Division of Health and Biomedical Informatics, Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
The Center for Molecular Innovation and Drug Discovery, Northwestern University, Evanston, IL, USA.
Sci Rep. 2020 Jan 10;10(1):134. doi: 10.1038/s41598-019-56894-x.
Identifying and evaluating the right target are the most important factors in early drug discovery phase. Most studies focus on one protein ignoring the multiple splice-variant or protein-isoforms, which might contribute to unexpected therapeutic activity or adverse side effects. Here, we present computational analysis of cancer drug-target interactions affected by alternative splicing. By integrating information from publicly available databases, we curated 883 FDA approved or investigational stage small molecule cancer drugs that target 1,434 different genes, with an average of 5.22 protein isoforms per gene. Of these, 618 genes have ≥5 annotated protein-isoforms. By analyzing the interactions with binding pocket information, we found that 76% of drugs either miss a potential target isoform or target other isoforms with varied expression in multiple normal tissues. We present sequence and structure level alignments at isoform-level and make this information publicly available for all the curated drugs. Structure-level analysis showed ligand binding pocket architectures differences in size, shape and electrostatic parameters between isoforms. Our results emphasize how potentially important isoform-level interactions could be missed by solely focusing on the canonical isoform, and suggest that on- and off-target effects at isoform-level should be investigated to enhance the productivity of drug-discovery research.
在药物研发早期阶段，确定和评估正确的靶标是最重要的因素。大多数研究都集中在一种蛋白质上，而忽略了可能导致意外治疗效果或不良反应的多种剪接变异体或蛋白质同工型。在这里，我们提出了一种计算分析受选择性剪接影响的癌症药物-靶标相互作用的方法。通过整合来自公共数据库的信息，我们整理了 883 种已获美国食品和药物管理局批准或处于临床研究阶段的小分子癌症药物，这些药物针对 1434 种不同的基因，平均每个基因有 5.22 种蛋白质同工型。其中，618 个基因有≥5 个注释的蛋白质同工型。通过分析与结合口袋信息的相互作用，我们发现 76%的药物要么错过了潜在的靶标同工型，要么针对在多种正常组织中表达不同的其他同工型。我们在同工型水平上进行了序列和结构水平的比对，并将这些信息公开提供给所有整理好的药物。结构水平分析表明，同工型之间的配体结合口袋结构在大小、形状和静电参数方面存在差异。我们的研究结果强调了仅关注规范同工型可能会错过潜在重要的同工型相互作用，并表明应该在同工型水平上研究靶标和脱靶效应，以提高药物发现研究的生产力。
