| scholarly article | Q13442814 |
| P50 | author | Claudio N. Cavasotto | Q54867248 |
| P2093 | author name string | Ruben A Abagyan | |
| Julio A Kovacs | |||
| P433 | issue | 26 | |
| P407 | language of work or name | English | Q1860 |
| P304 | page(s) | 9632-9640 | |
| P577 | publication date | 2005-07-01 | |
| P1433 | published in | Journal of the American Chemical Society | Q898902 |
| P1476 | title | Representing receptor flexibility in ligand docking through relevant normal modes | |
| P478 | volume | 127 |
| Q35685828 | 2,3-Dihydro-1-benzofuran derivatives as a series of potent selective cannabinoid receptor 2 agonists: design, synthesis, and binding mode prediction through ligand-steered modeling. |
| Q45984545 | A docking study using atomistic conformers generated via elastic network model for cyclosporin A/cyclophilin A complex. |
| Q40496890 | A flexible docking scheme to explore the binding selectivity of PDZ domains |
| Q36175910 | A mining minima approach to exploring the docking pathways of p-nitrocatechol sulfate to YopH. |
| Q43181588 | A new method for ligand docking to flexible receptors by dual alanine scanning and refinement (SCARE). |
| Q34402706 | ALiBERO: evolving a team of complementary pocket conformations rather than a single leader |
| Q28474233 | AMMOS: Automated Molecular Mechanics Optimization tool for in silico Screening |
| Q37253674 | Accurate prediction of the bound form of the Akt pleckstrin homology domain using normal mode analysis to explore structural flexibility |
| Q37409322 | An Evaluation of Explicit Receptor Flexibility in Molecular Docking Using Molecular Dynamics and Torsion Angle Molecular Dynamics |
| Q38908260 | An analysis of horseradish peroxidase enzyme for effluent treatment |
| Q36838120 | An improved relaxed complex scheme for receptor flexibility in computer-aided drug design |
| Q43105884 | Assessment of programs for ligand binding affinity prediction |
| Q30385726 | Automated NMR Assignment and Protein Structure Determination using Sparse Dipolar Coupling Constraints. |
| Q101237263 | Automated and optimally FRET-assisted structural modeling |
| Q41043727 | BP-Dock: a flexible docking scheme for exploring protein-ligand interactions based on unbound structures |
| Q30044592 | Building a virtual ligand screening pipeline using free software: a survey |
| Q34354249 | Can conformational change be described by only a few normal modes? |
| Q26779035 | Charting a Path to Success in Virtual Screening |
| Q30826992 | ClustENM: ENM-Based Sampling of Essential Conformational Space at Full Atomic Resolution |
| Q41834158 | Collective dynamics of the ribosomal tunnel revealed by elastic network modeling |
| Q27662173 | Complementarity Between a Docking and a High-Throughput Screen in Discovering New Cruzain Inhibitors |
| Q38834773 | Computational generation inhibitor-bound conformers of p38 MAP kinase and comparison with experiments. |
| Q34519388 | Computer-aided drug-discovery techniques that account for receptor flexibility |
| Q58042896 | Computing protein dynamics from protein structure with elastic network models |
| Q28472382 | Conformational transitions upon ligand binding: holo-structure prediction from apo conformations |
| Q36949327 | Conformer selection and induced fit in flexible backbone protein-protein docking using computational and NMR ensembles |
| Q34440071 | Consensus Induced Fit Docking (cIFD): methodology, validation, and application to the discovery of novel Crm1 inhibitors |
| Q41382543 | Consistent improvement of cross-docking results using binding site ensembles generated with elastic network normal modes |
| Q37392115 | Convergence and combination of methods in protein-protein docking |
| Q90148769 | Cooperative dynamics of proteins unraveled by network models |
| Q36447801 | DARC: Mapping Surface Topography by Ray-Casting for Effective Virtual Screening at Protein Interaction Sites |
| Q38606437 | Dealing with structural variability in molecular replacement and crystallographic refinement through normal-mode analysis |
| Q33289718 | Discovery of antiandrogen activity of nonsteroidal scaffolds of marketed drugs |
| Q35630615 | Discovery of novel checkpoint kinase 1 inhibitors by virtual screening based on multiple crystal structures |
| Q41735613 | Discovery of novel inhibitors targeting enoyl-acyl carrier protein reductase in Plasmodium falciparum by structure-based virtual screening |
| Q37445757 | Docking flexible peptide to flexible protein by molecular dynamics using two implicit-solvent models: an evaluation in protein kinase and phosphatase systems |
