Supervised Consensus Scoring for Docking and Virtual Screening
暂无分享,去创建一个
[1] Janet M. Thornton,et al. BLEEP—potential of mean force describing protein–ligand interactions: I. Generating potential , 1999 .
[2] Anna Vulpetti,et al. Assessment of Docking Poses: Interactions-Based Accuracy Classification (IBAC) versus Crystal Structure Deviations. , 2004 .
[3] E. Shakhnovich,et al. SMoG: de Novo Design Method Based on Simple, Fast, and Accurate Free Energy Estimates. 1. Methodology and Supporting Evidence , 1996 .
[4] David S. Goodsell,et al. Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function , 1998, J. Comput. Chem..
[5] Shaomeng Wang,et al. MCDOCK: A Monte Carlo simulation approach to the molecular docking problem , 1999, J. Comput. Aided Mol. Des..
[6] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[7] M. Murcko,et al. Consensus scoring: A method for obtaining improved hit rates from docking databases of three-dimensional structures into proteins. , 1999, Journal of medicinal chemistry.
[8] Maria Kontoyianni,et al. Evaluation of library ranking efficacy in virtual screening , 2005, J. Comput. Chem..
[9] Y. Martin,et al. A general and fast scoring function for protein-ligand interactions: a simplified potential approach. , 1999, Journal of medicinal chemistry.
[10] Colin McMartin,et al. QXP: Powerful, rapid computer algorithms for structure-based drug design , 1997, J. Comput. Aided Mol. Des..
[11] W Patrick Walters,et al. A detailed comparison of current docking and scoring methods on systems of pharmaceutical relevance , 2004, Proteins.
[12] Gerhard Klebe,et al. Successful virtual screening for novel inhibitors of human carbonic anhydrase: strategy and experimental confirmation. , 2002, Journal of medicinal chemistry.
[13] D. Rognan,et al. Protein-based virtual screening of chemical databases. 1. Evaluation of different docking/scoring combinations. , 2000, Journal of medicinal chemistry.
[14] S. Vajda,et al. Protein docking along smooth association pathways , 2001, Proceedings of the National Academy of Sciences of the United States of America.
[15] J. Apostolakis,et al. Exhaustive docking of molecular fragments with electrostatic solvation , 1999, Proteins.
[16] Maria I. Zavodszky,et al. Distilling the essential features of a protein surface for improving protein-ligand docking, scoring, and virtual screening , 2002, J. Comput. Aided Mol. Des..
[17] Robert P. Sheridan,et al. Random Forest: A Classification and Regression Tool for Compound Classification and QSAR Modeling , 2003, J. Chem. Inf. Comput. Sci..
[18] Ajay N. Jain. Surflex: fully automatic flexible molecular docking using a molecular similarity-based search engine. , 2003, Journal of medicinal chemistry.
[19] Thomas Lengauer,et al. A fast flexible docking method using an incremental construction algorithm. , 1996, Journal of molecular biology.
[20] Matthew P. Repasky,et al. Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. , 2004, Journal of medicinal chemistry.
[21] Maria Kontoyianni,et al. Evaluation of docking performance: comparative data on docking algorithms. , 2004, Journal of medicinal chemistry.
[22] J. Onuchic,et al. Funnels, pathways, and the energy landscape of protein folding: A synthesis , 1994, Proteins.
[23] C. E. Peishoff,et al. A critical assessment of docking programs and scoring functions. , 2006, Journal of medicinal chemistry.
[24] R. Clark,et al. Consensus scoring for ligand/protein interactions. , 2002, Journal of molecular graphics & modelling.
[25] J M Blaney,et al. A geometric approach to macromolecule-ligand interactions. , 1982, Journal of molecular biology.
[26] Renxiao Wang,et al. Comparative evaluation of 11 scoring functions for molecular docking. , 2003, Journal of medicinal chemistry.
[27] P Willett,et al. Development and validation of a genetic algorithm for flexible docking. , 1997, Journal of molecular biology.
[28] Ruben Abagyan,et al. ICM—A new method for protein modeling and design: Applications to docking and structure prediction from the distorted native conformation , 1994, J. Comput. Chem..
[29] Tingjun Hou,et al. Automated docking of peptides and proteins by using a genetic algorithm combined with a tabu search. , 1999, Protein engineering.
[30] Yuan-Ping Pang,et al. Successful virtual screening of a chemical database for farnesyltransferase inhibitor leads. , 2000, Journal of medicinal chemistry.
[31] Richard D. Taylor,et al. Virtual Screening Using Protein—Ligand Docking: Avoiding Artificial Enrichment. , 2004 .
[32] Protein-Ligand Interactions,et al. Knowledge-based Scoring Function to Predict , 2000 .
[33] M Rarey,et al. Detailed analysis of scoring functions for virtual screening. , 2001, Journal of medicinal chemistry.
[34] A. N. Jain,et al. Hammerhead: fast, fully automated docking of flexible ligands to protein binding sites. , 1996, Chemistry & biology.
[35] Didier Rognan,et al. Comparative evaluation of eight docking tools for docking and virtual screening accuracy , 2004, Proteins.
[36] D. Frank Hsu,et al. Consensus Scoring Criteria for Improving Enrichment in Virtual Screening , 2005, J. Chem. Inf. Model..
[37] Todd J. A. Ewing,et al. DOCK 4.0: Search strategies for automated molecular docking of flexible molecule databases , 2001, J. Comput. Aided Mol. Des..
[38] D. E. Clark,et al. Flexible docking using tabu search and an empirical estimate of binding affinity , 1998, Proteins.
[39] Nagarajan Vaidehi,et al. HierVLS hierarchical docking protocol for virtual ligand screening of large-molecule databases. , 2004, Journal of medicinal chemistry.