Chakravarti Suman K, Klopman Gilles
Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106, USA.
Bioorg Med Chem. 2008 Apr 1;16(7):4052-63. doi: 10.1016/j.bmc.2008.01.024. Epub 2008 Jan 19.
The primary functions of cancer chemotherapeutic agents are not only to inhibit the growth or kill the cancer cells, but to do so without eliciting unreasonable cytotoxic effects on the healthy cells and to withstand the ability of the cancer cells to develop resistance against it. This has unfortunately been proven so far to be a very difficult objective. In this perspective, the ability of small molecules (anti-tumor agents) to 'see' different cell types differently can be a key attribute. Thus the term 'differential cytotoxicity' is normally used to describe the drug's specificity. In the present paper, we have quantified differential cytotoxicity from a study of the chemicals tested in the National Cancer Institute's Developmental Therapeutics Program. The MULTICASE (Multiple Computer Automated Structure Evaluation) methodology was used to discover statistically significant structural fragments (biophores) related to the differential cytotoxicity of the compounds. We found that even small structural features often become important in this regard which is evident from the biophores that were found in structurally diverse chemicals. By utilizing the difference between the raw and normalized differential cytotoxicity indices, we found that the alpha,beta-unsaturated carbonyl group (O=C-C=CH(2)) is the major biophore associated with compounds with essentially parallel concentration profiles in the cell lines in question. These compounds have high non-normalized differential cytotoxicity but considerably low normalized differential cytotoxocity. The models developed were cross validated for their predictive ability.
癌症化疗药物的主要功能不仅是抑制癌细胞生长或杀死癌细胞，而且要在不对健康细胞产生不合理细胞毒性作用的情况下做到这一点，并抵御癌细胞产生耐药性的能力。不幸的是，到目前为止，这已被证明是一个非常困难的目标。从这个角度来看，小分子（抗肿瘤药物）以不同方式“识别”不同细胞类型的能力可能是一个关键特性。因此，术语“差异细胞毒性”通常用于描述药物的特异性。在本文中，我们通过对美国国立癌症研究所发展治疗项目中测试的化学物质的研究，对差异细胞毒性进行了量化。使用多案例（Multiple Computer Automated Structure Evaluation，多重计算机自动结构评估）方法来发现与化合物差异细胞毒性相关的具有统计学意义的结构片段（生物活性基团）。我们发现，即使是很小的结构特征在这方面往往也很重要，这从在结构多样的化学物质中发现的生物活性基团中可以明显看出。通过利用原始差异细胞毒性指数和归一化差异细胞毒性指数之间的差异，我们发现α,β-不饱和羰基（O=C-C=CH₂）是与所讨论的细胞系中具有基本平行浓度分布的化合物相关的主要生物活性基团。这些化合物具有高的非归一化差异细胞毒性，但归一化差异细胞毒性相当低。所开发的模型针对其预测能力进行了交叉验证。
