studies, using genetically engineered mutants, showed that this improvement in potency is mediated through novel interactions with distal acidic residues of the AcrB binding pocket. Of the two leads, compound 44 was found to have favorable physico-chemical properties and suitable plasma and microsomal stability. Together, this work expands the current structure-activity relationship data on pyridylpiperazine efflux pump inhibitors, and provides a promising step towards future in vivo proof of concept of pyridylpiperazines as antibiotic potentiators.

Synthesis and preliminary evaluation of benzylaminoimidazoline derivatives as novel norepinephrine transporter ligands.

A series of benzylaminoimidazoline derivatives was synthesized and evaluated for norepinephrine transporter (NET) targeting. Among them, N-(3-iodobenzyl)-4,5-dihydro-1H-imidazol-2-amine (Compound 9) displayed the highest affinity for NET (IC50 = 5.65 ± 0.97 μM). The corresponding radiotracer [125 I]9 was further prepared by copper-mediated radioiodination and evaluated both in vitro and in vivo. The cellular uptake results suggested that [125 I]9 was specifically taken up by the NET-expressing SK-N-SH cell line. Biodistribution studies showed that [125 I]9 accumulated in the heart (5.54 ± 1.24 %ID/g at 5 min p.i. and 0.79 ± 0.08 %ID/g at 2 h p.i.) and adrenal gland (14.83 ± 3.47 %ID/g at 5 min p.i. and 3.87 ± 0.24 %ID/g at 2 h p.i.). The uptake in the heart and adrenal gland could be significantly inhibited by preinjection of desipramine (DMI). These results indicated that the benzylaminoimidazoline derivatives retained affinity for NET, which could provide structure-activity relationship data for further studies.

Structure of the complex between calmodulin and a functional construct of eukaryotic elongation factor 2 kinase bound to an ATP-competitive inhibitor

The calmodulin-activated α-kinase, eukaryotic elongation factor 2 kinase (eEF-2K), serves as a master regulator of translational elongation by specifically phosphorylating and reducing the ribosome affinity of the guanosine triphosphatase, eukaryotic elongation factor 2 (eEF-2). Given its critical role in a fundamental cellular process, dysregulation of eEF-2K has been implicated in several human diseases, including those of the cardiovascular system, chronic neuropathies, and many cancers, making it a critical pharmacological target. In the absence of high-resolution structural information, high-throughput screening efforts have yielded small-molecule candidates that show promise as eEF-2K antagonists. Principal among these is the ATP-competitive pyrido-pyrimidinedione inhibitor, A-484954, which shows high specificity toward eEF-2K relative to a panel of "typical" protein kinases. A-484954 has been shown to have some degree of efficacy in animal models of several disease states. It has also been widely deployed as a reagent in eEF-2K-specific biochemical and cell-biological studies. However, given the absence of structural information, the precise mechanism of the A-484954-mediated inhibition of eEF-2K has remained obscure. Leveraging our identification of the calmodulin-activatable catalytic core of eEF-2K, and our recent determination of its long-elusive structure, here we present the structural basis for its specific inhibition by A-484954. This structure, which represents the first for an inhibitor-bound catalytic domain of a member of the α-kinase family, enables rationalization of the existing structure-activity relationship data for A-484954 variants and lays the groundwork for further optimization of this scaffold to attain enhanced specificity/potency against eEF-2K.

Critical Non-Covalent Binding Intermediate for an Allosteric Covalent Inhibitor of SUMO E1.

Post-translational modifications by small ubiquitin-like modifiers (SUMOs) are dysregulated in many types of cancers. The SUMO E1 enzyme has recently been suggested as a new immuno-oncology target. COH000 was recently identified as a highly specific allosteric covalent inhibitor of SUMO E1. However, a marked discrepancy was found between the X-ray structure of the covalent COH000-bound SUMO E1 complex and the available structure-activity relationship (SAR) data of inhibitor analogues due to unresolved noncovalent protein-ligand interactions. Here, we have investigated noncovalent interactions between COH000 and SUMO E1 during inhibitor dissociation through novel Ligand Gaussian accelerated molecular dynamics (LiGaMD) simulations. Our simulations have identified a critical low-energy non-covalent binding intermediate conformation of COH000 that agreed excellently with published and new SAR data of the COH000 analogues, which were otherwise inconsistent with the X-ray structure. Altogether, our biochemical experiments and LiGaMD simulations have uncovered a critical non-covalent binding intermediate during allosteric inhibition of the SUMO E1 complex.

Synthesis and Biological Evaluation of 3-Amino-4,4-Dimethyl Lithocholic Acid Derivatives as Novel, Selective, and Cellularly Active Allosteric SHP1 Activators.

Src homology 2 domain-containing protein tyrosine phosphatase 1 (SHP1), a non-receptor member of the protein tyrosine phosphatase (PTP) family, negatively regulates several signaling pathways that are responsible for pathological cell processes in cancers. In this study, we report a series of 3-amino-4,4-dimethyl lithocholic acid derivatives as SHP1 activators. The most potent compounds, 5az-ba, showed low micromolar activating effects (EC50: 1.54-2.10 μM) for SHP1, with 7.63-8.79-fold maximum activation and significant selectivity over the closest homologue Src homology 2 domain-containing protein tyrosine phosphatase 2 (SHP2) (>32-fold). 5az-ba showed potent anti-tumor effects with IC50 values of 1.65-5.51 μM against leukemia and lung cancer cells. A new allosteric mechanism of SHP1 activation, whereby small molecules bind to a central allosteric pocket and stabilize the active conformation of SHP1, was proposed. The activation mechanism was consistent with the structure-activity relationship (SAR) data. This study demonstrates that 3-amino-4,4-dimethyl lithocholic acid derivatives can be selective SHP1 activators with potent cellular efficacy.

