| scholarly article | Q13442814 |
| P50 | author | Heather A Carlson | Q57549493 |
| P2093 | author name string | Katrina W Lexa | |
| P2860 | cites work | Application of a Theory of Enzyme Specificity to Protein Synthesis | Q24620284 |
| Flexible ligand docking to multiple receptor conformations: a practical alternative | Q24650066 | ||
| Refinement of docked protein-ligand and protein-DNA structures using low frequency normal mode amplitude optimization | Q24811274 | ||
| Locating interaction sites on proteins: the crystal structure of thermolysin soaked in 2% to 100% isopropanol | Q27621096 | ||
| Experimental and computational mapping of the binding surface of a crystalline protein | Q27631035 | ||
| Approaches to solving the rigid receptor problem by identifying a minimal set of flexible residues during ligand docking | Q27631837 | ||
| Organic solvents order the dynamic switch II in Ras crystals | Q27641611 | ||
| Enzymes with lid-gated active sites must operate by an induced fit mechanism instead of conformational selection | Q27651987 | ||
| Design of annulated pyrazoles as inhibitors of HIV-1 reverse transcriptase | Q27652894 | ||
| Fragment-based discovery of the pyrazol-4-yl urea (AT9283), a multitargeted kinase inhibitor with potent aurora kinase activity | Q27653420 | ||
| Multiple solvent crystal structures of ribonuclease A: an assessment of the method | Q27654183 | ||
| Enzyme crystal structure in a neat organic solvent | Q27732014 | ||
| Ionic interactions in crystalline bovine pancreatic ribonuclease A | Q27734234 | ||
| The crystal structure of subtilisin Carlsberg in anhydrous dioxane and its comparison with those in water and acetonitrile | Q27736243 | ||
| X-ray studies on cross-linked lysozyme crystals in acetonitrile-water mixture | Q27760488 | ||
| Comparison of x-ray crystal structures of an acyl-enzyme intermediate of subtilisin Carlsberg formed in anhydrous acetonitrile and in water | Q27765738 | ||
| Comparative protein structure modeling of genes and genomes | Q27860712 | ||
| ON THE NATURE OF ALLOSTERIC TRANSITIONS: A PLAUSIBLE MODEL | Q27861036 | ||
| Surflex: fully automatic flexible molecular docking using a molecular similarity-based search engine | Q28207735 | ||
| Docking ligands into flexible and solvated macromolecules. 4. Are popular scoring functions accurate for this class of proteins? | Q28245128 | ||
| Backbone-dependent rotamer library for proteins. Application to side-chain prediction | Q28267713 | ||
| Computational identification of uncharacterized cruzain binding sites | Q28473888 | ||
| AMMOS: Automated Molecular Mechanics Optimization tool for in silico Screening | Q28474233 | ||
| Computational fragment-based binding site identification by ligand competitive saturation | Q28475699 | ||
| ICM?A new method for protein modeling and design: Applications to docking and structure prediction from the distorted native conformation | Q29010774 | ||
| AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility | Q29547658 | ||
| Calculating structures and free energies of complex molecules: combining molecular mechanics and continuum models | Q29616389 | ||
| A critical assessment of docking programs and scoring functions | Q29616761 | ||
| Discovering high-affinity ligands for proteins: SAR by NMR | Q29617569 | ||
| Developing a dynamic pharmacophore model for HIV-1 integrase. | Q30326870 | ||
| FlexE: efficient molecular docking considering protein structure variations. | Q30328164 | ||
| Structure-based ligand design for flexible proteins: application of new F-DycoBlock. | Q30330267 | ||
| Distilling the essential features of a protein surface for improving protein-ligand docking, scoring, and virtual screening. | Q30333075 | ||
| Protein-ligand docking. | Q37881603 | ||
| Computational analysis of protein hotspots | Q39157726 | ||
| In pursuit of virtual lead optimization: the role of the receptor structure and ensembles in accurate docking | Q40419101 | ||
| Mining protein dynamics from sets of crystal structures using "consensus structures". | Q40454703 | ||
| Consistent improvement of cross-docking results using binding site ensembles generated with elastic network normal modes | Q41382543 | ||
| Soft docking and multiple receptor conformations in virtual screening | Q41968000 | ||
| Recipes for the selection of experimental protein conformations for virtual screening | Q42081112 | ||
| Reproducing crystal binding modes of ligand functional groups using Site-Identification by Ligand Competitive Saturation (SILCS) simulations | Q42130025 | ||
| Blind docking of pharmaceutically relevant compounds using RosettaLigand | Q42637708 | ||
| Side-chain flexibility in protein-ligand binding: the minimal rotation hypothesis | Q42769467 | ||
| Effects of protein conformation in docking: improved pose prediction through protein pocket adaptation | Q43115469 | ||
