Vedani Angelo, Dobler Max
Biographics Laboratory 3R, Friedensgasse 35, CH-4056 Basel, Switzerland.
J Med Chem. 2002 May 23;45(11):2139-49. doi: 10.1021/jm011005p.
In this journal we recently reported the development and the validation of a four-dimensional (4D)-QSAR (quantitative structure-activity relationships) concept, allowing for multiple conformation, orientation, and protonation state representation of ligand molecules. While this approach significantly reduces the bias with selecting a bioactive conformer, orientation, or protonation state, it still requires a "sophisticated guess" about manifestation and magnitude of the associated local induced fit-the adaptation of the receptor binding pocket to the individual ligand topology. We have therefore extended our concept (software Quasar) by an additional degree of freedom--the fifth dimension--allowing for a multiple representation of the topology of the quasi-atomistic receptor surrogate. While this entity may be generated using up to six different induced-fit protocols, we demonstrate that the simulated evolution converges to a single model and that 5D-QSAR--due to the fact that model selection may vary throughout the entire simulation--yields less biased results than 4D-QSAR where only a single induced- fit model can be evaluated at a time. Using two bioregulators (the neurokinin-1 receptor and the aryl hydrocarbon receptor), we compare the results obtained with 4D- and 5D-QSAR. The NK-1 receptor system (represented by a total of 65 antagonist molecules) converges at a cross-validated r2 of 0.870 and a predictive r2 of 0.837; the corresponding values for the Ah receptor system (represented by a total of 131 dibenzodioxins, dibenzofurans, biphenyls, and polyaromatic hydrocarbons) are 0.838 and 0.832, respectively. The results indicate that the formal investment of additional computer time is well-returned both in quantitative and in qualitative values: less-biased boundary conditions, healthier (i.e., less inbred) model populations, and more accurate predictions of new compounds.
在本期刊中，我们最近报道了一种四维（4D）-定量构效关系（QSAR）概念的开发与验证，该概念允许对配体分子进行多种构象、取向和质子化状态的表示。虽然这种方法在选择生物活性构象、取向或质子化状态时显著减少了偏差，但它仍然需要对相关局部诱导契合（受体结合口袋对单个配体拓扑结构的适应性）的表现形式和程度进行“复杂的猜测”。因此，我们通过增加一个自由度——第五维，扩展了我们的概念（软件Quasar），允许对准原子受体替代物的拓扑结构进行多种表示。虽然这个实体可以使用多达六种不同的诱导契合协议生成，但我们证明模拟进化收敛到一个单一模型，并且5D-QSAR——由于在整个模拟过程中模型选择可能会有所不同——与一次只能评估一个诱导契合模型的4D-QSAR相比，产生的偏差结果更少。使用两种生物调节剂（神经激肽-1受体和芳烃受体），我们比较了4D-和5D-QSAR获得的结果。NK-1受体系统（由总共65种拮抗剂分子表示）在交叉验证的r2为0.870和预测r2为0.837时收敛；Ah受体系统（由总共131种二苯并二恶英、二苯并呋喃、联苯和多环芳烃表示）的相应值分别为0.838和0.832。结果表明，额外计算机时间的正式投入在定量和定性价值方面都得到了很好的回报：偏差更小的边界条件、更健康（即近亲繁殖程度更低）的模型群体以及对新化合物更准确的预测。
