离子通道是一类重要的药物靶点。由于靶向离子通道小分子药物特异性不够的问题很难解决，制药界将目光投向生物类药物，而现有几种离子通道的生物类药物均是毒素多肽。保守估计自然中存在17万种有毒生物、4000万种毒素多肽。随着毒腺的转录组和蛋白质组研究发现越来越多毒素多肽，迫切需要开发在毒素组水平高通量鉴定毒素功能的方法。近期我们结合“基于自分泌的筛选”和“基于邻位检测的报告系统”完成了从天然毒素多肽基因文库中筛选针对钾离子通道Kv1.3的毒素以及通过“组合多肽库”改造毒素的概念验证性试验。通过本项目，我们将完善和优化该技术，包括构建包含所有已知毒素基因的慢病毒文库以及建立正、负筛选方法用于毒素特异性的改造等，最终实现技术定型，为其推广和应用打下基础。该技术有望成为生物多样性开发利用以及离子通道药物开发的一个强大而且容易使用的工具。

Ion channels are an attractive class of drug targets. Due to the challenge to find subtype selective small molecules, the pharmaceutical and biotechnology industry increasingly shift their attention to the biologics. All of the current ion channels targeting biologic drugs are venom derived peptides. It’s estimated that there are about 170,000 venomous animals and 40 million venom peptides in nature. As transcriptomics and proteomics studies of venom glands reveal more venom peptides, there is urgent need of high throughput method to characterize venom peptides’ function and their targets in venomics level. Recently we had completed proof-of-concept experiments to identify new Kv1.3 targeting venom peptides from natural venom peptide lentiviral library and optimize anemone venom peptide ShK for high selectivity using “autocrine based selection” and “proximity based assay”. In the current project, we want to further develop the technology so that it will become mature enough for one of ordinary skill in the art to use. We will also construct a natural venom peptide lentiviral library that covers every known cysteine knot venom peptide and develop screening/counter-screening method for optimization of venom peptide selectivity. This emerging approach can solve many of the problems that hamper current research on venoms and should enable discovery of many new venoms and ultimately new medicines.