Structure and Function of RhoBTB1 Required for Substrate Specificity and Cullin-3 Ubiquitination

SSL-VQ: vector-quantized variational autoencoders for semi-supervised prediction of therapeutic targets across diverse diseases

MOTIVATION

Identifying effective therapeutic targets poses a challenge in drug discovery, especially for uncharacterized diseases without known therapeutic targets (e.g. rare diseases, intractable diseases).

RESULTS

This study presents a novel machine learning approach using multimodal vector-quantized variational autoencoders (VQ-VAEs) for predicting therapeutic target molecules across diseases. To address the lack of known therapeutic target-disease associations, we incorporate the information on uncharacterized diseases without known targets or uncharacterized proteins without known indications (applicable diseases) in the semi-supervised learning (SSL) framework. The method integrates disease-specific and protein perturbation profiles with genetic perturbations (e.g. gene knockdowns and gene overexpressions) at the transcriptome level. Cross-cell representation learning, facilitated by VQ-VAEs, was performed to extract informative features from protein perturbation profiles across diverse human cell types. Concurrently, cross-disease representation learning was performed, leveraging VQ-VAE, to extract informative features reflecting disease states from disease-specific profiles. The model's applicability to uncharacterized diseases or proteins is enhanced by considering the consistency between disease-specific and patient-specific signatures. The efficacy of the method is demonstrated across three practical scenarios for 79 diseases: target repositioning for target-disease pairs, new target prediction for uncharacterized diseases, and new indication prediction for uncharacterized proteins. This method is expected to be valuable for identifying therapeutic targets across various diseases.

AVAILABILITY AND IMPLEMENTATION

Code: github.com/YamanishiLab/SSL-VQ and Data: 10.5281/zenodo.14644837.

Familial Hyperkalemic Hypertension

The rare disease Familial Hyperkalemic Hypertension (FHHt) is caused by mutations in the genes encoding Cullin 3 (CUL3), Kelch-Like 3 (KLHL3), and two members of the With-No-Lysine [K] (WNK) kinase family, WNK1 and WNK4. In the kidney, these mutations ultimately cause hyperactivation of NCC along the renal distal convoluted tubule. Hypertension results from increased NaCl retention, and hyperkalemia by impaired K + secretion by downstream nephron segments. CUL3 and KLHL3 are now known to form a ubiquitin ligase complex that promotes proteasomal degradation of WNK kinases, which activate downstream kinases that phosphorylate and thus activate NCC. For CUL3, potent effects on the vasculature that contribute to the more severe hypertensive phenotype have also been identified. Here we outline the in vitro and in vivo studies that led to the discovery of the molecular pathways regulating NCC and vascular tone, and how FHHt-causing mutations disrupt these pathways. Potential mechanisms for variability in disease severity related to differential effects of each mutation on the kidney and vasculature are described, and other possible effects of the mutant proteins beyond the kidney and vasculature are explored. © 2024 American Physiological Society. Compr Physiol 14:5839-5874, 2024.

The 2023 Walter B. Cannon Award Lecture: Mechanisms Regulating Vascular Function and Blood Pressure by the PPARγ-RhoBTB1-CUL3 Pathway

Human genetic and clinical trial data suggest that peroxisome proliferator activated receptor γ (PPARγ), a nuclear receptor transcription factor plays an important role in the regulation of arterial blood pressure. The examination of a series of novel animal models, coupled with transcriptomic and proteomic analysis, has revealed that PPARγ and its target genes employ diverse pathways to regulate vascular function and blood pressure. In endothelium, PPARγ target genes promote an antioxidant state, stimulating both nitric oxide (NO) synthesis and bioavailability, essential components of endothelial-smooth muscle communication. In vascular smooth muscle, PPARγ induces the expression of a number of genes that promote an antiinflammatory state and tightly control the level of cGMP, thus promoting responsiveness to endothelial-derived NO. One of the PPARγ targets in smooth muscle, Rho related BTB domain containing 1 (RhoBTB1) acts as a substrate adaptor for proteins to be ubiquitinated by the E3 ubiquitin ligase Cullin-3 and targeted for proteasomal degradation. One of these proteins, phosphodiesterase 5 (PDE5) is a target of the Cullin-3/RhoBTB1 pathway. Phosphodiesterase 5 degrades cGMP to GMP and thus regulates the smooth muscle response to NO. Moreover, expression of RhoBTB1 under condition of RhoBTB1 deficiency reverses established arterial stiffness. In conclusion, the coordinated action of PPARγ in endothelium and smooth muscle is needed to maintain NO bioavailability and activity, is an essential regulator of vasodilator/vasoconstrictor balance, and regulates blood vessel structure and stiffness.