These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
3. 2D QSAR and similarity studies on cruzain inhibitors aimed at improving selectivity over cathepsin L. Freitas RF; Oprea TI; Montanari CA Bioorg Med Chem; 2008 Jan; 16(2):838-53. PubMed ID: 17996450 [TBL] [Abstract][Full Text] [Related]
4. Optimization of compound ranking for structure-based virtual ligand screening using an established FRED-Surflex consensus approach. Du J; Bleylevens IW; Bitorina AV; Wichapong K; Nicolaes GA Chem Biol Drug Des; 2014 Jan; 83(1):37-51. PubMed ID: 23941463 [TBL] [Abstract][Full Text] [Related]
6. Comparison of structure- and ligand-based virtual screening protocols considering hit list complementarity and enrichment factors. Krüger DM; Evers A ChemMedChem; 2010 Jan; 5(1):148-58. PubMed ID: 19908272 [TBL] [Abstract][Full Text] [Related]
7. Integrated in silico-in vitro strategy for screening of some traditional Egyptian plants for human aromatase inhibitors. Dawood HM; Ibrahim RS; Shawky E; Hammoda HM; Metwally AM J Ethnopharmacol; 2018 Oct; 224():359-372. PubMed ID: 29909120 [TBL] [Abstract][Full Text] [Related]
8. Comparative evaluation of 3D virtual ligand screening methods: impact of the molecular alignment on enrichment. Giganti D; Guillemain H; Spadoni JL; Nilges M; Zagury JF; Montes M J Chem Inf Model; 2010 Jun; 50(6):992-1004. PubMed ID: 20527883 [TBL] [Abstract][Full Text] [Related]
9. Lead finder: an approach to improve accuracy of protein-ligand docking, binding energy estimation, and virtual screening. Stroganov OV; Novikov FN; Stroylov VS; Kulkov V; Chilov GG J Chem Inf Model; 2008 Dec; 48(12):2371-85. PubMed ID: 19007114 [TBL] [Abstract][Full Text] [Related]
10. A Comparison between Enrichment Optimization Algorithm (EOA)-Based and Docking-Based Virtual Screening. Spiegel J; Senderowitz H Int J Mol Sci; 2021 Dec; 23(1):. PubMed ID: 35008467 [TBL] [Abstract][Full Text] [Related]
11. On evaluating molecular-docking methods for pose prediction and enrichment factors. Chen H; Lyne PD; Giordanetto F; Lovell T; Li J J Chem Inf Model; 2006; 46(1):401-15. PubMed ID: 16426074 [TBL] [Abstract][Full Text] [Related]
12. Toward fully automated high performance computing drug discovery: a massively parallel virtual screening pipeline for docking and molecular mechanics/generalized Born surface area rescoring to improve enrichment. Zhang X; Wong SE; Lightstone FC J Chem Inf Model; 2014 Jan; 54(1):324-37. PubMed ID: 24358939 [TBL] [Abstract][Full Text] [Related]
18. Docking-based virtual screening of Brazilian natural compounds using the OOMT as the pharmacological target database. Carregal AP; Maciel FV; Carregal JB; Dos Reis Santos B; da Silva AM; Taranto AG J Mol Model; 2017 Apr; 23(4):111. PubMed ID: 28285443 [TBL] [Abstract][Full Text] [Related]
19. Hybrid structure-based virtual screening protocol for the identification of novel BACE1 inhibitors. Vijayan RS; Prabu M; Mascarenhas NM; Ghoshal N J Chem Inf Model; 2009 Mar; 49(3):647-57. PubMed ID: 19434899 [TBL] [Abstract][Full Text] [Related]
20. Optimization of Structure Based Virtual Screening Protocols Against Thymidine Monophosphate Kinase Inhibitors as Antitubercular Agents. Ul-Haq Z; Uddin R; Gul S Mol Inform; 2011 Oct; 30(10):851-62. PubMed ID: 27468105 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]