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使用计算方法鉴定用于癌症相关蛋白碳酸酐酶IX的潜在选择性荧光探针。

Identifying potential selective fluorescent probes for cancer-associated protein carbonic anhydrase IX using a computational approach.

作者信息

Kamstra Rhiannon L, Floriano Wely B

机构信息

Lakehead University, Department of Chemistry, Thunder Bay, ON P7B 5E1, Canada; Thunder Bay Regional Research Institute, Thunder Bay, ON P7A 7T1, Canada.

Lakehead University, Department of Chemistry, Thunder Bay, ON P7B 5E1, Canada; Thunder Bay Regional Research Institute, Thunder Bay, ON P7A 7T1, Canada.

出版信息

J Mol Graph Model. 2014 Nov;54:184-93. doi: 10.1016/j.jmgm.2014.10.010. Epub 2014 Oct 24.

DOI:10.1016/j.jmgm.2014.10.010
PMID:25459770
Abstract

Carbonic anhydrase IX (CAIX) is a biomarker for tumor hypoxia. Fluorescent inhibitors of CAIX have been used to study hypoxic tumor cell lines. However, these inhibitor-based fluorescent probes may have a therapeutic effect that is not appropriate for monitoring treatment efficacy. In the search for novel fluorescent probes that are not based on known inhibitors, a database of 20,860 fluorescent compounds was virtually screened against CAIX using hierarchical virtual ligand screening (HierVLS). The screening database contained 14,862 compounds tagged with the ATTO680 fluorophore plus an additional 5998 intrinsically fluorescent compounds. Overall ranking of compounds to identify hit molecular probe candidates utilized a principal component analysis (PCA) approach. Four potential binding sites, including the catalytic site, were identified within the structure of the protein and targeted for virtual screening. Available sequence information for 23 carbonic anhydrase isoforms was used to prioritize the four sites based on the estimated "uniqueness" of each site in CAIX relative to the other isoforms. A database of 32 known inhibitors and 478 decoy compounds was used to validate the methodology. A receiver-operating characteristic (ROC) analysis using the first principal component (PC1) as predictive score for the validation database yielded an area under the curve (AUC) of 0.92. AUC is interpreted as the probability that a binder will have a better score than a non-binder. The use of first component analysis of binding energies for multiple sites is a novel approach for hit selection. The very high prediction power for this approach increases confidence in the outcome from the fluorescent library screening. Ten of the top scoring candidates for isoform-selective putative binding sites are suggested for future testing as fluorescent molecular probe candidates.

摘要

碳酸酐酶IX(CAIX)是肿瘤缺氧的生物标志物。CAIX的荧光抑制剂已被用于研究缺氧肿瘤细胞系。然而,这些基于抑制剂的荧光探针可能具有治疗效果,不适用于监测治疗效果。在寻找不基于已知抑制剂的新型荧光探针时,使用分层虚拟配体筛选(HierVLS)对一个包含20,860种荧光化合物的数据库进行了针对CAIX的虚拟筛选。筛选数据库包含14,862种标记有ATTO680荧光团的化合物以及另外5,998种内在荧光化合物。利用主成分分析(PCA)方法对化合物进行总体排名,以确定命中的分子探针候选物。在蛋白质结构内确定了四个潜在的结合位点,包括催化位点,并将其作为虚拟筛选的目标。利用23种碳酸酐酶同工型的可用序列信息,根据每个位点相对于其他同工型在CAIX中的估计“独特性”对这四个位点进行优先级排序。使用一个包含32种已知抑制剂和478种诱饵化合物的数据库来验证该方法。使用第一主成分(PC1)作为验证数据库的预测分数进行的受试者工作特征(ROC)分析产生了曲线下面积(AUC)为0.92。AUC被解释为结合剂得分优于非结合剂的概率。对多个位点的结合能进行第一成分分析的方法是一种用于命中选择的新方法。这种方法的非常高的预测能力增加了对荧光文库筛选结果的信心。建议对异构体选择性推定结合位点的十个得分最高的候选物进行未来测试,作为荧光分子探针候选物。

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