柔性原子受体模型(FLARM)

Flexible Atom Receptor Model

柔性原子受体模型 (FlexibleAtomReceptorModel,FLARM)方法使用了改进的遗传算法 (IGA) ,比传统的受体模型方法具有更快的计算速度 ;FLARM受体模型中的原子空间坐标在遗传演化过程中是可变的 ,避免了不合适的起始位点对模型的影响 ;另外 ,FLARM用增加空原子权重的方法 ,可以生成不完全封闭的、允许有大段空区域的受体模型 ,这样的模型能更好地模拟实际受体的结构 ,并且容易和药效团模型找到对应关系 .我们用FLARM方法分别计算了甾类化合物体系的CBG蛋白亲和性和 1,1,3 三氧 2H ,4H 噻吩并 [3,4 e][1,2 ,4]噻二嗪衍生物 (TTD)体系的抗HIV 1活性 ,计算结果表明FLARM生成的虚拟受体模型对配体分子的活性具有较高的预测能力 ,在此虚拟受体模型的基础上还可以进一步分析虚拟受体分子与配体分子的相互作用机制 。

Improved Genetic Algorithm (IGA), which has a higher efficiency than the conventional ones, has been used for FLARM (Flexible Atom Receptor Model) algorithm. All the atoms in a FLARM receptor model are spacially moveable in the process of genetic evolving. This can avoid the bias of the initial coordinate setting. Void atom is specialty favored (a chance of 50%) in the atom selection to obtain open receptors model that allow large gaps. An open model may provide a better simulation of the real receptor and may rationally correspond to the pharmacophore model. Two data sets (one is the binding affinity to corticosteroid binding globulin of 21 steroids, and another is the anti-HIV-1 activities of 38 1,1,3-trioxo-2H,4H-thieno[3,4-e] [1, 2,4] thiadiazine derivatives) were investigated by using FLARM. The resulted receptor models showed high prediction ability (q(2) are 0.782 and 0.72 for die predicting sets of the two systems, respectively) that can be used to predict the activity of new drugs. Moreover, The explicit atom models can help to understand the mechanism of the interaction between ligands and receptors and even to preliminarily predict the active sites of the real receptors.