| Q30495708 | Docking to RNA via root-mean-square-deviation-driven energy minimization with flexible ligands and flexible targets |
| Q34561020 | Docking-based virtual screening for ligands of G protein-coupled receptors: not only crystal structures but also in silico models. |
| Q31152113 | DrugScorePPI knowledge-based potentials used as scoring and objective function in protein-protein docking |
| Q90353407 | Druggability Simulations and X-Ray Crystallography Reveal a Ligand-Binding Site in the GluA3 AMPA Receptor N-Terminal Domain |
| Q38815460 | Dynamical persistence of active sites identified in maltose-binding protein. |
| Q51532081 | Efficient inclusion of receptor flexibility in grid-based protein-ligand docking. |
| Q35211087 | Efficient incorporation of protein flexibility and dynamics into molecular docking simulations |
| Q36420334 | Efficient molecular docking of NMR structures: application to HIV-1 protease |
| Q41561349 | Elastic network model of learned maintained contacts to predict protein motion. |
| Q84037024 | Elastic potential grids: accurate and efficient representation of intermolecular interactions for fully flexible docking |
| Q34908421 | Emerging methods for ensemble-based virtual screening |
| Q30370020 | Ensemble-based virtual screening reveals potential novel antiviral compounds for avian influenza neuraminidase. |
| Q38976083 | Expanding the horizons of G protein-coupled receptor structure-based ligand discovery and optimization using homology models. |
| Q41856020 | Exploiting conformational dynamics in drug discovery: design of C-terminal inhibitors of Hsp90 with improved activities |
| Q42760404 | Exploring NMR ensembles of calcium binding proteins: perspectives to design inhibitors of protein-protein interactions |
| Q51438298 | Exploring c-Met kinase flexibility by sampling and clustering its conformational space. |
| Q64121450 | Exponential consensus ranking improves the outcome in docking and receptor ensemble docking |
| Q28535400 | Fast docking on graphics processing units via Ray-Casting |
| Q34909306 | FiberDock: Flexible induced-fit backbone refinement in molecular docking |
| Q33957727 | FiberDock: a web server for flexible induced-fit backbone refinement in molecular docking |
| Q24650066 | Flexible ligand docking to multiple receptor conformations: a practical alternative |
| Q38574930 | Flexible receptor docking for drug discovery |
| Q37303892 | Focused functional dynamics of supramolecules by use of a mixed-resolution elastic network model |
| Q43153980 | Four-dimensional docking: a fast and accurate account of discrete receptor flexibility in ligand docking |
| Q51668649 | HIV-1 TAR RNA Spontaneously Undergoes Relevant Apo-to-Holo Conformational Transitions in Molecular Dynamics and Constrained Geometrical Simulations |
| Q56984187 | How to choose relevant multiple receptor conformations for virtual screening: a test case of Cdk2 and normal mode analysis |
| Q55692117 | Identification of potential inhibitor targeting enoyl-acyl carrier protein reductase (InhA) in Mycobacterium tuberculosis: a computational approach. |
| Q45353103 | Identification of potential inhibitors of H5N1 influenza A virus neuraminidase by ligand-based virtual screening approach |
| Q27671773 | Identification of the functional binding pocket for compounds targeting small-conductance Ca2+-activated potassium channels |
| Q24656051 | Identification of xenoestrogens in food additives by an integrated in silico and in vitro approach |
| Q80642884 | Improving database enrichment through ensemble docking |
| Q30391029 | In Pursuit of Fully Flexible Protein-Ligand Docking: Modeling the Bilateral Mechanism of Binding |
| Q30413844 | In silico analysis of drug-resistant mutant of neuraminidase (N294S) against oseltamivir |
| Q38089793 | Incorporating protein flexibility into docking and structure-based drug design. |
| Q28287816 | Insights into protein flexibility: The relationship between normal modes and conformational change upon protein-protein docking |
| Q90193662 | Key Topics in Molecular Docking for Drug Design |
| Q28552181 | Ligand Docking to Intermediate and Close-To-Bound Conformers Generated by an Elastic Network Model Based Algorithm for Highly Flexible Proteins |
| Q33636089 | Ligand and structure-based models for the prediction of ligand-receptor affinities and virtual screenings: Development and application to the beta(2)-adrenergic receptor |
