Center for Computational Biology, The University of Kansas, 2030 Becker Drive, Lawrence, KS, 66047, USA.
Department of Molecular Biosciences, The University of Kansas, Lawrence, KS, 66045, USA.
J Comput Aided Mol Des. 2018 Jul;32(7):769-779. doi: 10.1007/s10822-018-0124-z. Epub 2018 Jul 12.
Modulating protein interaction pathways may lead to the cure of many diseases. Known protein-protein inhibitors bind to large pockets on the protein-protein interface. Such large pockets are detected also in the protein-protein complexes without known inhibitors, making such complexes potentially druggable. The inhibitor-binding site is primary defined by the side chains that form the largest pocket in the protein-bound conformation. Low-resolution ligand docking shows that the success rate for the protein-bound conformation is close to the one for the ligand-bound conformation, and significantly higher than for the apo conformation. The conformational change on the protein interface upon binding to the other protein results in a pocket employed by the ligand when it binds to that interface. This proof-of-concept study suggests that rather than using computational pocket-opening procedures, one can opt for an experimentally determined structure of the target co-crystallized protein-protein complex as a starting point for drug design.
调节蛋白质相互作用途径可能会导致许多疾病的治愈。已知的蛋白质-蛋白质抑制剂结合在蛋白质-蛋白质界面的大口袋上。在没有已知抑制剂的蛋白质-蛋白质复合物中也检测到这种大口袋,这使得这些复合物具有潜在的成药性。抑制剂结合位点主要由在蛋白质结合构象中形成最大口袋的侧链定义。低分辨率配体对接表明,对于蛋白质结合构象的成功率接近于配体结合构象的成功率,并且明显高于无配体结合构象的成功率。与另一个蛋白质结合时,蛋白质界面上的构象变化导致配体结合该界面时使用的口袋。这项概念验证研究表明,人们可以选择实验确定的目标共结晶蛋白质-蛋白质复合物的结构作为药物设计的起点,而不是使用计算口袋打开程序。