Drug discovery historically starts with an established function, either that of compounds or proteins. This can hamper discovery of novel therapeutics. As structure determines function, we hypothesized that unique 3D protein structures constitute primary data that can inform novel discovery. Using a computationally intensive physics-based analytical platform operating at supercomputing speeds, we probed a high-resolution protein X-ray crystallographic library developed by us. For each of the eight identified novel 3D structures, we analyzed binding of sixty million compounds. Top-ranking compounds were acquired and screened for efficacy against breast, prostate, colon, or lung cancer, and for toxicity on normal human bone marrow stem cells, both using eight-day colony formation assays. Effective and non-toxic compounds segregated to two pockets. One compound, Dxr2-017, exhibited selective anti-melanoma activity in the NCI-60 cell line screen. In eight-day assays, Dxr2-017 had an IC50 of 12 nM against melanoma cells, while concentrations over 2100-fold higher had minimal stem cell toxicity. Dxr2-017 induced anoikis, a unique form of programmed cell death in need of targeted therapeutics. Our findings demonstrate proof-of-concept that protein structures represent high-value primary data to support the discovery of novel acting therapeutics. This approach is widely applicable.
药物研发历来始于既定的功能研究，无论是针对化合物还是蛋白质。这种方法可能阻碍新型治疗药物的发现。由于结构决定功能，我们假设独特的蛋白质三维结构可作为指导新药发现的一级数据源。通过运用基于超级计算速度的密集型物理计算分析平台，我们对自主研发的高分辨率蛋白质X射线晶体学数据库进行了系统性筛选。针对识别出的八种新型三维结构，我们分别分析了六千万种化合物的结合特性。通过八天集落形成实验，对筛选出的高评分化合物进行了抗乳腺癌、前列腺癌、结肠癌或肺癌的药效评估，并检测了其对正常人骨髓干细胞的毒性。有效且无毒的化合物主要富集于两个结合口袋。其中化合物Dxr2-017在国家癌症研究所60株细胞系筛选中显示出选择性抗黑色素瘤活性。在八天实验中，该化合物对黑色素瘤细胞的半数抑制浓度为12 nM，而浓度提升2100倍以上时仍对干细胞表现出极低毒性。Dxr2-017能诱导失巢凋亡——这是一种急需靶向治疗的特殊程序性细胞死亡形式。我们的研究证实了蛋白质结构作为高价值一级数据支持新型作用机制药物研发的概念验证。该方法具有广泛适用性。
Protein Structure Inspired Discovery of a Novel Inducer of Anoikis in Human Melanoma
肿瘤(癌症)患者之家