Selwa Edithe, Martiny Virginie Y, Iorga Bogdan I
Institut de Chimie des Substances Naturelles, CNRS UPR 2301, LabEx LERMIT, Université Paris-Saclay, 91198, Gif-sur-Yvette, France.
Department of Nephrology and Dialysis, AP-HP, Tenon Hospital, INSERM UMR-S 1155, 75020, Paris, France.
J Comput Aided Mol Des. 2016 Sep;30(9):829-839. doi: 10.1007/s10822-016-9983-3. Epub 2016 Oct 3.
The D3R Grand Challenge 2015 was focused on two protein targets: Heat Shock Protein 90 (HSP90) and Mitogen-Activated Protein Kinase Kinase Kinase Kinase 4 (MAP4K4). We used a protocol involving a preliminary analysis of the available data in PDB and PubChem BioAssay, and then a docking/scoring step using more computationally demanding parameters that were required to provide more reliable predictions. We could evidence that different docking software and scoring functions can behave differently on individual ligand datasets, and that the flexibility of specific binding site residues is a crucial element to provide good predictions.
2015年的D3R大挑战聚焦于两个蛋白质靶点:热休克蛋白90(HSP90)和丝裂原活化蛋白激酶激酶激酶激酶4(MAP4K4)。我们采用了一种方案,包括对蛋白质数据银行(PDB)和化学数据库生物测定(PubChem BioAssay)中的现有数据进行初步分析,然后使用要求更高计算参数的对接/评分步骤,以提供更可靠的预测。我们可以证明,不同的对接软件和评分函数在单个配体数据集上的表现可能不同,并且特定结合位点残基的灵活性是提供良好预测的关键因素。