Membrane proteins are attractive targets for drug discovery due to their crucial roles in various biological processes. Studying the binding poses of amphipathic molecules to membrane proteins is essential for understanding the functions of membrane proteins and docking simulations can facilitate the screening of protein–ligand complexes at low computational costs. However, identifying docking poses for a ligand in non-aqueous environments such as lipid bilayers can be challenging. To address this issue, we propose a new docking score called logP-corrected membrane docking (LoCoMock) score. To screen putative protein–ligand complexes embedded in a membrane, the LoCoMock score considers the affinity between a target ligand and the membrane. It combines the docking score of the protein–ligand complex with the logP of the target ligand. In demonstrations using several model ligands, the LoCoMock score screened more putative complexes than the conventional docking score. As extended docking, the LoCoMock score makes it possible to screen membrane proteins more effectively as drug targets than the conventional docking.

Graphical abstract

中文翻译：

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使用 LoCoMock 分数有效筛选脂质双层中的蛋白质-配体复合物

膜蛋白因其在各种生物过程中的关键作用而成为药物发现的有吸引力的目标。研究两亲性分子与膜蛋白的结合姿势对于理解膜蛋白的功能至关重要，对接模拟可以促进以低计算成本筛选蛋白质-配体复合物。然而，在非水环境（如脂质双层）中识别配体的对接姿势可能具有挑战性。为了解决这个问题，我们提出了一个新的对接分数，称为 log P-校正膜对接 (LoCoMock) 分数。为了筛选嵌入膜中的假定蛋白质-配体复合物，LoCoMock 评分考虑了目标配体与膜之间的亲和力。它将蛋白质-配体复合物的对接分数与目标配体的log P相结合。在使用多个模型配体的演示中，LoCoMock 评分筛选出比传统对接评分更多的假定复合物。作为扩展对接，LoCoMock 分数使得比传统对接更有效地筛选膜蛋白作为药物靶点成为可能。

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