| Four-dimensional docking: a fast and accurate account of discrete receptor flexibility in ligand docking | Q43153980 | ||
| In pursuit of virtual lead optimization: pruning ensembles of receptor structures for increased efficiency and accuracy during docking | Q43170586 | ||
| A new method for ligand docking to flexible receptors by dual alanine scanning and refinement (SCARE). | Q43181588 | ||
| Automated docking to multiple target structures: incorporation of protein mobility and structural water heterogeneity in AutoDock | Q43825573 | ||
| Optimization and computational evaluation of a series of potential active site inhibitors of the V82F/I84V drug-resistant mutant of HIV-1 protease: an application of the relaxed complex method of structure-based drug design | Q43909316 | ||
| Computational drug design accommodating receptor flexibility: the relaxed complex scheme | Q43992973 | ||
| Enhanced docking with the mining minima optimizer: acceleration and side-chain flexibility | Q44190842 | ||
| The relaxed complex method: Accommodating receptor flexibility for drug design with an improved scoring scheme | Q44310443 | ||
| Efficient conformational sampling of local side-chain flexibility | Q44321337 | ||
| Functionality maps of binding sites: a multiple copy simultaneous search method | Q44440703 | ||
| A structure-based design approach for the identification of novel inhibitors: application to an alanine racemase. | Q44490685 | ||
| Molecular dynamics studies of alanine racemase: a structural model for drug design. | Q44601529 | ||
| "Soft docking": matching of molecular surface cubes | Q44675898 | ||
| Rapid protein-ligand docking using soft modes from molecular dynamics simulations to account for protein deformability: binding of FK506 to FKBP. | Q44784463 | ||
| Protein flexibility in ligand docking and virtual screening to protein kinases. | Q44786754 | ||
| Protein-ligand docking against non-native protein conformers | Q44921180 | ||
| Allosteric inhibition of protein tyrosine phosphatase 1B. | Q44982496 | ||
| Modeling correlated main-chain motions in proteins for flexible molecular recognition | Q45039418 | ||
| Conformational selection in silico: loop latching motions and ligand binding in enzymes. | Q45965729 | ||
| The limit of accuracy of protein modeling: influence of crystal packing on protein structure. | Q30351019 | ||
| Receptor flexibility in de novo ligand design and docking. | Q30351605 | ||
| Novel procedure for modeling ligand/receptor induced fit effects. | Q30352584 | ||
| Effective handling of induced-fit motion in flexible docking. | Q30353351 | ||
| Ensemble docking of multiple protein structures: considering protein structural variations in molecular docking. | Q30357936 | ||
| Exploring experimental sources of multiple protein conformations in structure-based drug design. | Q30362194 | ||
| Small molecule inhibitors of the MDM2-p53 interaction discovered by ensemble-based receptor models. | Q30364854 | ||
| Novel druggable hot spots in avian influenza neuraminidase H5N1 revealed by computational solvent mapping of a reduced and representative receptor ensemble. | Q30367220 | ||
| A poke in the eye: inhibiting HIV-1 protease through its flap-recognition pocket | Q30368595 | ||
| Ensemble-based virtual screening reveals potential novel antiviral compounds for avian influenza neuraminidase. | Q30370020 | ||
| Solvent dramatically affects protein structure refinement. | Q30373863 | ||
| In Pursuit of Fully Flexible Protein-Ligand Docking: Modeling the Bilateral Mechanism of Binding | Q30391029 | ||
| Full protein flexibility is essential for proper hot-spot mapping. | Q30397411 | ||
| Comparison of four independently determined structures of human recombinant interleukin-4. | Q30417777 | ||
| The Protein Data Bank and the challenge of structural genomics | Q30620508 | ||
| Relaxed complex scheme suggests novel inhibitors for the lyase activity of DNA polymerase beta. | Q30993534 | ||
| DrugScore(CSD)-knowledge-based scoring function derived from small molecule crystal data with superior recognition rate of near-native ligand poses and better affinity prediction | Q31007675 | ||
| Insights into equilibrium dynamics of proteins from comparison of NMR and X-ray data with computational predictions | Q31115351 | ||
| FDS: flexible ligand and receptor docking with a continuum solvent model and soft-core energy function | Q31154219 | ||
| Docking ligands onto binding site representations derived from proteins built by homology modelling. | Q32181064 | ||
| Combining docking and molecular dynamic simulations in drug design | Q33245994 | ||
| Virtual ligand screening: strategies, perspectives and limitations | Q33247681 | ||
| Towards in silico lead optimization: scores from ensembles of protein/ligand conformations reliably correlate with biological activity | Q33262339 | ||