Simple monocyclic pyrimidine analogs as microtubule targeting agents binding to the colchicine site

Complex natural products that bind to tubulin/microtubules come under the broad category of microtubule binding agents. The design of simplified analogs of previously reported bicyclic, microtubule depolymerizer, pyrrolo[2,3–d]pyrimidine, provided valuable structure–activity relationship data and led to the identification of novel monocyclic pyrimidine analogs of which 12 was 47-fold more potent (EC50 123 nM) for cellular microtubule depolymerization activity and 7.5-fold more potent (IC50 24.4 nM) at inhibiting the growth of MDA-MB-435 cancer cells, suggesting significantly better binding of the target within the colchicine site of tubulin compared to lead compound 1. This compound and others of this series of monocyclic pyrimidine analogs were able to overcome multidrug resistance due to the expression of the βIII-isotype of tubulin and P-glycoprotein. In vivo evaluation of the most potent analog 12 in an MDA-MB-435 xenograft mouse model indicated, along with paclitaxel, that both compounds showed a trend towards lower tumor volume however neither compound showed significant antitumor activity in the trial. To our knowledge these are the first examples of simple substituted monocyclic pyrimidines as colchicine site binding antitubulin compounds with potent antitumor activity.

New Iron Twist to Chloroquine─Upgrading Antimalarials with Immunomodulatory and Antimicrobial Features.

Herein, upgraded chloroquine (CQ) derivatives capable of overcoming Plasmodium resistance and, at the same time, suppressing excessive immune response and risk of concurrent bacteremia were developed. Twelve new ferrocene-CQ hybrids tethered with a small azathia heterocycle (1,3-thiazolidin-4-one, 1,3-thiazinan-4-one, or 5-methyl-1,3-thiazolidin-4-one) were synthesized and fully characterized. All hybrids were evaluated for their in vitro antiplasmodial, antimicrobial, and immunomodulatory activities. Additional assays were performed on selected hybrids to gain insights into their mode of action. Although only hybrid 4a was more potent than the parent drug toward CQ-resistant Dd2 Plasmodium falciparum strain, several other hybrids (such as 6b, 6c, and 6d) manifested substantially improved antimicrobial and immunomodulatory properties. Interesting structure-activity relationship data were obtained, hinting at future research for the development of new multitarget chemotherapies for malaria and other infectious diseases complicated by drug resistance, bacterial co-infection, and immune-driven pathology issues.

Significance of Benzimidazole analogues for the creation of novel molecules in drug discovery

Fused heterocyclic derivatives have become an important scaffold nowadays, which could be used as a template in drug development and medicinal chemistry. Benzimidazole moiety is an imperious aromatic heterocycle which is frequently present in naturally occurring products such as purines, vitamin B 12 and histidine as well as synthesized bioactive compounds, indomethacin and albendazole, for example. This study comprises widespread and comprehensive literature analysis on chemical reactivity and biological properties associated with Benzimidazole containing molecules. Benzimidazole ring structure possesses an extensive variety of pharmacological activities in several medications of therapeutic interest against a variety of diseases such as hypertension, malaria, cancer, microbial diseases, inflammatory disorders, etc. Furthermore, this fused heterocycle benzimidazole core might interact with various anions and cations in addition to biomolecules over different reactions in the human body, therefore exhibiting wide-ranging biological activities such as antineoplastic, antibacterial and antifungal, anti-inflammatory and analgesic, antihypertensive, antiviral and antidepressant. In this review, we are focusing on the chemistry and recent biological activities, designing approaches, and SAR (structure-activity relationship) data of different benzimidazole-based analogues during the past years.

Identification of a Cardiac Glycoside Exhibiting Favorable Brain Bioavailability and Potency for Reducing Levels of the Cellular Prion Protein.

Several strands of investigation have established that a reduction in the levels of the cellular prion protein (PrPC) is a promising avenue for the treatment of prion diseases. We recently described an indirect approach for reducing PrPC levels that targets Na,K-ATPases (NKAs) with cardiac glycosides (CGs), causing cells to respond with the degradation of these pumps and nearby molecules, including PrPC. Because the therapeutic window of widely used CGs is narrow and their brain bioavailability is low, we set out to identify a CG with improved pharmacological properties for this indication. Starting with the CG known as oleandrin, we combined in silico modeling of CG binding poses within human NKA folds, CG structure-activity relationship (SAR) data, and predicted blood-brain barrier (BBB) penetrance scores to identify CG derivatives with improved characteristics. Focusing on C4'-dehydro-oleandrin as a chemically accessible shortlisted CG derivative, we show that it reaches four times higher levels in the brain than in the heart one day after subcutaneous administration, exhibits promising pharmacological properties, and suppresses steady-state PrPC levels by 84% in immortalized human cells that have been differentiated to acquire neural or astrocytic characteristics. Finally, we validate that the mechanism of action of this approach for reducing cell surface PrPC levels requires C4'-dehydro-oleandrin to engage with its cognate binding pocket within the NKA α subunit. The improved brain bioavailability of C4'-dehydro-oleandrin, combined with its relatively low toxicity, make this compound an attractive lead for brain CG indications and recommends its further exploration for the treatment of prion diseases.