利用计算方法进行药物载体的预测

P. Mistry, Anna Palczewska, D. Neagu, P. Trundle
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引用次数: 0

摘要

药物载体是帮助药物通过生物体的化学载体。虽然它们不具有内在功效,但它们被设计为达到理想的特性,包括改善药物的渗透性和/或溶解度,将药物靶向到特定部位或降低药物的毒性。所有这些都是在不影响药物功效的情况下理想地实现的。虽然大多数药物载体研究都集中在药物的溶解度和渗透性问题上,但在使用载体降低毒性方面已经取得了重大进展。实现这一目标可以更安全、更有效地使用一种强效药物来治疗癌症等疾病。从分子的角度来看,药物通过与细胞大分子的相互作用激活或灭活生化途径,从而产生毒性。对于新开发的药物,这些途径并不总是被清楚地理解,但毒性终点仍然需要作为药物注册的一部分。了解哪些载体可以用来改善新开发药物的有害毒性对制药业来说是非常可取的。在本文中,我们展示了使用不同的分类器作为选择最适合避免药物的毒性作用的载体的手段,当没有关于药物特性的其他信息是已知的。通过分析从发育治疗项目(DTP)获得的数据,我们能够建立药物毒性和所用载体之间的联系。我们证明了基于药物选择的相似性可以对合适的载体进行分类和选择。
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Using computational methods for the prediction of drug vehicles
Drug vehicles are chemical carriers that aid a drug's passage through an organism. Whilst they possess no intrinsic efficacy they are designed to achieve desirable characteristics which can include improving a drug's permeability and or solubility, targeting a drug to a specific site or reducing a drug's toxicity. All of which are ideally achieved without compromising the efficacy of the drug. Whilst the majority of drug vehicle research is focused on the solubility and permeability issues of a drug, significant progress has been made on using vehicles for toxicity reduction. Achieving this can enable safer and more effective use of a potent drug against diseases such as cancer. From a molecular perspective, drugs activate or deactivate biochemical pathways through interactions with cellular macromolecules resulting in toxicity. For newly developed drugs such pathways are not always clearly understood but toxicity endpoints are still required as part of a drug's registration. An understanding of which vehicles could be used to ameliorate the unwanted toxicities of newly developed drugs would be highly desirable to the pharmaceutical industry. In this paper we demonstrate the use of different classifiers as a means to select vehicles best suited to avert a drug's toxic effects when no other information about a drug's characteristics is known. Through analysis of data acquired from the Developmental Therapeutics Program (DTP) we are able to establish a link between a drug's toxicity and vehicle used. We demonstrate that classification and selection of the appropriate vehicle can be made based on the similarity of drug choice.
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