Small-molecule inhibitors of ferrochelatase are antiangiogenic agents

Activity of the heme synthesis enzyme ferrochelatase (FECH) is implicated in multiple diseases. In particular, it is a mediator of neovascularization in the eye and thus an appealing therapeutic target for preventing blindness. However, no drug-like direct FECH inhibitors are known. Here, we set out to identify small-molecule inhibitors of FECH as potential therapeutic leads using a high-throughput screening approach to identify potent inhibitors of FECH activity. A structure-activity relationship study of a class of triazolopyrimidinone hits yielded drug-like FECH inhibitors. These compounds inhibit FECH in cells, bind the active site in cocrystal structures, and are antiangiogenic in multiple in vitro assays. One of these promising compounds was antiangiogenic in vivo in a mouse model of choroidal neovascularization. This foundational work may be the basis for new therapeutic agents to combat not only ocular neovascularization but also other diseases characterized by FECH activity

CAGI, the critical assessment of genome interpretation, establishes progress and prospects for computational genetic variant interpretation methods

Background: The Critical Assessment of Genome Interpretation (CAGI) aims to advance the state-of-the-art for computational prediction of genetic variant impact, particularly where relevant to disease. The five complete editions of the CAGI community experiment comprised 50 challenges, in which participants made blind predictions of phenotypes from genetic data, and these were evaluated by independent assessors. Results: Performance was particularly strong for clinical pathogenic variants, including some difficult-to-diagnose cases, and extends to interpretation of cancer-related variants. Missense variant interpretation methods were able to estimate biochemical effects with increasing accuracy. Assessment of methods for regulatory variants and complex trait disease risk was less definitive and indicates performance potentially suitable for auxiliary use in the clinic. Conclusions: Results show that while current methods are imperfect, they have major utility for research and clinical applications. Emerging methods and increasingly large, robust datasets for training and assessment promise further progress ahead