Batiste Laurent, Unzue Andrea, Dolbois Aymeric, Hassler Fabrice, Wang Xuan, Deerain Nicholas, Zhu Jian, Spiliotopoulos Dimitrios, Nevado Cristina, Caflisch Amedeo
Department of Biochemistry, University of Zurich, Winterthurerstrasse 190, CH-8057, Zürich, Switzerland.
Department of Chemistry, University of Zurich, Winterthurerstrasse 190, CH-8057, Zürich, Switzerland.
ACS Cent Sci. 2018 Feb 28;4(2):180-188. doi: 10.1021/acscentsci.7b00401. Epub 2018 Feb 7.
Expanding the chemical space and simultaneously ensuring synthetic accessibility is of upmost importance, not only for the discovery of effective binders for novel protein classes but, more importantly, for the development of compounds against hard-to-drug proteins. Here, we present AutoCouple, a de novo approach to computational ligand design focused on the diversity-oriented generation of chemical entities via virtual couplings. In a benchmark application, chemically diverse compounds with low-nanomolar potency for the CBP bromodomain and high selectivity against the BRD4(1) bromodomain were achieved by the synthesis of about 50 derivatives of the original fragment. The binding mode was confirmed by X-ray crystallography, target engagement in cells was demonstrated, and antiproliferative activity was showcased in three cancer cell lines. These results reveal AutoCouple as a useful in silico coupling method to expand the chemical space in hit optimization campaigns resulting in potent, selective, and cell permeable bromodomain ligands.
扩大化学空间并同时确保合成可及性至关重要,这不仅对于发现针对新型蛋白质类别的有效结合剂,更重要的是对于开发针对难成药蛋白质的化合物而言。在此,我们展示了AutoCouple,这是一种从头开始的计算配体设计方法,专注于通过虚拟偶联以多样性为导向生成化学实体。在一个基准应用中,通过合成约50种原始片段的衍生物,获得了对CBP溴结构域具有低纳摩尔效力且对BRD4(1)溴结构域具有高选择性的化学性质多样的化合物。通过X射线晶体学确认了结合模式,证明了在细胞中的靶点结合,并在三种癌细胞系中展示了抗增殖活性。这些结果表明AutoCouple是一种有用的计算机偶联方法,可在命中优化活动中扩大化学空间,从而产生强效、选择性和细胞可渗透的溴结构域配体。