CBP [cyclic adenosine monophosphate (cAMP) response element-binding protein (CREB)-binding protein] is one of the most researched proteins for its therapeutic function. Several studies have identified its vast functions and interactions with other transcription factors to initiate cellular signals of survival. In cancer and other diseases such as Alzheimer’s, Rubinstein-taybi syndrome, and inflammatory diseases, CBP has been implicated and hence an attractive target in drug design and development. In this review, we explore the various computational techniques that have been used in CBP research, furthermore we identified computational gaps that could be explored to facilitate the development of highly therapeutic CBP inhibitors.

CBP [环状单磷酸腺苷（cAMP）反应元件结合蛋白（CREB）结合蛋白]是治疗功能最受研究的蛋白之一。几项研究已经确定了其广泛的功能以及与其他转录因子的相互作用以启动细胞存活信号。在癌症和其他疾病（例如阿尔茨海默氏病，鲁宾斯坦-泰比综合征和炎症性疾病）中，CBP受到牵连，因此成为药物设计和开发中有吸引力的目标。在这篇综述中，我们探索了CBP研究中使用的各种计算技术，此外，我们确定了可以探索的计算缺口，以促进高度治疗性CBP抑制剂的开发。