Department of Cancer Biology, Mayo Clinic, Jacksonville, FL, 32224, United States.
Department of Neuroscience, Mayo Clinic, Jacksonville, FL, 32224, United States.
Curr Drug Discov Technol. 2021;18(3):365-378. doi: 10.2174/1570163817666200311114819.
Diseases are often caused by mutant proteins. Many drugs have limited effectiveness and/or toxic side effects because of a failure to selectively target the disease-causing mutant variant, rather than the functional wild type protein. Otherwise, the drugs may even target different proteins with similar structural features. Designing drugs that successfully target mutant proteins selectively represents a major challenge. Decades of cancer research have led to an abundance of potential therapeutic targets, often touted to be "master regulators". For many of these proteins, there are no FDA-approved drugs available; for others, off-target effects result in dose-limiting toxicity. Cancer-related proteins are an excellent medium to carry the story of mutant-specific targeting, as the disease is both initiated and sustained by mutant proteins; furthermore, current chemotherapies generally fail at adequate selective distinction. This review discusses some of the challenges associated with selective targeting from a structural biology perspective, as well as some of the developments in algorithm approach and computational workflow that can be applied to address those issues. One of the most widely researched proteins in cancer biology is p53, a tumor suppressor. Here, p53 is discussed as a specific example of a challenging target, with contemporary drugs and methodologies used as examples of burgeoning successes. The oncogene KRAS, which has been described as "undruggable", is another extensively investigated protein in cancer biology. This review also examines KRAS to exemplify progress made towards selective targeting of diseasecausing mutant proteins. Finally, possible future directions relevant to the topic are discussed.
疾病通常是由突变蛋白引起的。许多药物由于不能选择性地针对致病的突变变体，而不是功能正常的野生型蛋白，因此效果有限，或者具有毒性副作用。否则，这些药物甚至可能针对具有相似结构特征的不同蛋白。设计能够成功选择性地针对突变蛋白的药物是一个主要挑战。几十年来的癌症研究产生了大量潜在的治疗靶点，这些靶点通常被吹捧为“主调控因子”。对于许多这些蛋白，没有获得 FDA 批准的药物；对于其他蛋白，脱靶效应导致剂量限制毒性。癌症相关蛋白是携带突变体特异性靶向故事的绝佳载体，因为该疾病是由突变蛋白引发和维持的；此外，目前的化疗药物通常无法进行充分的选择性区分。本文从结构生物学的角度讨论了选择性靶向的一些挑战，以及一些算法方法和计算工作流程的发展，这些方法和流程可以应用于解决这些问题。在癌症生物学中，研究最广泛的蛋白之一是 p53，一种肿瘤抑制因子。在这里，p53 被讨论为一个具有挑战性的目标的具体例子，同时也讨论了当代药物和方法学的应用，这些应用是新兴成功的例子。致癌基因 KRAS 曾被描述为“不可成药”，是癌症生物学中另一个广泛研究的蛋白。本文还研究了 KRAS，以说明在针对致病突变蛋白的选择性靶向方面取得的进展。最后，讨论了与该主题相关的可能的未来方向。
