Cruz-Monteagudo Maykel, Schürer Stephan, Tejera Eduardo, Pérez-Castillo Yunierkis, Medina-Franco José L, Sánchez-Rodríguez Aminael, Borges Fernanda
CIQUP/Departamento de Química e Bioquímica, Faculdade de Ciências, Universidade do Porto, Porto 4169-007, Portugal.
Department of Pharmacology, Miller School of Medicine and Center for Computational Science, University of Miami, Miami, FL 33136, USA.
Drug Discov Today. 2017 Jul;22(7):994-1007. doi: 10.1016/j.drudis.2017.02.004. Epub 2017 Mar 6.
Current advances in systems biology suggest a new change of paradigm reinforcing the holistic nature of the drug discovery process. According to the principles of systems biology, a simple drug perturbing a network of targets can trigger complex reactions. Therefore, it is possible to connect initial events with final outcomes and consequently prioritize those events, leading to a desired effect. Here, we introduce a new concept, 'Systemic Chemogenomics/Quantitative Structure-Activity Relationship (QSAR)'. To elaborate on the concept, relevant information surrounding it is addressed. The concept is challenged by implementing a systemic QSAR approach for phenotypic virtual screening (VS) of candidate ligands acting as neuroprotective agents in Parkinson's disease (PD). The results support the suitability of the approach for the phenotypic prioritization of drug candidates.
系统生物学的当前进展表明，一种新的范式转变正在强化药物发现过程的整体性。根据系统生物学原理，一种简单的干扰靶点网络的药物可能引发复杂反应。因此，将初始事件与最终结果联系起来并据此对这些事件进行优先级排序从而产生预期效果是可能的。在此，我们引入一个新概念，即“系统化学基因组学/定量构效关系（QSAR）”。为详细阐述这一概念，我们探讨了其相关信息。通过实施系统QSAR方法对作为帕金森病（PD）神经保护剂的候选配体进行表型虚拟筛选（VS），对该概念提出了挑战。结果支持了该方法用于药物候选体表型优先级排序的适用性。