| Discovery of antiandrogen activity of nonsteroidal scaffolds of marketed drugs | Q33289718 | ||
| A flexible approach to induced fit docking | Q33306730 | ||
| Docking ligands into flexible and solvated macromolecules. 2. Development and application of fitted 1.5 to the virtual screening of potential HCV polymerase inhibitors | Q33323904 | ||
| Fragment-based identification of druggable 'hot spots' of proteins using Fourier domain correlation techniques | Q33403707 | ||
| A virtual screening study of the acetylcholine binding protein using a relaxed-complex approach | Q33404791 | ||
| The multi-copy simultaneous search methodology: a fundamental tool for structure-based drug design | Q33464348 | ||
| Ensemble-based virtual screening reveals dual-inhibitors for the p53-MDM2/MDMX interactions. | Q33522505 | ||
| Folding funnels, binding funnels, and protein function | Q33674287 | ||
| Folding and binding cascades: shifts in energy landscapes | Q33723481 | ||
| The rise of fragment-based drug discovery | Q33838157 | ||
| Folding and binding cascades: dynamic landscapes and population shifts | Q33876426 | ||
| Locating and characterizing binding sites on proteins | Q34066761 | ||
| The many roles of computation in drug discovery | Q34307063 | ||
| Testing a flexible-receptor docking algorithm in a model binding site | Q34309041 | ||
| Structured disorder and conformational selection | Q34325473 | ||
| Computer-aided drug-discovery techniques that account for receptor flexibility | Q34519388 | ||
| Docking validation resources: protein family and ligand flexibility experiments | Q34680415 | ||
| Binding site detection and druggability index from first principles. | Q34964806 | ||
| Predictive power of molecular dynamics receptor structures in virtual screening | Q35073109 | ||
| Implications of protein flexibility for drug discovery | Q35167908 | ||
| Conformational flexibility models for the receptor in structure based drug design. | Q35181130 | ||
| CSAR benchmark exercise of 2010: selection of the protein-ligand complexes. | Q35232599 | ||
| CSAR benchmark exercise of 2010: combined evaluation across all submitted scoring functions. | Q35263970 | ||
| Conformational isomerism and the diversity of antibodies | Q35851135 | ||
| Is allostery an intrinsic property of all dynamic proteins? | Q35894622 | ||
| Maximizing discovery efficiency with a computationally driven fragment approach | Q36126338 | ||
| Target flexibility in molecular recognition | Q36266696 | ||
| Accounting for global protein deformability during protein-protein and protein-ligand docking | Q36281420 | ||
| Protein-ligand docking: current status and future challenges | Q36544700 | ||
| Prediction of protein-ligand interactions. Docking and scoring: successes and gaps | Q36605327 | ||
| Protein-ligand docking with multiple flexible side chains | Q36788480 | ||
| An improved relaxed complex scheme for receptor flexibility in computer-aided drug design | Q36838120 | ||
| Towards the development of universal, fast and highly accurate docking/scoring methods: a long way to go. | Q37014096 | ||
| Current topics in computer-aided drug design | Q37063579 | ||
| Target flexibility: an emerging consideration in drug discovery and design | Q37240137 | ||
| Conformational selection or induced fit: a flux description of reaction mechanism | Q37310586 | ||
| Binding of small-molecule ligands to proteins: "what you see" is not always "what you get". | Q37372747 | ||
| Managing protein flexibility in docking and its applications | Q37382489 | ||
| Docking flexible peptide to flexible protein by molecular dynamics using two implicit-solvent models: an evaluation in protein kinase and phosphatase systems | Q37445757 | ||
| Successful applications of computer aided drug discovery: moving drugs from concept to the clinic | Q37636258 | ||
| Scoring functions and their evaluation methods for protein-ligand docking: recent advances and future directions. | Q37781709 | ||
| Accounting for induced-fit effects in docking: what is possible and what is not? | Q37799620 | ||
| Development of a new predictive model for interactions with human cytochrome P450 2A6 using pharmacophore ensemble/support vector machine (PhE/SVM) approach | Q46185299 | ||
| Representing receptor flexibility in ligand docking through relevant normal modes. | Q46211444 | ||
| Binding mode prediction for a flexible ligand in a flexible pocket using multi-conformation simulated annealing pseudo crystallographic refinement | Q46347054 | ||
| Surflex-Dock 2.1: robust performance from ligand energetic modeling, ring flexibility, and knowledge-based search | Q46358770 | ||
| Unveiling the full potential of flexible receptor docking using multiple crystallographic structures | Q46563192 | ||
| Molecular docking to ensembles of protein structures | Q46668232 | ||
