CANDOCK: Chemical atomic network based hierarchical flexible docking algorithm using generalized statistical potentials
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Ram Samudrala | Jonathan Fine | Gaurav Chopra | Janez Konc | R. Samudrala | Janez Konc | G. Chopra | Jonathan A Fine
[1] Michael M. Mysinger,et al. Directory of Useful Decoys, Enhanced (DUD-E): Better Ligands and Decoys for Better Benchmarking , 2012, Journal of medicinal chemistry.
[2] Yu-chian Chen. Beware of docking! , 2015, Trends in pharmacological sciences.
[3] Thomas Lengauer,et al. FlexE: efficient molecular docking considering protein structure variations. , 2001, Journal of molecular biology.
[4] R. Woods,et al. Vina-Carb: Improving Glycosidic Angles during Carbohydrate Docking. , 2016, Journal of chemical theory and computation.
[5] I. Luque,et al. Structural stability of binding sites: Consequences for binding affinity and allosteric effects , 2000, Proteins.
[6] Ram Samudrala,et al. Computational Multitarget Drug Discovery , 2012 .
[7] Xiaoqin Zou,et al. Efficient molecular docking of NMR structures: Application to HIV‐1 protease , 2006, Protein science : a publication of the Protein Society.
[8] Zhihai Liu,et al. Forging the Basis for Developing Protein-Ligand Interaction Scoring Functions. , 2017, Accounts of chemical research.
[9] R. Samudrala,et al. Distal Effect of Amino Acid Substitutions in CYP2C9 Polymorphic Variants Causes Differences in Interatomic Interactions against (S)-Warfarin , 2013, PloS one.
[10] Yan Li,et al. Comparative Assessment of Scoring Functions: The CASF-2016 Update , 2018, J. Chem. Inf. Model..
[11] Ram Samudrala,et al. A generalized knowledge‐based discriminatory function for biomolecular interactions , 2009, Proteins.
[12] Rafael Najmanovich,et al. FlexAID: Revisiting Docking on Non-Native-Complex Structures , 2015, J. Chem. Inf. Model..
[13] Daniel A. Gschwend,et al. Orientational sampling and rigid‐body minimization in molecular docking , 1993, Proteins.
[14] Hong Wang,et al. Can the Energy Gap in the Protein-Ligand Binding Energy Landscape Be Used as a Descriptor in Virtual Ligand Screening? , 2012, PloS one.
[15] Dan Li,et al. Comprehensive evaluation of ten docking programs on a diverse set of protein-ligand complexes: the prediction accuracy of sampling power and scoring power. , 2016, Physical chemistry chemical physics : PCCP.
[16] Kenji Onodera,et al. Evaluations of Molecular Docking Programs for Virtual Screening , 2007, J. Chem. Inf. Model..
[17] Feng Ding,et al. Rapid Flexible Docking Using a Stochastic Rotamer Library of Ligands , 2010, J. Chem. Inf. Model..
[18] Richard D. Taylor,et al. Improved protein–ligand docking using GOLD , 2003, Proteins.
[19] 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.
[20] W Patrick Walters,et al. A detailed comparison of current docking and scoring methods on systems of pharmaceutical relevance , 2004, Proteins.
[21] Yongbo Hu,et al. Comparison of Several Molecular Docking Programs: Pose Prediction and Virtual Screening Accuracy , 2009, J. Chem. Inf. Model..
[22] Elizabeth Yuriev,et al. Latest developments in molecular docking: 2010–2011 in review , 2013, Journal of molecular recognition : JMR.
[23] Ram Samudrala,et al. Rappertk: a versatile engine for discrete restraint-based conformational sampling of macromolecules , 2007, BMC Structural Biology.
[24] P. Kollman,et al. Automatic atom type and bond type perception in molecular mechanical calculations. , 2006, Journal of molecular graphics & modelling.
