Comprehensive predictions of target proteins based on protein-chemical interaction using virtual screening and experimental verifications.
Comprehensive predictions of target proteins based on protein-chemical interaction using virtual screening and experimental verifications.
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DOI：
10.1186/1472-6769-12-2
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发表时间：
2012-04-05
期刊：
影响因子：
--
通讯作者：
Sakakibara Y
中科院分区：
文献类型：
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作者：
Kobayashi H;Harada H;Nakamura M;Futamura Y;Ito A;Yoshida M;Iemura SI;Shin-Ya K;Doi T;Takahashi T;Natsume T;Imoto M;Sakakibara Y
鉴定生物活性化合物的目标蛋白对于阐明作用方式至关重要；然而，鉴定目标通常是困难的，主要是由于亲和层析、CBB染色和MS/MS分析的检测灵敏度较低。我们将我们的目标蛋白预测方法应用于对inedine的电子筛选和实验验证，该方法以一种未知的机制抑制了bclxl的抗凋亡功能。用该统计预测方法计算了182个候选靶蛋白与9个蛋白的结合，并通过与7个蛋白的体外结合验证了预测结果，这些蛋白在我们的细胞系统中得到了证实。因此，计算预测的准确率达到了40%，我们新发现了3个新的九结合蛋白。这项研究表明，我们提出的预测目标蛋白的方法在计算机筛选和实验验证中是有用的，并为识别小分子目标蛋白的策略提供了新的见解。
Identification of the target proteins of bioactive compounds is critical for elucidating the mode of action; however, target identification has been difficult in general, mostly due to the low sensitivity of detection using affinity chromatography followed by CBB staining and MS/MS analysis. We applied our protocol of predicting target proteins combining in silico screening and experimental verification for incednine, which inhibits the anti-apoptotic function of Bcl-xL by an unknown mechanism. One hundred eighty-two target protein candidates were computationally predicted to bind to incednine by the statistical prediction method, and the predictions were verified by in vitro binding of incednine to seven proteins, whose expression can be confirmed in our cell system. As a result, 40% accuracy of the computational predictions was achieved successfully, and we newly found 3 incednine-binding proteins. This study revealed that our proposed protocol of predicting target protein combining in silico screening and experimental verification is useful, and provides new insight into a strategy for identifying target proteins of small molecules.