Toschi N
Department of Behavioral Neuroendocrinology, MaxPlanck Institute of Psychiatry, Kraepelinstrasse 2-10, Munich, D-80804, Germany.
Methods. 2000 Nov;22(3):261-9. doi: 10.1006/meth.2000.1078.
Antisense targeting, an innovative technology based on preventing biosynthesis through sequence-specific hybridization of mRNA to synthetic oligodeoxynucleotides (ODNs), is used to selectively and transiently downregulate the expression of any gene product. Its potential applications are both investigative (neurobiology and related disciplines) and therapeutic (oncology, virology, genetic diseases), and several antisense-based drugs are currently undergoing clinical trials. However, the reported efficiencies vary and there is still a lack of clarity in the underlying mechanisms of action. A critical factor of antisense efficiency is the issue of target site selection, as both mRNA and ODN molecules exhibit a significant amount of highly heterogeneous self-structure and the region selected for targeting may well be sterically or energetically inaccessible. Because of the prohibitively large chain length, mRNA structural information is not accessible by X-ray crystallography or NMR, making a modeling approach indispensable. I outline how the latest molecular modeling techniques can be employed to establish the secondary (2D) and tertiary (3D) structures into which a given mRNA folds during and after transcription. The aim should be to integrate 2D prediction results achieved by (a) free-energy minimization, (b) kinetic folding simulations, (c) iterative population breeding by genetic algorithms, and (d) phylogenetic comparison techniques. These results can form the input of a 3D structure prediction paradigm based on constraint-satisfying programming, governed by experimental molecular mechanical constraints, and refined by molecular dynamics simulations. Finally, the automated docking (by simulated annealing) of ODN molecules to the mRNA structure can provide information about the accessibility of target mRNA regions for hybridization. To date, the great majority of studies that employ antisense as a tool select their target sequences more or less randomly. Although the wealth of molecular interactions that take place within a cell makes complete predictability unrealistic, the kind of information that can be extracted from such techniques is of relevance to every application of antisense technology, both investigative and therapeutic.
反义靶向技术是一项基于通过mRNA与合成寡脱氧核苷酸（ODN）进行序列特异性杂交来阻止生物合成的创新技术，用于选择性和短暂地下调任何基因产物的表达。其潜在应用既包括研究性的（神经生物学及相关学科），也包括治疗性的（肿瘤学、病毒学、遗传性疾病），目前有几种基于反义的药物正在进行临床试验。然而，报道的效率各不相同，其作用的潜在机制仍不明确。反义效率的一个关键因素是靶位点选择问题，因为mRNA和ODN分子都表现出大量高度异质的自身结构，所选的靶向区域在空间上或能量上可能难以接近。由于链长过长，无法通过X射线晶体学或核磁共振获得mRNA的结构信息，因此建模方法必不可少。我概述了如何运用最新的分子建模技术来确定给定mRNA在转录期间及转录后折叠形成的二级（2D）和三级（3D）结构。目标应该是整合通过以下方法获得的2D预测结果：（a）自由能最小化、（b）动力学折叠模拟、（c）遗传算法的迭代群体繁殖以及（d）系统发育比较技术。这些结果可以作为基于约束满足编程的3D结构预测范式的输入，该范式受实验分子力学约束的支配，并通过分子动力学模拟进行优化。最后，ODN分子与mRNA结构的自动对接（通过模拟退火）可以提供有关靶mRNA区域杂交可及性的信息。迄今为止，绝大多数将反义技术用作工具的研究或多或少都是随机选择其靶序列。尽管细胞内发生的大量分子相互作用使得完全可预测性不切实际，但从这些技术中提取的信息类型与反义技术的每一项应用都相关，无论是研究性还是治疗性应用。