[25] Suzanne C Brewerton,et al. The use of protein-ligand interaction fingerprints in docking. , 2008, Current opinion in drug discovery & development.
[26] Feng Ding,et al. CSAR Benchmark of Flexible MedusaDock in Affinity Prediction and Nativelike Binding Pose Selection , 2016, J. Chem. Inf. Model..
[27] Cheng Wang,et al. Improving scoring‐docking‐screening powers of protein–ligand scoring functions using random forest , 2017, J. Comput. Chem..
[28] A. Caflisch,et al. Discovery of ZAP70 inhibitors by high-throughput docking into a conformation of its kinase domain generated by molecular dynamics. , 2013, Bioorganic & medicinal chemistry letters.
[29] A. A. Lagunin,et al. Computer-aided prediction of xenobiotic metabolism in humans , 2016 .
[30] Jorge Nocedal,et al. On the limited memory BFGS method for large scale optimization , 1989, Math. Program..
[31] J. Irwin,et al. Benchmarking sets for molecular docking. , 2006, Journal of medicinal chemistry.
[32] G. Chopra,et al. Identification of New FLT3 Inhibitors That Potently Inhibit AML Cell Lines via an Azo Click-It/Staple-It Approach. , 2017, ACS medicinal chemistry letters.
[33] Richard D. Smith,et al. CSAR 2014: A Benchmark Exercise Using Unpublished Data from Pharma , 2016, J. Chem. Inf. Model..
[34] Aleksey A. Porollo,et al. Survey of public domain software for docking simulations and virtual screening , 2011, Human Genomics.
[35] Ram Samudrala,et al. Exploring Polypharmacology in Drug Discovery and Repurposing Using the CANDO Platform. , 2016, Current pharmaceutical design.
[36] Amedeo Caflisch,et al. Docking small ligands in flexible binding sites , 1998, J. Comput. Chem..
[37] Ram Samudrala,et al. Novel paradigms for drug discovery: computational multitarget screening. , 2008, Trends in pharmacological sciences.
[38] Arthur J. Olson,et al. AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading , 2009, J. Comput. Chem..
[39] Mohamed A. Khamis,et al. Comparative assessment of machine-learning scoring functions on PDBbind 2013 , 2015, Eng. Appl. Artif. Intell..
[40] Santiago Vilar,et al. Medicinal chemistry and the molecular operating environment (MOE): application of QSAR and molecular docking to drug discovery. , 2008, Current topics in medicinal chemistry.
[41] J A McCammon,et al. Accommodating protein flexibility in computational drug design. , 2000, Molecular pharmacology.
[42] Elaine C. Meng,et al. Determination of molecular topology and atomic hybridization states from heavy atom coordinates , 1991 .
[43] Christopher M. Summa,et al. Solvent dramatically affects protein structure refinement , 2008, Proceedings of the National Academy of Sciences.
[44] Miklos Feher,et al. Effect of Input Differences on the Results of Docking Calculations , 2009, J. Chem. Inf. Model..
[45] Vijay S. Pande,et al. OpenMM 7: Rapid development of high performance algorithms for molecular dynamics , 2016, bioRxiv.
[46] Janez Konc,et al. An improved branch and bound algorithm for the maximum clique problem , 2007 .
[47] X. Zou,et al. Ensemble docking of multiple protein structures: Considering protein structural variations in molecular docking , 2006, Proteins.
[48] Paul N. Mortenson,et al. Diverse, high-quality test set for the validation of protein-ligand docking performance. , 2007, Journal of medicinal chemistry.
[49] Junmei Wang,et al. Development and testing of a general amber force field , 2004, J. Comput. Chem..
[50] Richard D. Smith,et al. CSAR Benchmark Exercise 2011–2012: Evaluation of Results from Docking and Relative Ranking of Blinded Congeneric Series , 2013, J. Chem. Inf. Model..
