Using Buriedness To Improve Discrimination between Actives and Inactives in Docking
暂无分享,去创建一个
[1] Xiaoqin Zou,et al. An iterative knowledge‐based scoring function to predict protein–ligand interactions: II. Validation of the scoring function , 2006, J. Comput. Chem..
[2] N. Foloppe,et al. Towards predictive ligand design with free-energy based computational methods? , 2006, Current medicinal chemistry.
[3] Ajay N. Jain,et al. Parameter estimation for scoring protein-ligand interactions using negative training data. , 2006, Journal of medicinal chemistry.
[4] Ajay N. Jain,et al. Scoring functions for protein-ligand docking. , 2006, Current protein & peptide science.
[5] Alexander D. MacKerell,et al. Consideration of Molecular Weight during Compound Selection in Virtual Target-Based Database Screening , 2003, J. Chem. Inf. Comput. Sci..
[6] Richard D. Taylor,et al. Virtual Screening Using Protein—Ligand Docking: Avoiding Artificial Enrichment. , 2004 .
[7] R. Glen,et al. Molecular recognition of receptor sites using a genetic algorithm with a description of desolvation. , 1995, Journal of molecular biology.
[8] Gergana Dimitrova,et al. A Stepwise Approach for Defining the Applicability Domain of SAR and QSAR Models , 2005, J. Chem. Inf. Model..
[9] Daniel A. Gschwend,et al. Analysis and optimization of structure-based virtual screening protocols. (3). New methods and old problems in scoring function design. , 2003, Journal of molecular graphics & modelling.
[10] D. E. Clark,et al. Flexible docking using tabu search and an empirical estimate of binding affinity , 1998, Proteins.
[11] G. V. Paolini,et al. Empirical scoring functions: I. The development of a fast empirical scoring function to estimate the binding affinity of ligands in receptor complexes , 1997, J. Comput. Aided Mol. Des..
[12] Richard D. Taylor,et al. Improved protein–ligand docking using GOLD , 2003, Proteins.
[13] Jaroslav Koca,et al. CAVER: a new tool to explore routes from protein clefts, pockets and cavities , 2006, BMC Bioinformatics.
[14] Gerhard Klebe,et al. Comparison of Automatic Three-Dimensional Model Builders Using 639 X-ray Structures , 1994, J. Chem. Inf. Comput. Sci..
[15] Martin Stahl,et al. Scoring functions for protein-ligand interactions: a critical perspective. , 2004, Drug discovery today. Technologies.
[16] Ajay N. Jain. Scoring noncovalent protein-ligand interactions: A continuous differentiable function tuned to compute binding affinities , 1996, J. Comput. Aided Mol. Des..
[17] C. E. Peishoff,et al. A critical assessment of docking programs and scoring functions. , 2006, Journal of medicinal chemistry.
[18] B. Shoichet,et al. Decoys for docking. , 2005, Journal of medicinal chemistry.
[19] Eric Jones,et al. SciPy: Open Source Scientific Tools for Python , 2001 .
[20] Paul N. Mortenson,et al. Diverse, high-quality test set for the validation of protein-ligand docking performance. , 2007, Journal of medicinal chemistry.
[21] Gerta Rücker,et al. y-Randomization and Its Variants in QSPR/QSAR , 2007, J. Chem. Inf. Model..
[22] Martin Stahl,et al. Modifications of the scoring function in FlexX for virtual screening applications , 2000 .
[23] P Willett,et al. Development and validation of a genetic algorithm for flexible docking. , 1997, Journal of molecular biology.
[24] Thomas Lengauer,et al. A fast flexible docking method using an incremental construction algorithm. , 1996, Journal of molecular biology.
[25] K. Sharp,et al. Travel depth, a new shape descriptor for macromolecules: application to ligand binding. , 2006, Journal of molecular biology.
[26] A. Leach,et al. Prediction of Protein—Ligand Interactions. Docking and Scoring: Successes and Gaps , 2006 .