The understudied members of the druggable proteomes offer promising prospects for drug discovery efforts. While large-scale initiatives have generated valuable functional information on understudied members of the druggable gene families, translating this information into actionable knowledge for drug discovery requires specialized informatics tools and resources. Here, we review the unique informatics challenges and advances in annotating understudied members of the druggable proteome. We demonstrate the application of statistical evolutionary inference tools, knowledge graph mining approaches, and protein language models in illuminating understudied protein kinases, pseudokinases, and ion channels.

中文翻译：

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阐明可药物蛋白质组的信息挑战和进展

可药物蛋白质组中未被充分研究的成员为药物发现工作提供了充满希望的前景。虽然大规模举措已经产生了有关可成药基因家族中尚未研究的成员的宝贵功能信息，但将这些信息转化为药物发现的可操作知识需要专门的信息学工具和资源。在这里，我们回顾了注释可成药蛋白质组中未被充分研究的成员的独特信息学挑战和进展。我们展示了统计进化推理工具、知识图挖掘方法和蛋白质语言模型在阐明尚未研究的蛋白激酶、假激酶和离子通道方面的应用。