[51] Leslie A Kuhn,et al. Side‐chain flexibility in protein–ligand binding: The minimal rotation hypothesis , 2005, Protein science : a publication of the Protein Society.
[52] C. E. Peishoff,et al. A critical assessment of docking programs and scoring functions. , 2006, Journal of medicinal chemistry.
[53] Didier Rognan,et al. Protein‐based virtual screening of chemical databases. II. Are homology models of g‐protein coupled receptors suitable targets? , 2002, Proteins.
[54] A. Butte,et al. Predicting Adverse Drug Reactions Using Publicly Available PubChem BioAssay Data , 2011, Clinical pharmacology and therapeutics.
[55] Frank H. Allen,et al. Cambridge Structural Database , 2002 .
[56] William J. Allen,et al. DOCK 6: Impact of new features and current docking performance , 2015, J. Comput. Chem..
[57] Ram Samudrala,et al. CANDO and the infinite drug discovery frontier. , 2014, Drug discovery today.
[58] Didier Rognan,et al. Comparative evaluation of eight docking tools for docking and virtual screening accuracy , 2004, Proteins.
[59] Ram Samudrala,et al. Identification of potential multitarget antimalarial drugs. , 2005, JAMA.
[60] Andreas Bender,et al. Computational Prediction of Metabolism: Sites, Products, SAR, P450 Enzyme Dynamics, and Mechanisms , 2012, J. Chem. Inf. Model..
[61] Ram Samudrala,et al. Combating Ebola with Repurposed Therapeutics Using the CANDO Platform , 2016, Molecules.
[62] Xavier Barril,et al. rDock: A Fast, Versatile and Open Source Program for Docking Ligands to Proteins and Nucleic Acids , 2014, PLoS Comput. Biol..
[63] Dieter Lang,et al. Predicting drug metabolism: experiment and/or computation? , 2015, Nature Reviews Drug Discovery.
[64] Ram Samudrala,et al. Computational chemoproteomics to understand the role of selected psychoactives in treating mental health indications , 2019, Scientific Reports.
[65] Kam Y. J. Zhang,et al. Structural basis for the activity of drugs that inhibit phosphodiesterases. , 2004, Structure.
[66] R Samudrala,et al. Strategic Protein Target Analysis for Developing Drugs to Stop Dental Caries , 2012, Advances in dental research.
[67] Z. Deng,et al. Structural interaction fingerprint (SIFt): a novel method for analyzing three-dimensional protein-ligand binding interactions. , 2004, Journal of medicinal chemistry.
[68] Yuri Pevzner,et al. Fragment-Based Docking: Development of the CHARMMing Web User Interface as a Platform for Computer-Aided Drug Design , 2014, J. Chem. Inf. Model..
[69] David S. Goodsell,et al. The RCSB Protein Data Bank: views of structural biology for basic and applied research and education , 2014, Nucleic Acids Res..
[70] Arthur J Olson,et al. Fragment-Based Analysis of Ligand Dockings Improves Classification of Actives , 2016, J. Chem. Inf. Model..
[71] Thomas E. Cheatham,et al. Quantum mechanically derived AMBER‐compatible heme parameters for various states of the cytochrome P450 catalytic cycle , 2012, J. Comput. Chem..
[72] Ram Samudrala,et al. Multiscale modelling of relationships between protein classes and drug behavior across all diseases using the CANDO platform. , 2015, Mini reviews in medicinal chemistry.
[73] A. Leach,et al. Ligand docking to proteins with discrete side-chain flexibility. , 1994, Journal of molecular biology.
[74] Michael Levitt,et al. KoBaMIN: a knowledge-based minimization web server for protein structure refinement , 2012, Nucleic Acids Res..
[75] Michael Levitt,et al. Consistent refinement of submitted models at CASP using a knowledge‐based potential , 2010, Proteins.
[76] Simon S. J. Cross. Improved FlexX Docking Using FlexS-Determined Base Fragment Placement , 2005, J. Chem. Inf. Model..