Phenotypic screening with deep learning identifies HDAC6 inhibitors as cardioprotective in a BAG3 mouse model of dilated cardiomyopathy

Preferential HDAC6 inhibitors derived from HPOB exhibit synergistic antileukemia activity in combination with decitabine

Histone deacetylase 6 (HDAC6) is an emerging drug target to treat oncological and non-oncological conditions. Since highly selective HDAC6 inhibitors display limited anticancer activity when used as single agent, they usually require combination therapies with other chemotherapeutics. In this work, we synthesized a mini library of analogues of the preferential HDAC6 inhibitor HPOB in only two steps via an Ugi four-component reaction as the key step. Biochemical HDAC inhibition and cell viability assays led to the identification of 1g (highest antileukemic activity) and 2b (highest HDAC6 inhibition) as hit compounds. In subsequent combination screens, both 1g and especially 2b showed synergy with DNA methyltransferase inhibitor decitabine in acute myeloid leukemia (AML). Our findings highlight the potential of combining HDAC6 inhibitors with DNA methyltransferase inhibitors as a strategy to improve AML treatment outcomes.

Design, synthesis and neuroprotective biological evaluation of novel HDAC6 inhibitors incorporating benzothiadiazinyl systems as cap groups

Histone deacetylase 6 (HDAC6), as the key regulatory enzyme, plays an important role in the development of the nervous system. More and more studies indicate that HDAC6 has become a promising therapeutic target for CNS diseases. Herein we designed and synthesized a series of novel HDAC6 inhibitors with benzothiadiazinyl systems as cap groups and evaluated their activity in vitro and in vivo. Among them, compound 3 exhibited superior selective inhibitory activity against HDAC6 (IC50 = 5.1 nM, about 30-fold selectivity over HDAC1). The results of docking showed that compound 3 can interact well with the key amino acid residues of HDAC6. Compound 3 showed lower cytotoxicity (20 μM to SH-SY5Y cells, inhibition rate = 25.75%) and better neuroprotective activity against L-glutamate-induced SH-SY5Y cell injury model in vitro. Meanwhile, compound 3 exhibited weak cardiotoxicity (10 μM hERG inhibition rate = 17.35%) and possess good druggability properties. Especially, compound 3 could significantly reduce cerebral infarction from 49.87% to 32.18%, and similar with butylphthalide in MCAO model, indicating potential clinical application prospects for alleviating ischemic stroke-induced brain infarction.

Deep Learning-Driven Exploration of Pyrroloquinoline Quinone Neuroprotective Activity in Alzheimer's Disease

Alzheimer's disease (AD) is a pressing concern in neurodegenerative research. To address the challenges in AD drug development, especially those targeting Aβ, this study uses deep learning and a pharmacological approach to elucidate the potential of pyrroloquinoline quinone (PQQ) as a neuroprotective agent for AD. Using deep learning for a comprehensive molecular dataset, blood-brain barrier (BBB) permeability is predicted and the anti-inflammatory and antioxidative properties of compounds are evaluated. PQQ, identified in the Mediterranean-DASH intervention for a diet that delays neurodegeneration, shows notable BBB permeability and low toxicity. In vivo tests conducted on an Aβ₁₋₄₂-induced AD mouse model verify the effectiveness of PQQ in reducing cognitive deficits. PQQ modulates genes vital for synapse and anti-neuronal death, reduces reactive oxygen species production, and influences the SIRT1 and CREB pathways, suggesting key molecular mechanisms underlying its neuroprotective effects. This study can serve as a basis for future studies on integrating deep learning with pharmacological research and drug discovery.

Targeting HDAC6 to treat heart failure with preserved ejection fraction in mice

Heart failure with preserved ejection fraction (HFpEF) poses therapeutic challenges due to the limited treatment options. Building upon our previous research that demonstrates the efficacy of histone deacetylase 6 (HDAC6) inhibition in a genetic cardiomyopathy model, we investigate HDAC6's role in HFpEF due to their shared mechanisms of inflammation and metabolism. Here, we show that inhibiting HDAC6 with TYA-018 effectively reverses established heart failure and its associated symptoms in male HFpEF mouse models. Additionally, in male mice lacking Hdac6 gene, HFpEF progression is delayed and they are resistant to TYA-018's effects. The efficacy of TYA-018 is comparable to a sodium-glucose cotransporter 2 (SGLT2) inhibitor, and the combination shows enhanced effects. Mechanistically, TYA-018 restores gene expression related to hypertrophy, fibrosis, and mitochondrial energy production in HFpEF heart tissues. Furthermore, TYA-018 also inhibits activation of human cardiac fibroblasts and enhances mitochondrial respiratory capacity in cardiomyocytes. In this work, our findings show that HDAC6 impacts on heart pathophysiology and is a promising target for HFpEF treatment.

