Discovery of Small Molecule Renal Outer Medullary Potassium (ROMK) Channel Inhibitors: A Brief History of Medicinal Chemistry Approaches To Develop Novel Diuretic Therapeutics

The role of uromodulin in cardiovascular disease: a review

Uromodulin, also referred to as Tamm Horsfall protein (THP), is a renal protein exclusively synthesized by the kidneys and represents the predominant urinary protein under normal physiological conditions. It assumes a pivotal role within the renal system, contributing not only to ion transport and immune modulation but also serving as a critical factor in the prevention of urinary tract infections and kidney stone formation. Emerging evidence indicates that uromodulin may serve as a potential biomarker extending beyond renal function. Recent clinical investigations and Mendelian randomization studies have unveiled a discernible association between urinary regulatory protein levels and cardiovascular events and mortality. This review primarily delineates the intricate relationship between uromodulin and cardiovascular disease, elucidates its predictive utility as a novel biomarker for cardiovascular events, and delves into its involvement in various physiological and pathophysiological facets of the cardiovascular system, incorporating recent advancements in corresponding genetics.

Discovery of BMS-986308: A Renal Outer Medullary Potassium Channel Inhibitor for the Treatment of Heart Failure

Recent literature reports highlight the importance of the renal outer medullary potassium (ROMK) channel in renal sodium and potassium homeostasis and emphasize the potential impact that ROMK inhibitors could have as a novel mechanism diuretic in heart failure patients. A series of piperazine-based ROMK inhibitors were designed and optimized to achieve excellent ROMK potency, hERG selectivity, and ADME properties, which led to the identification of compound 28 (BMS-986308). BMS-986308 demonstrated efficacy in the volume-loaded rat diuresis model as well as promising in vitro and in vivo profiles and was therefore advanced to clinical development.

Modern trends in diuretics development

Diuretics are the first-line therapy for widespread cardiovascular and non-cardiovascular diseases. Traditional diuretics are commonly prescribed for treatment in patients with hypertension, edema and heart failure, as well as with a number of kidney problems. They are diseases with high mortality, and the number of patients suffering from heart and kidney diseases is increasing year by year. The use of several classes of diuretics currently available for clinical use exhibits an overall favorable risk/benefit balance. However, they are not devoid of side effects. Hence, pharmaceutical researchers have been making efforts to develop new drugs with a better pharmacological profile. High-throughput screening, progress in protein structure analysis and modern methods of chemical modification have opened good possibilities for identification of new promising agents for preclinical and clinical testing. In this review, we provide an overview of the medicinal chemistry approaches toward the development of small molecule compounds showing diuretic activity that have been discovered over the past decade and are interesting drug candidates. We have discussed promising natriuretics/aquaretics/osmotic diuretics from such classes as: vasopressin receptor antagonists, SGLT2 inhibitors, urea transporters inhibitors, aquaporin antagonists, adenosine receptor antagonists, natriuretic peptide receptor agonists, ROMK inhibitors, WNK-SPAK inhibitors, and pendrin inhibitors.

Complementary computational and experimental evaluation of missense variants in the ROMK potassium channel

The renal outer medullary potassium (ROMK) channel is essential for potassium transport in the kidney, and its dysfunction is associated with a salt-wasting disorder known as Bartter syndrome. Despite its physiological significance, we lack a mechanistic understanding of the molecular defects in ROMK underlying most Bartter syndrome-associated mutations. To this end, we employed a ROMK-dependent yeast growth assay and tested single amino acid variants selected by a series of computational tools representative of different approaches to predict each variants’ pathogenicity. In one approach, we used in silico saturation mutagenesis, i.e. the scanning of all possible single amino acid substitutions at all sequence positions to estimate their impact on function, and then employed a new machine learning classifier known as Rhapsody. We also used two additional tools, EVmutation and Polyphen-2, which permitted us to make consensus predictions on the pathogenicity of single amino acid variants in ROMK. Experimental tests performed for selected mutants in different classes validated the vast majority of our predictions and provided insights into variants implicated in ROMK dysfunction. On a broader scope, our analysis suggests that consolidation of data from complementary computational approaches provides an improved and facile method to predict the severity of an amino acid substitution and may help accelerate the identification of disease-causing mutations in any protein.

As the number of sequenced human genomes rises, a major challenge is to identify which single amino acid variations in a protein affect function and predispose individuals to disease. While predictive algorithms are available for this purpose, a comparative analysis of recently developed algorithms has not been adequately performed, nor is it clear whether combining algorithms would improve predictive power. To this end, we compared the efficacy of three publicly available algorithms and applied the results to Bartter syndrome, a human disease for which numerous poorly-characterized single amino acid variants have been identified and for which there is no cure. In silico saturation mutagenesis, i.e., the computational prediction of pathogenesis for every possible amino acid substitution, allowed us to experimentally test predictions by measuring the activity of an ion channel linked to Bartter syndrome. Based on data from blinded experiments, we discovered that Rhapsody and EVmutation successfully predicted deleterious mutations. Moreover, Rhapsody—which takes into account evolutionary as well as structural and dynamic considerations—predicted that >90% of known Bartter syndrome mutations are deleterious. Overall, our data will aid investigators who wish to test single amino acid variants in any protein and aid biomedical researchers who wish to develop hypotheses on the potential severity of genetic variants uncovered from genome databases.