Alchemical Grid Dock (AlGDock) calculations in the D3R Grand Challenge 3: Binding free energies between flexible ligands and rigid receptors

被引:4
|
作者
Xie, Bing [1 ]
Minh, David D. L. [1 ]
机构
[1] IIT, Dept Chem, Chicago, IL 60616 USA
基金
美国国家卫生研究院;
关键词
D3R; Drug Design Data Resource; Binding affinity; Pose prediction; AlGDock; MOLECULAR-DYNAMICS; EFFICIENT GENERATION; AM1-BCC MODEL; PREDICTION; MM/PBSA;
D O I
10.1007/s10822-018-0143-9
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
We participated in Subchallenges 1 and 2 of the Drug Design Data Resource (D3R) Grand Challenge 3. To prepare our submissions, we performed molecular docking with UCSF DOCK 6 and binding potential of mean force (BPMF) calculationsfree energy calculations between flexible ligands and rigid receptorsusing our open-source software package Alchemical Grid Dock (AlGDock). For each system, submissions were based on the minimum BPMF calculated for a selected set of crystal structures. In Subchallenge 1, our workflow performed poorly. Possible reasons for the poor performance include the neglect of cooperative ligands and limited sampling of ligand binding poses. In Subchallenge 2, our workflow led to some of most highly correlated submissions (Pearson R = 0.5) for vascular endothelial growth factor receptor 2. However, our results were poorly correlated for Janus Kinase 2 and Mitogen-activated protein kinase 14. Affinity prediction could potentially be improved by systematic selection of more diverse receptor configurations.
引用
收藏
页码:61 / 69
页数:9
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