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揭示药物设计重要水域的奥秘:模拟与基于网格的方法。

Shedding Light on Important Waters for Drug Design: Simulations versus Grid-Based Methods.

机构信息

Galapagos SASU , 102 Avenue Gaston Roussel , 93230 Romainville , France.

Galapagos NV , Generaal De Wittelaan L11 A3 , 2800 Mechelen , Belgium.

出版信息

J Chem Inf Model. 2018 Mar 26;58(3):692-699. doi: 10.1021/acs.jcim.7b00642. Epub 2018 Mar 5.

Abstract

Water molecules play an important role in the association of drugs with their pharmaceutical targets. For this reason, calculating the energetic contribution of water is essential to make accurate predictions of compounds' affinity and selectivity. Water molecules can also modify the binding mode of compounds by forming water bridges, or clusters, that stabilize a particular orientation of the ligand. Several computational methods have been developed for solvent mapping, but few studies have attempted to compare them in a drug design context. In this paper, four commercially available solvent mapping tools (SZMAP, WaterFLAP, 3D-RISM, and WaterMap) are evaluated on three different protein targets. The methods were compared by looking at their ability to predict the structure-activity relations of lead compounds. All methods were found to be useful to some degree and to improve the predictions from docking alone. However, the only simulation-based approach tested, WaterMap, was found in some cases to be more accurate than grid-based methods.

摘要

水分子在药物与其药物靶点的结合中起着重要作用。因此,计算水的能量贡献对于准确预测化合物的亲和力和选择性至关重要。水分子还可以通过形成水桥或簇来改变化合物的结合模式,从而稳定配体的特定取向。已经开发了几种用于溶剂映射的计算方法,但很少有研究试图在药物设计背景下对它们进行比较。在本文中,我们评估了四种商业上可用的溶剂映射工具(SZMAP、WaterFLAP、3D-RISM 和 WaterMap)在三个不同的蛋白质靶标上的性能。通过观察它们预测先导化合物结构-活性关系的能力来比较这些方法。所有方法都在某种程度上被发现是有用的,并提高了仅从对接获得的预测。然而,在所测试的唯一基于模拟的方法 WaterMap 中,在某些情况下发现它比基于网格的方法更准确。

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