| Q42108854 | Manipulation of Conformational Change in Proteins by Single-Residue Perturbations |
| Q37539924 | Mastering tricyclic ring systems for desirable functional cannabinoid activity |
| Q30574019 | Modeling protein conformational transitions by a combination of coarse-grained normal mode analysis and robotics-inspired methods |
| Q33511631 | Molecular docking screens using comparative models of proteins |
| Q37843834 | Molecular motions in drug design: the coming age of the metadynamics method |
| Q35733861 | Molecular recognition in the case of flexible targets |
| Q36131058 | Multivalent interactions between lectins and supramolecular complexes: Galectin-1 and self-assembled pseudopolyrotaxanes |
| Q28478611 | Mutation D816V alters the internal structure and dynamics of c-KIT receptor cytoplasmic region: implications for dimerization and activation mechanisms |
| Q42553727 | NOMAD-Ref: visualization, deformation and refinement of macromolecular structures based on all-atom normal mode analysis |
| Q58571868 | Normal mode analysis as a prerequisite for drug design: Application to matrix metalloproteinases inhibitors |
| Q33718901 | Normal mode analysis of biomolecular structures: functional mechanisms of membrane proteins |
| Q41172407 | On the functional significance of soft modes predicted by coarse-grained models for membrane proteins |
| Q36931811 | Overcoming the inadequacies or limitations of experimental structures as drug targets by using computational modeling tools and molecular dynamics simulations |
| Q38136697 | Perspective: Coarse-grained models for biomolecular systems |
| Q36502439 | Pocket-based drug design: exploring pocket space |
| Q30405812 | Pre-existing soft modes of motion uniquely defined by native contact topology facilitate ligand binding to proteins |
| Q35624629 | Predicting flexible loop regions that interact with ligands: the challenge of accurate scoring |
| Q30406906 | Predicting large-scale conformational changes in proteins using energy-weighted normal modes. |
| Q34060024 | Predicting protein ligand binding motions with the conformation explorer |
| Q36952164 | Principles of flexible protein-protein docking |
| Q38428430 | Protein Flexibility in Drug Discovery: From Theory to Computation |
| Q57990955 | Protein Ligand DockingDocking in Drug DiscoveryDrug Discovery |
| Q26864013 | Protein flexibility in docking and surface mapping |
| Q40291466 | Protein-Protein Docking Using EMAP in CHARMM and Support Vector Machine: Application to Ab/Ag Complexes. |
| Q26865357 | Rational approaches to improving selectivity in drug design |
| Q36795631 | Rational prediction with molecular dynamics for hit identification |
| Q57975284 | Receptor flexibility in small-molecule docking calculations |
| Q42081112 | Recipes for the selection of experimental protein conformations for virtual screening |
| Q42380648 | Sequence composition and environment effects on residue fluctuations in protein structures |
| Q42863821 | Status of GPCR modeling and docking as reflected by community-wide GPCR Dock 2010 assessment |
| Q33238328 | Structure-based development of target-specific compound libraries |
| Q34408300 | Structure-based virtual screening of the nociceptin receptor: hybrid docking and shape-based approaches for improved hit identification |
| Q41239235 | SwarmDock and the use of normal modes in protein-protein docking |
| Q37240137 | Target flexibility: an emerging consideration in drug discovery and design |
| Q30380115 | The intrinsic dynamics of enzymes plays a dominant role in determining the structural changes induced upon inhibitor binding |
| Q83278382 | The molecular mechanism of bee venom phospholipase A2 inactivation by bolinaquinone |
| Q39844414 | Three amino acids in the D2 dopamine receptor regulate selective ligand function and affinity. |
| Q33376019 | Toward a molecular understanding of the interaction of dual specificity phosphatases with substrates: insights from structure-based modeling and high throughput screening |
| Q30383112 | Ultra-High-Throughput Structure-Based Virtual Screening for Small-Molecule Inhibitors of Protein-Protein Interactions. |
| Q38594557 | Understanding the challenges of protein flexibility in drug design. |
| Q58571808 | Use of normal modes for structural modeling of proteins: the case study of rat heme oxygenase 1 |
| Q39707773 | Vaccinia virus virulence factor N1L is a novel promising target for antiviral therapeutic intervention |
| Q48115185 | iMod: multipurpose normal mode analysis in internal coordinates |
Search more.