| Prediction of cytochrome P450 2B6-substrate interactions using pharmacophore ensemble/support vector machine (PhE/SVM) approach | Q47222678 | ||
| A novel approach using pharmacophore ensemble/support vector machine (PhE/SVM) for prediction of hERG liability | Q47303824 | ||
| Ensemble docking into multiple crystallographically derived protein structures: an evaluation based on the statistical analysis of enrichments | Q47618164 | ||
| Protein-ligand docking accounting for receptor side chain and global flexibility in normal modes: evaluation on kinase inhibitor cross docking | Q47669698 | ||
| Combining Elastic Network Analysis and Molecular Dynamics Simulations by Hamiltonian Replica Exchange | Q47881320 | ||
| Docking ligands into flexible and solvated macromolecules. 3. Impact of input ligand conformation, protein flexibility, and water molecules on the accuracy of docking programs | Q47948640 | ||
| Grand canonical free-energy calculations of protein-ligand binding. | Q50453664 | ||
| Grand canonical Monte Carlo simulation of ligand-protein binding. | Q50481549 | ||
| Can we trust docking results? Evaluation of seven commonly used programs on PDBbind database. | Q51664708 | ||
| RosettaLigand docking with full ligand and receptor flexibility. | Q51861937 | ||
| Modeling and selection of flexible proteins for structure-based drug design: backbone and side chain movements in p38 MAPK. | Q51898453 | ||
| FLIPDock: docking flexible ligands into flexible receptors. | Q51913931 | ||
| Docking ligands into flexible and solvated macromolecules. 1. Development and validation of FITTED 1.0. | Q51922137 | ||
| ROSETTALIGAND: protein-small molecule docking with full side-chain flexibility. | Q51933455 | ||
| Fully flexible low-mode docking: application to induced fit in HIV integrase. | Q52050278 | ||
| GRID/CPCA: a new computational tool to design selective ligands. | Q52074933 | ||
| Side-chain flexibility in proteins upon ligand binding. | Q52080522 | ||
| MCSS functionality maps for a flexible protein. | Q52082500 | ||
| A fast flexible docking method using an incremental construction algorithm. | Q52298930 | ||
| Ligand docking to proteins with discrete side-chain flexibility. | Q52383197 | ||
| Selected-fit versus induced-fit protein binding: kinetic differences and mutational analysis. | Q53529546 | ||
| Generation and selection of novel estrogen receptor ligands using the de novo structure-based design tool, SkelGen. | Q53601149 | ||
| Diverse, high-quality test set for the validation of protein-ligand docking performance. | Q55043208 | ||
| Fragment-Based Drug Discovery | Q55934078 | ||
| Synthese des Traubenzuckers | Q55953108 | ||
| How to choose relevant multiple receptor conformations for virtual screening: a test case of Cdk2 and normal mode analysis | Q56984187 | ||
| Docking Ligands on Protein Surfaces: The Case Study of Prion Protein | Q56990148 | ||
| COCO: A simple tool to enrich the representation of conformational variability in NMR structures | Q57831887 | ||
| How Reliable Are Current Docking Approaches for Structure-Based Drug Design? Lessons from Aldose Reductase | Q59171688 | ||
| Comparison of experimental and computational functional group mapping of an RNase A structure: implications for computer-aided drug design | Q71719496 | ||
| A method for including protein flexibility in protein-ligand docking: improving tools for database mining and virtual screening | Q73047696 | ||
| The sensitivity of the results of molecular docking to induced fit effects: application to thrombin, thermolysin and neuraminidase | Q73233694 | ||
| Antigen recognition by conformational selection | Q77816644 | ||
| Exploring the dynamic information content of a protein NMR structure: comparison of a molecular dynamics simulation with the NMR and X-ray structures of Escherichia coli ribonuclease HI | Q77894293 | ||
| Addressing protein flexibility and ligand selectivity by "in situ cross-docking" | Q79197682 | ||
| High-resolution structure of the p53 core domain: implications for binding small-molecule stabilizing compounds | Q79397464 | ||
| A novel computational analysis of ligand-induced conformational changes in the ATP binding sites of cyclin dependent kinases | Q80189222 | ||
| Use of an induced fit receptor structure in virtual screening | Q82621813 | ||
| Computational sampling of a cryptic drug binding site in a protein receptor: explicit solvent molecular dynamics and inhibitor docking to p38 MAP kinase | Q83158635 | ||
| P433 | issue | 3 | |
| P407 | language of work or name | English | Q1860 |
| P304 | page(s) | 301-343 | |
| P577 | publication date | 2012-05-09 | |
| P1433 | published in | Quarterly Reviews of Biophysics | Q2361372 |
| P1476 | title | Protein flexibility in docking and surface mapping | |
| P478 | volume | 45 |
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