Selective and Bioavailable HDAC6 2-(Difluoromethyl)-1,3,4-oxadiazole Substrate Inhibitors and Modeling of Their Bioactivation Mechanism

Histone deacetylase 6 (HDAC6) is a unique member of the HDAC family mainly targeting cytosolic nonhistone substrates, such as α-tubulin, cortactin, and heat shock protein 90 to regulate cell proliferation, metastasis, invasion, and mitosis in tumors. We describe the identification and characterization of a series of 2-(difluoromethyl)-1,3,4-oxadiazoles (DFMOs) as selective nonhydroxamic acid HDAC6 inhibitors. By comparing structure-activity relationships and performing quantum mechanical calculations of the HDAC6 catalytic mechanism, we show that potent oxadiazoles are electrophilic substrates of HDAC6 and propose a mechanism for the bioactivation. We also observe that the inherent electrophilicity of the oxadiazoles makes them prone to degradation in water solution and the generation of potentially toxic products cannot be ruled out, limiting the developability for chronic diseases. However, the oxadiazoles demonstrate high oral bioavailability and low in vivo clearance and are excellent tools for studying the role of HDAC6 in vitro and in vivo in rats and mice.

Use of Deep-Learning Assisted Assessment of Cardiac Parameters in Zebrafish to Discover Cyanidin Chloride as a Novel Keap1 Inhibitor Against Doxorubicin-Induced Cardiotoxicity

Doxorubicin-induced cardiomyopathy (DIC) brings tough clinical challenges as well as continued demand in developing agents for adjuvant cardioprotective therapies. Here, a zebrafish phenotypic screening with deep-learning assisted multiplex cardiac functional analysis using motion videos of larval hearts is established. Through training the model on a dataset of 2125 labeled ventricular images, ZVSegNet and HRNet exhibit superior performance over previous methods. As a result of high-content phenotypic screening, cyanidin chloride (CyCl) is identified as a potent suppressor of DIC. CyCl effectively rescues cardiac cell death and improves heart function in both in vitro and in vivo models of Doxorubicin (Dox) exposure. CyCl shows strong inhibitory effects on lipid peroxidation and mitochondrial damage and prevents ferroptosis and apoptosis-related cell death. Molecular docking and thermal shift assay further suggest a direct binding between CyCl and Keap1, which may compete for the Keap1-Nrf2 interaction, promote nuclear accumulation of Nrf2, and subsequentially transactivate Gpx4 and other antioxidant factors. Site-specific mutation of R415A in Keap1 significantly attenuates the protective effects of CyCl against Dox-induced cardiotoxicity. Taken together, the capability of deep-learning-assisted phenotypic screening in identifying promising lead compounds against DIC is exhibited, and new perspectives into drug discovery in the era of artificial intelligence are provided.

AI-powered therapeutic target discovery

Disease modeling and target identification are the most crucial initial steps in drug discovery, and influence the probability of success at every step of drug development. Traditional target identification is a time-consuming process that takes years to decades and usually starts in an academic setting. Given its advantages of analyzing large datasets and intricate biological networks, artificial intelligence (AI) is playing a growing role in modern drug target identification. We review recent advances in target discovery, focusing on breakthroughs in AI-driven therapeutic target exploration. We also discuss the importance of striking a balance between novelty and confidence in target selection. An increasing number of AI-identified targets are being validated through experiments and several AI-derived drugs are entering clinical trials; we highlight current limitations and potential pathways for moving forward.

