| Literature DB >> 30084078 |
Abstract
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) calculations-free energy calculations between flexible ligands and rigid receptors-using 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.Entities:
Keywords: AlGDock; Binding affinity; D3R; Drug Design Data Resource; Pose prediction
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Year: 2018 PMID: 30084078 PMCID: PMC6363907 DOI: 10.1007/s10822-018-0143-9
Source DB: PubMed Journal: J Comput Aided Mol Des ISSN: 0920-654X Impact factor: 3.686