Balius Trent E, Tan Y Stanley, Chakrabarti Mayukh
NCI RAS Initiative, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research, Inc., Frederick, Maryland, USA.
J Comput Chem. 2024 Jan 5;45(1):47-63. doi: 10.1002/jcc.27218. Epub 2023 Sep 25.
To allow DOCK 6 access to unprecedented chemical space for screening billions of small molecules, we have implemented features from DOCK 3.7 into DOCK 6, including a search routine that traverses precomputed ligand conformations stored in a hierarchical database. We tested them on the DUDE-Z and SB2012 test sets. The hierarchical database search routine is 16 times faster than anchor-and-grow. However, the ability of hierarchical database search to reproduce the experimental pose is 16% worse than that of anchor-and-grow. The enrichment performance is on average similar, but DOCK 3.7 has better enrichment than DOCK 6, and DOCK 6 is on average 1.7 times slower. However, with post-docking torsion minimization, DOCK 6 surpasses DOCK 3.7. A large-scale virtual screen is performed with DOCK 6 on 23 million fragment molecules. We use current features in DOCK 6 to complement hierarchical database calculations, including torsion minimization, which is not available in DOCK 3.7.
为了使DOCK 6能够访问前所未有的化学空间以筛选数十亿个小分子,我们已将DOCK 3.7的功能应用于DOCK 6,包括一个遍历存储在分层数据库中的预计算配体构象的搜索程序。我们在DUDE-Z和SB2012测试集上对它们进行了测试。分层数据库搜索程序比锚定生长法快16倍。然而,分层数据库搜索重现实验姿态的能力比锚定生长法差16%。富集性能平均相似,但DOCK 3.7的富集效果优于DOCK 6,且DOCK 6平均慢1.7倍。然而,通过对接后扭转最小化,DOCK 6超过了DOCK 3.7。使用DOCK 6对2300万个片段分子进行了大规模虚拟筛选。我们利用DOCK 6中的当前功能来补充分层数据库计算,包括扭转最小化,这在DOCK 3.7中是不可用的。