| scholarly article | Q13442814 |
| P8978 | DBLP publication ID | journals/jcisd/HoustonW13 |
| P356 | DOI | 10.1021/CI300399W |
| P698 | PubMed publication ID | 23351099 |
| P5875 | ResearchGate publication ID | 235373295 |
| P50 | author | Malcolm Walkinshaw | Q42659772 |
| P2093 | author name string | Douglas R Houston | |
| P2860 | cites work | Open Babel: An open chemical toolbox | Q21198766 |
| P433 | issue | 2 | |
| P921 | main subject | virtual screening | Q4112105 |
| P304 | page(s) | 384-390 | |
| P577 | publication date | 2013-02-07 | |
| P1433 | published in | Journal of Chemical Information and Modeling | Q3007982 |
| P1476 | title | Consensus docking: improving the reliability of docking in a virtual screening context | |
| P478 | volume | 53 |
| Q90172097 | An open-source drug discovery platform enables ultra-large virtual screens |
| Q90442960 | Assessing and improving the performance of consensus docking strategies using the DockBox package |
| Q52666970 | Assessing protein-ligand interaction scoring functions with the CASF-2013 benchmark. |
| Q41935814 | Attracting cavities for docking. Replacing the rough energy landscape of the protein by a smooth attracting landscape |
| Q92081890 | Can We Still Trust Docking Results? An Extension of the Applicability of DockBench on PDBbind Database |
| Q26779035 | Charting a Path to Success in Virtual Screening |
| Q26746941 | Computational approaches in target identification and drug discovery |
| Q59807300 | Computer-Aided Discovery of Small Molecule Inhibitors of Transcriptional Activity of TLX (NR2E1) Nuclear Receptor |
| Q52665633 | Cyclophilin J PPIase Inhibitors Derived from 2,3-Quinoxaline-6 Amine Exhibit Antitumor Activity. |
| Q33860716 | DDI-CPI, a server that predicts drug-drug interactions through implementing the chemical-protein interactome |
| Q98894849 | Design of drug-like hepsin inhibitors against prostate cancer and kidney stones |
| Q38729630 | Design, Synthesis, and Evaluation of Dasatinib-Amino Acid and Dasatinib-Fatty Acid Conjugates as Protein Tyrosine Kinase Inhibitors. |
| Q64954374 | Discovery of an intrasubunit nicotinic acetylcholine receptor binding site for the positive allosteric modulator Br-PBTC. |
| Q49355412 | Diversity of Nicotinic Acetylcholine Receptor Positive Allosteric Modulators Revealed by Mutagenesis and a Revised Structural Model. |
| Q35649682 | DockBench: An Integrated Informatic Platform Bridging the Gap between the Robust Validation of Docking Protocols and Virtual Screening Simulations. |
| Q42056130 | Evaluation of 11 scoring functions performance on matrix metalloproteinases |
| Q41409203 | Evaluation of a novel virtual screening strategy using receptor decoy binding sites. |
| Q34222933 | Fragment-based docking: development of the CHARMMing Web user interface as a platform for computer-aided drug design |
| Q93155087 | GLUT1 and TUBB4 in Glioblastoma Could be Efficacious Targets |
| Q35834844 | Identification and activity of inhibitors of the essential nematode-specific metalloprotease DPY-31 |
| Q47885052 | Identification of Phytochemicals Targeting c-Met Kinase Domain using Consensus Docking and Molecular Dynamics Simulation Studies. |
| Q38390892 | Improvements, trends, and new ideas in molecular docking: 2012-2013 in review. |
| Q54963827 | Improving Docking Performance Using Negative Image-Based Rescoring. |
| Q47700521 | In silico and empirical approaches toward understanding the structural adaptation of the alkaline-stable lipase KV1 from Acinetobacter haemolyticus. |
| Q57173973 | In silicoanalysis reveals the anti-malarial potential of quinolinyl chalcone derivatives |
| Q35836731 | Integrating sampling techniques and inverse virtual screening: toward the discovery of artificial peptide-based receptors for ligands |
| Q90193662 | Key Topics in Molecular Docking for Drug Design |
| Q36579823 | Ligand binding mode prediction by docking: mdm2/mdmx inhibitors as a case study |
| Q45946918 | Machine Learning Consensus Scoring Improves Performance Across Targets in Structure-Based Virtual Screening. |
| Q26750642 | Machine-learning scoring functions to improve structure-based binding affinity prediction and virtual screening |
| Q45943415 | Methods for Virtual Screening of GPCR Targets: Approaches and Challenges. |
| Q91657657 | Molecular Architect: A User-Friendly Workflow for Virtual Screening |
| Q36403490 | Potential Broad Spectrum Inhibitors of the Coronavirus 3CLpro: A Virtual Screening and Structure-Based Drug Design Study |
| Q38783140 | Receptor-ligand molecular docking |
| Q51699441 | Reliability analysis and optimization of the consensus docking approach for the development of virtual screening studies. |
| Q38553677 | Role of computer-aided drug design in modern drug discovery. |
| Q89831501 | Structure of Microtubule-Trapped Human Kinesin-5 and Its Mechanism of Inhibition Revealed Using Cryoelectron Microscopy |
| Q39747547 | Structure- and ligand-based virtual screening identifies new scaffolds for inhibitors of the oncoprotein MDM2. |
| Q35576545 | Structure-based virtual screening and discovery of New PPARδ/γ dual agonist and PPARδ and γ agonists |
| Q35282223 | Structure-based virtual screening for drug discovery: principles, applications and recent advances. |
| Q35754939 | The Augmenting Effects of Desolvation and Conformational Energy Terms on the Predictions of Docking Programs against mPGES-1. |
| Q28543708 | The interaction of RNA helicase DDX3 with HIV-1 Rev-CRM1-RanGTP complex during the HIV replication cycle |
| Q89779574 | Towards a Treatment for Gulf War Illness: A Consensus Docking Approach |
| Q58114472 | Using a Consensus Docking Approach to Predict Adverse Drug Reactions in Combination Drug Therapies for Gulf War Illness |
| Q64108583 | Vasodilation Elicited by Isoxsuprine, Identified by High-Throughput Virtual Screening of Compound Libraries, Involves Activation of the NO/cGMP and H₂S/K Pathways and Blockade of α₁-Adrenoceptors and Calcium Channels |
| Q40774775 | systemsDock: a web server for network pharmacology-based prediction and analysis |
| Q27902311 | vSDC: a method to improve early recognition in virtual screening when limited experimental resources are available |
Search more.