Using Multiple Microenvironments to Find Similar Ligand-Binding Sites: Application to Kinase Inhibitor Binding
出版年份 2011 全文链接
标题
Using Multiple Microenvironments to Find Similar Ligand-Binding Sites: Application to Kinase Inhibitor Binding
作者
关键词
Kinase inhibitors, Tyrosine kinases, Adenine, Small molecules, Protein structure, Sequence alignment, Binding analysis, Adverse reactions
出版物
PLoS Computational Biology
Volume 7, Issue 12, Pages e1002326
出版商
Public Library of Science (PLoS)
发表日期
2011-12-30
DOI
10.1371/journal.pcbi.1002326
参考文献
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注意:仅列出部分参考文献,下载原文获取全部文献信息。- Remote Thioredoxin Recognition Using Evolutionary Conservation and Structural Dynamics
- (2011) Grace W. Tang et al. STRUCTURE
- Alignment-Free Ultra-High-Throughput Comparison of Druggable Protein−Ligand Binding Sites
- (2010) Nathanaël Weill et al. Journal of Chemical Information and Modeling
- Computer-aided drug design platform using PyMOL
- (2010) Markus A. Lill et al. JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN
- In-Silico Approaches to Multi-target Drug Discovery
- (2010) Xiao Hua Ma et al. PHARMACEUTICAL RESEARCH
- Basal Subtype and MAPK/ERK Kinase (MEK)-Phosphoinositide 3-Kinase Feedback Signaling Determine Susceptibility of Breast Cancer Cells to MEK Inhibition
- (2009) O. K. Mirzoeva et al. CANCER RESEARCH
- QSAR Models for Predicting the Similarity in Binding Profiles for Pairs of Protein Kinases and the Variation of Models between Experimental Data Sets
- (2009) Robert P. Sheridan et al. Journal of Chemical Information and Modeling
- ChEMBL. An interview with John Overington, team leader, chemogenomics at the European Bioinformatics Institute Outstation of the European Molecular Biology Laboratory (EMBL-EBI)
- (2009) Wendy A. Warr JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN
- Selectively Nonselective Kinase Inhibition: Striking the Right Balance
- (2009) Richard Morphy JOURNAL OF MEDICINAL CHEMISTRY
- Prediction of calcium-binding sites by combining loop-modeling with machine learning
- (2009) Tianyun Liu et al. BMC STRUCTURAL BIOLOGY
- Predicting Protein Ligand Binding Sites by Combining Evolutionary Sequence Conservation and 3D Structure
- (2009) John A. Capra et al. PLoS Computational Biology
- Drug Discovery Using Chemical Systems Biology: Identification of the Protein-Ligand Binding Network To Explain the Side Effects of CETP Inhibitors
- (2009) Li Xie et al. PLoS Computational Biology
- Detection of 3D atomic similarities and their use in the discrimination of small molecule protein-binding sites
- (2008) R. Najmanovich et al. BIOINFORMATICS
- How to Measure the Similarity Between Protein Ligand-Binding Sites?
- (2008) Esther Kellenberger et al. Current Computer-Aided Drug Design
- Quantifying the Relationships among Drug Classes
- (2008) Jérôme Hert et al. Journal of Chemical Information and Modeling
- A quantitative analysis of kinase inhibitor selectivity
- (2008) Mazen W Karaman et al. NATURE BIOTECHNOLOGY
- Targeted polypharmacology: discovery of dual inhibitors of tyrosine and phosphoinositide kinases
- (2008) Beth Apsel et al. Nature Chemical Biology
- Detecting evolutionary relationships across existing fold space, using sequence order-independent profile-profile alignments
- (2008) L. Xie et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- A simple and fuzzy method to align and compare druggable ligand-binding sites
- (2008) Claire Schalon et al. PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
- The SeqFEATURE library of 3D functional site models: comparison to existing methods and applications to protein function annotation
- (2008) Shirley Wu et al. GENOME BIOLOGY
- Inhibition of casein kinase 1-epsilon induces cancer-cell-selective, PERIOD2-dependent growth arrest
- (2008) Wan Seok Yang et al. GENOME BIOLOGY
- MAMMOTH (Matching molecular models obtained from theory): An automated method for model comparison
- (2002) Angel R. Ortiz et al. PROTEIN SCIENCE
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