Computational blind challenges offer critical, unbiased opportunities to assess and accelerate scientific progress, as demonstrated by a breadth of breakthroughs over the past decade. We report the outcomes and key insights from an open science community blind challenge focused on computational methods in drug discovery, using lead optimization data from the AI-driven Structure-enabled Antiviral Platform Discovery Consortium's pan-coronavirus antiviral discovery program, in partnership with Polaris and the OpenADMET project. This collaborative initiative invited global participants from both academia and industry to develop and apply computational methods to predict the biochemical potency and crystallographic ligand poses of small molecules against key coronavirus targets, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and Middle East Respiratory Syndrome Coronavirus (MERS-CoV) main protease (Mpro), as well as multiple ADMET assay end points, using previously undisclosed comprehensive experimental drug discovery data sets as benchmarks. By evaluating submissions across multiple tasks and compounds, we established performance leaderboards and conducted meta-analyses to assess methodological strengths, common pitfalls, and areas for improvement. This analysis provides a foundation for best practices in real-world machine learning evaluation, grounded in community-driven benchmarking. We also highlight how next-generation platforms, such as Polaris, enable rigorous challenge design, embedded evaluation frameworks, and broad community engagement. This paper reports the collective findings of the challenge, offering a high-level overview of the data, evaluation infrastructure, and top-performing strategies. We further provide context and support for the accompanying papers authored by the challenge participants in this special issue, which explore individual approaches in greater depth. Together, these contributions aim to advance reproducible, trustworthy, and high-impact computational methods in drug discovery, and to explore best practices and pitfalls in future blind challenge design and execution, including planned initiatives for the OpenADMET project.
Tobacco (Nicotiana tabacum) is one of the most important commercial crops. It is an allotetraploid with two subgenomes derived from two wild diploid species: the maternal ancestor Nicotiana sylvestris and the paternal ancestor Nicotiana tomentosiformis. The functional duplication of homologous genes derived from both subgenomes often hinders phenotypic screening because a recessive mutation on one homeolog is complemented by the other. In this study, to establish a forward genetics platform for the genus Nicotiana, we constructed an ethyl methanesulfonate-induced N. sylvestris mutant library with high mutation frequency and generated an improved-quality reference genome of this species. We phenotypically screened the mutants with reduced nicotine content and selected two non-allelic mutants from the library. MutMap analysis using the reference genome, and subsequent molecular analyses, identified causal mutations in aspartate oxidase 2 (AO2) and ethylene responsible factor 199 genes. We genotypically screened N. tabacum mutants for AO2 and confirmed that nicotine biosynthesis was significantly affected in N. tabacum mutants with nonsense mutations in AO2s in both subgenomes, as observed in N. sylvestris. Thus, screening the N. sylvestris mutant library and gene identification using the reference genome are promising forward genetic approaches for gene discovery. This would allow researchers to improve N. tabacum by using reverse genetics and to elucidate the molecular mechanisms underlying traits. This study opens new avenues in Nicotiana functional genomics.
BackgroundBased on both physiological perspectives and observational findings, increasing cerebral glucose uptake appears to be a novel therapeutic strategy to preserve cognitive function in patients with Alzheimer's disease (AD). However, the inherent limitations of observational studies make it difficult to establish clear causality.ObjectiveTo evaluate the potential of cerebral glucose uptake as a novel therapeutic strategy for AD through a systematic investigation of its causal relationship with cognitive function.MethodsThe [18F] fluoro-2-deoxy-2-D-glucose positron emission tomography (FDG-PET) was used as an indicator of cerebral glucose uptake. Phenome-wide Mendelian randomization was performed to investigate the causal relationships between glucose uptake across 113 brain regions and 96 cognitive assessment scores using data from the Alzheimer's Disease Neuroimaging Initiative.ResultsIn the primary analysis, employing the inverse-variance weighted method, genetically predicted increases in cerebral glucose uptake exhibited a consistent trend toward beneficial changes in cognitive assessment scores across brain regions independent of brain volume. Subsequent sensitivity analyses, horizontal pleiotropy assessments and corrections for multiple testing demonstrated robust causal relationships between cerebral glucose uptakes and cognitive assessment scores, including the Alzheimer's Disease Assessment Scale and the Clinical Dementia Rating, across multiple brain regions.ConclusionsThis study provides genetic evidence suggesting causal relationship between cerebral glucose uptake and cognitive function. These findings indicate that FDG-PET images in specific brain regions may serve as a surrogate marker for cognitive function and support the potential of therapeutic strategies targeting cerebral glucose uptake to preserve cognitive function in patients with AD.
Basal plasmacytosis is a histopathological hallmark of ulcerative colitis (UC). However, the precise roles of plasma cells in UC pathogenesis remain unknown. In this study, we investigated the effects of a proteasome inhibitor, which depletes plasma cells, on chronic colitis progression in mice to clarify their contribution to disease pathogenesis. Chronic colitis was induced in female C57BL/6 mice by three cycles of ad libitum dextran sulfate sodium (DSS) feeding followed by distilled water (DW), each cycle lasting seven days. The proteasome inhibitor bortezomib was administered intravenously twice weekly for three weeks after the second DSS/DW cycle. Elevated plasma IgG and perinuclear anti-neutrophil cytoplasmic antibody (pANCA) levels, as well as infiltration of IgG-producing plasma cells into the colon, were observed after the second DSS/DW cycle in chronic DSS-induced colitis model mice. Plasma cells in the colon exhibited an immature CD19⁺CD138⁺ phenotype. Bortezomib significantly ameliorated colitis and intestinal fibrosis by reducing plasma IgG and pANCA levels and the number of IgG-producing plasma cells in the colon. In conclusion, IgG-producing plasma cells were involved in colitis pathogenesis, and their depletion ameliorated colitis. Thus, IgG-producing plasma cells are associated with colitis pathogenesis and potential therapeutic targets for UC.
