.png){kind=icon}
返回
Docking Score ML: Target-Specific Machine Learning Models Improving Docking-Based Virtual Screening in 155 Targets
.png){kind=icon}
PRE
AI
DOI：10.1021/acs.jcim.4c00072.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In drug discovery, molecular docking methods face challenges in accurately predicting energy. Scoring functions used in molecular docking often fail to simulate complex protein-ligand interactions fully and accurately leading to biases and inaccuracies in virtual screening and target predictions. We introduce the Docking Score ML, developed from an analysis of over 200,000 docked complexes from 155 known targets for cancer treatments. The scoring functions used are founded on bioactivity data sourced from ChEMBL and have been fine-tuned using both supervised machine learning and deep learning techniques. We validated our approach extensively using multiple data sets such as validation of selectivity mechanism, the DUDE, DUD-AD, and LIT-PCBA data sets, and performed a multitarget analysis on drugs like sunitinib. To enhance prediction accuracy, feature fusion techniques were explored. By merging the capabilities of the Graph Convolutional Network (GCN) with multiple docking functions, our results indicated a clear superiority of our methodologies over conventional approaches. These advantages demonstrate that Docking Score ML is an efficient and accurate tool for virtual screening and reverse docking.
Keyword:
PROTEIN
GLIDE
ACCURACY
期刊
IF:
5.3
论文数:
9.1K
被引数:
4.0W
机构
引用论文
AutoDock Vina 1.2.0: New Docking Methods, Expanded Force Field, and Python BindingsAutoDock Vina 1.2.0: 新的对接方法，扩展的力场和Python绑定
OAAI
OAAI分享收藏DPDR-CPI, a server that predicts Drug Positioning and Drug Repositioning via Chemical-Protein Interactome.png)
SCIENTIFIC REPORTSOAAI
SCIENTIFIC REPORTSIF3.9
OAAI分享收藏LIT-PCBA: An Unbiased Data Set for Machine Learning and Virtual ScreeningLit-pcba: 用于机器学习和虚拟筛选的无偏数据集OAAI
OAAI分享收藏
Exponential consensus ranking improves the outcome in docking and receptor ensemble dockingSCIENTIFIC REPORTSOAAI
SCIENTIFIC REPORTSIF3.9
OAAI分享收藏
查看更多内容