An Unbiased Screen Identified the Hsp70-BAG3 Complex as a Regulator of Myosin-Binding Protein C3

Variants in the gene myosin-binding protein C3 (MYBPC3) account for approximately 50% of familial hypertrophic cardiomyopathy (HCM), leading to reduced levels of myosin-binding protein C3 (MyBP-C), the protein product made by gene MYBPC3. Elucidation of the pathways that regulate MyBP-C protein homeostasis could uncover new therapeutic strategies. Toward this goal, we screened a library of 2,426 bioactive compounds and identified JG98, an allosteric modulator of heat shock protein 70 that inhibits interaction with Bcl-2-associated athanogene (BAG) domain co-chaperones. JG98 reduces MyBP-C protein levels. Furthermore, genetic reduction of BAG3 phenocopies treatment with JG-98 by reducing MYBP-C protein levels.. Thus, an unbiased compound screen identified the heat shock protein 70-BAG3 complex as a regulator of MyBP-C stability.

Transcriptome studies of inherited dilated cardiomyopathies

Dilated cardiomyopathy (DCM) is a group of heart muscle diseases that often lead to heart failure, with more than 50 causative genes have being linked to DCM. The heterogenous nature of the inherited DCMs suggest the need of precision medicine. Consistent with this emerging concept, transcriptome studies in human patients with DCM indicated distinct molecular signature for DCMs of different genetic etiology. To facilitate this line of research, we reviewed the status of transcriptome studies of inherited DCMs by focusing on three predominant DCM causative genes, TTN, LMNA, and BAG3. Besides studies in human patients, we summarized transcriptomic analysis of these inherited DCMs in a variety of model systems ranging from iPSCs to rodents and zebrafish. We concluded that the RNA-seq technology is a powerful genomic tool that has already led to the discovery of new modifying genes, signaling pathways, and related therapeutic avenues. We also pointed out that both temporal (different pathological stages) and spatial (different cell types) information need to be considered for future transcriptome studies. While an important bottle neck is the low throughput in experimentally testing differentially expressed genes, new technologies in efficient animal models such as zebrafish starts to be developed. It is anticipated that the RNA-seq technology will continue to uncover both unique and common pathological events, aiding the development of precision medicine for inherited DCMs.

Augmentation of Histone Deacetylase 6 Activity Impairs Mitochondrial Respiratory Complex I in Ischemic/Reperfused Diabetic Hearts

BACKGROUND

Diabetes augments activity of histone deacetylase 6 (HDAC6) and generation of tumor necrosis factor α (TNFα) and impairs the physiological function of mitochondrial complex I (mCI) which oxidizes reduced nicotinamide adenine dinucleotide (NADH) to nicotinamide adenine dinucleotide to sustain the tricarboxylic acid cycle and β-oxidation. Here we examined how HDAC6 regulates TNFα production, mCI activity, mitochondrial morphology and NADH levels, and cardiac function in ischemic/reperfused diabetic hearts.

METHODS

HDAC6 knockout, streptozotocin-induced type 1 diabetic, and obese type 2 diabetic db/db mice underwent myocardial ischemia/reperfusion injury in vivo or ex vivo in a Langendorff-perfused system. H9c2 cardiomyocytes with and without HDAC6 knockdown were subjected to hypoxia/reoxygenation injury in the presence of high glucose. We compared the activities of HDAC6 and mCI, TNFα and mitochondrial NADH levels, mitochondrial morphology, myocardial infarct size, and cardiac function between groups.

RESULTS

Myocardial ischemia/reperfusion injury and diabetes synergistically augmented myocardial HDCA6 activity, myocardial TNFα levels, and mitochondrial fission and inhibited mCI activity. Interestingly, neutralization of TNFα with an anti-TNFα monoclonal antibody augmented myocardial mCI activity. Importantly, genetic disruption or inhibition of HDAC6 with tubastatin A decreased TNFα levels, mitochondrial fission, and myocardial mitochondrial NADH levels in ischemic/reperfused diabetic mice, concomitant with augmented mCI activity, decreased infarct size, and ameliorated cardiac dysfunction. In H9c2 cardiomyocytes cultured in high glucose, hypoxia/reoxygenation augmented HDAC6 activity and TNFα levels and decreased mCI activity. These negative effects were blocked by HDAC6 knockdown.

CONCLUSIONS

Augmenting HDAC6 activity inhibits mCI activity by increasing TNFα levels in ischemic/reperfused diabetic hearts. The HDAC6 inhibitor, tubastatin A, has high therapeutic potential for acute myocardial infarction in diabetes.