Vedani Angelo, Dobler Max, Lill Markus A
Biographics Laboratory 3R, Friedensgasse 35, CH-4056 Basel, Switzerland.
Toxicol Appl Pharmacol. 2005 Sep 1;207(2 Suppl):398-407. doi: 10.1016/j.taap.2005.01.055.
While the computer-assisted discovery and optimization of drug candidates based on the known three-dimensional structure of the macromolecular target (structure-based design) or a binding-site surrogate (receptor modeling) is doubtless one of the more potent approaches in rational drug design, the simulation and quantification of side effects triggered by drugs and chemicals are still in their infancy. Major obstacles include the often not available 3D structure of the molecular target, the low specificity of the involved bioregulators and the identification of the controlling metabolic pathways. In the recent past, our laboratory has explored concepts allowing to simulate receptor-mediated toxic phenomena by developing algorithms, allowing to construct realistic 3D binding-site surrogates of receptors known or assumed triggering adverse effects and validating them against large batches of molecular data. The underlying technology (software Quasar and Raptor, respectively) specifically allows for induced fit, solvation phenomena and entropic effects. It has been applied to various systems both of pharmacological and toxicological interest including the neurokinin-1, chemokine-3, bradykinin B(2), steroid, 5 HT(2A), aryl hydrocarbon, estrogen and androgen receptor, respectively. In this account, we describe the design of a virtual laboratory allowing for a reliable estimation of harmful effects triggered by drugs, chemicals and their metabolites in silico. In the recent past, the Biographics Laboratory 3R has compiled a 3D database including the surrogates of three major receptor systems known to mediate adverse effects (the aryl hydrocarbon, the estrogen and the androgen receptor, respectively) and validated them against a total of 345 compounds (drugs, chemicals, toxins) using multidimensional QSAR technologies. Within this pilot project, we could demonstrate that our virtual laboratory is able to both recognize toxic compounds substantially different from those used in the training set as well as to classify harmless compounds as being nontoxic. This suggests that our approach may be used for the prediction of adverse effects of drug molecules and chemicals. It is the aim to provide cost-covering access to this technology--particularly to universities, hospitals and regulatory bodies--as it bears a significant potential to recognize hazardous compounds early in the development process and hence improve resource and waste management as well as reduce animal testing. The Biographics Laboratory 3R is a non-profit-oriented organization aimed at reducing animal experimentation in the biomedical sciences by computational approaches (cf. http://www.biograf.ch).
虽然基于大分子靶标的已知三维结构（基于结构的设计）或结合位点替代物（受体建模）进行计算机辅助的药物候选物发现和优化无疑是合理药物设计中更有效的方法之一，但药物和化学物质引发的副作用的模拟和量化仍处于起步阶段。主要障碍包括分子靶标的三维结构往往难以获得、所涉及的生物调节剂特异性较低以及控制代谢途径的识别。最近，我们实验室探索了一些概念，通过开发算法来模拟受体介导的毒性现象，这些算法能够构建已知或假定引发不良反应的受体的逼真三维结合位点替代物，并根据大量分子数据对其进行验证。底层技术（分别为软件Quasar和Raptor）特别允许诱导契合、溶剂化现象和熵效应。它已应用于各种具有药理学和毒理学意义的系统，分别包括神经激肽-1、趋化因子-3、缓激肽B(2)、类固醇、5 HT(2A)、芳烃、雌激素和雄激素受体。在本报告中，我们描述了一个虚拟实验室的设计，该实验室能够在计算机上可靠地估计药物、化学物质及其代谢物引发的有害影响。最近，生物信息学实验室3R编制了一个三维数据库，其中包括已知介导不良反应的三种主要受体系统的替代物（分别为芳烃、雌激素和雄激素受体），并使用多维QSAR技术针对总共345种化合物（药物、化学物质、毒素）对其进行了验证。在这个试点项目中，我们能够证明我们的虚拟实验室既能识别与训练集中使用的化合物有很大不同的有毒化合物，也能将无害化合物归类为无毒。这表明我们的方法可用于预测药物分子和化学物质的不良反应。目标是为这项技术提供成本覆盖的使用途径，特别是提供给大学、医院和监管机构，因为它在开发过程早期识别有害化合物方面具有巨大潜力，从而改善资源和废物管理以及减少动物试验。生物信息学实验室3R是一个非营利性组织，旨在通过计算方法减少生物医学科学中的动物实验（参见http://www.biograf.ch）。
