A Chemocentric Approach to the Identification of Cancer Targets

A novel chemocentric approach to identifying cancer-relevant targets is introduced. Starting with a large chemical collection, the strategy uses the list of small molecule hits arising from a differential cytotoxicity screening on tumor HCT116 and normal MRC-5 cell lines to identify proteins associated with cancer emerging from a differential virtual target profiling of the most selective compounds detected in both cell lines. It is shown that this smart combination of differential in vitro and in silico screenings (DIVISS) is capable of detecting a list of proteins that are already well accepted cancer drug targets, while complementing it with additional proteins that, targeted selectively or in combination with others, could lead to synergistic benefits for cancer therapeutics. The complete list of 115 proteins identified as being hit uniquely by compounds showing selective antiproliferative effects for tumor cell lines is provided.本文介绍了一种用于识别癌症相关靶点的新型化学聚焦型（chemocentric）研究方法。该方法以大型化学化合物库为起始，先针对肿瘤细胞系HCT116与正常细胞系MRC-5开展差异细胞毒性筛选，得到小分子命中化合物列表；随后对两种细胞系中筛选获得的选择性最强的化合物进行差异虚拟靶点谱分析，以此识别与癌症相关的蛋白质。研究表明，这种体外（in vitro）差异筛选与虚拟（in silico）筛选的智能联用策略（differential in vitro and in silico screenings，缩写DIVISS），可检出一系列已被广泛认可的癌症药物靶点蛋白，同时还能补充得到额外的潜在蛋白质靶点——若对这些靶点进行选择性靶向或联合其他靶点进行干预，有望为癌症治疗带来协同获益。本文同时提供了115种蛋白质的完整列表，这些蛋白质仅被对肿瘤细胞系具有选择性抗增殖活性的化合物所命中。