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.
181 related articles for article (PubMed ID: 19995305)
1. A common feature-based 3D-pharmacophore model generation and virtual screening: identification of potential PfDHFR inhibitors. Adane L; Bharatam PV; Sharma V J Enzyme Inhib Med Chem; 2010 Oct; 25(5):635-45. PubMed ID: 19995305 [TBL] [Abstract][Full Text] [Related]
2. Shape- and chemical feature-based 3D-pharmacophore model generation and virtual screening: identification of potential leads for P. falciparum DHFR enzyme inhibition. Adane L; Patel DS; Bharatam PV Chem Biol Drug Des; 2010 Jan; 75(1):115-26. PubMed ID: 19895504 [TBL] [Abstract][Full Text] [Related]
3. Three-dimensional quantitative structure-activity relationship analysis of a set of Plasmodium falciparum dihydrofolate reductase inhibitors using a pharmacophore generation approach. Parenti MD; Pacchioni S; Ferrari AM; Rastelli G J Med Chem; 2004 Aug; 47(17):4258-67. PubMed ID: 15293997 [TBL] [Abstract][Full Text] [Related]
5. In silico screening against wild-type and mutant Plasmodium falciparum dihydrofolate reductase. Fogel GB; Cheung M; Pittman E; Hecht D J Mol Graph Model; 2008 Apr; 26(7):1145-52. PubMed ID: 18037315 [TBL] [Abstract][Full Text] [Related]
6. Docking and database screening reveal new classes of Plasmodium falciparum dihydrofolate reductase inhibitors. Rastelli G; Pacchioni S; Sirawaraporn W; Sirawaraporn R; Parenti MD; Ferrari AM J Med Chem; 2003 Jul; 46(14):2834-45. PubMed ID: 12825927 [TBL] [Abstract][Full Text] [Related]
7. Interactions between cycloguanil derivatives and wild type and resistance-associated mutant Plasmodium falciparum dihydrofolate reductases. Maitarad P; Kamchonwongpaisan S; Vanichtanankul J; Vilaivan T; Yuthavong Y; Hannongbua S J Comput Aided Mol Des; 2009 Apr; 23(4):241-52. PubMed ID: 19156529 [TBL] [Abstract][Full Text] [Related]
8. Multicomplex-based pharmacophore modeling in conjunction with multi-target docking and molecular dynamics simulations for the identification of Manhas A; Lone MY; Jha PC J Biomol Struct Dyn; 2019 Oct; 37(16):4181-4199. PubMed ID: 30648473 [No Abstract] [Full Text] [Related]
9. Origins of the specificity of inhibitor P218 toward wild-type and mutant PfDHFR: a molecular dynamics analysis. Abbat S; Jain V; Bharatam PV J Biomol Struct Dyn; 2015 Sep; 33(9):1913-28. PubMed ID: 25333695 [TBL] [Abstract][Full Text] [Related]
10. Investigation of potential glycogen synthase kinase 3 inhibitors using pharmacophore mapping and virtual screening. Dessalew N; Bharatam PV Chem Biol Drug Des; 2006 Sep; 68(3):154-65. PubMed ID: 17062013 [TBL] [Abstract][Full Text] [Related]
11. Identification of the optimal third generation antifolate against P. falciparum and P. vivax. Hunt SY; Detering C; Varani G; Jacobus DP; Schiehser GA; Shieh HM; Nevchas I; Terpinski J; Sibley CH Mol Biochem Parasitol; 2005 Dec; 144(2):198-205. PubMed ID: 16181688 [TBL] [Abstract][Full Text] [Related]
12. A specific pharmacophore model of Aurora B kinase inhibitors and virtual screening studies based on it. Wang HY; Li LL; Cao ZX; Luo SD; Wei YQ; Yang SY Chem Biol Drug Des; 2009 Jan; 73(1):115-26. PubMed ID: 19152640 [TBL] [Abstract][Full Text] [Related]
13. Pharmacophore modeling and virtual screening for designing potential 5-lipoxygenase inhibitors. Aparoy P; Kumar Reddy K; Kalangi SK; Chandramohan Reddy T; Reddanna P Bioorg Med Chem Lett; 2010 Feb; 20(3):1013-8. PubMed ID: 20045317 [TBL] [Abstract][Full Text] [Related]
14. Target guided synthesis of 5-benzyl-2,4-diamonopyrimidines: their antimalarial activities and binding affinities to wild type and mutant dihydrofolate reductases from Plasmodium falciparum. Sirichaiwat C; Intaraudom C; Kamchonwongpaisan S; Vanichtanankul J; Thebtaranonth Y; Yuthavong Y J Med Chem; 2004 Jan; 47(2):345-54. PubMed ID: 14711307 [TBL] [Abstract][Full Text] [Related]
15. First pharmacophore model of CCR3 receptor antagonists and its homology model-assisted, stepwise virtual screening. Jain V; Saravanan P; Arvind A; Mohan CG Chem Biol Drug Des; 2011 May; 77(5):373-87. PubMed ID: 21284830 [TBL] [Abstract][Full Text] [Related]
16. 3D QSAR pharmacophore based virtual screening and molecular docking for identification of potential HSP90 inhibitors. Sakkiah S; Thangapandian S; John S; Kwon YJ; Lee KW Eur J Med Chem; 2010 Jun; 45(6):2132-40. PubMed ID: 20206418 [TBL] [Abstract][Full Text] [Related]
17. Stoichiometric selection of tight-binding inhibitors by wild-type and mutant forms of malarial (Plasmodium falciparum) dihydrofolate reductase. Kamchonwongpaisan S; Vanichtanankul J; Tarnchompoo B; Yuvaniyama J; Taweechai S; Yuthavong Y Anal Chem; 2005 Mar; 77(5):1222-7. PubMed ID: 15732900 [TBL] [Abstract][Full Text] [Related]
18. The discovery of novel vascular endothelial growth factor receptor tyrosine kinases inhibitors: pharmacophore modeling, virtual screening and docking studies. Yu H; Wang Z; Zhang L; Zhang J; Huang Q Chem Biol Drug Des; 2007 Mar; 69(3):204-11. PubMed ID: 17441906 [TBL] [Abstract][Full Text] [Related]
19. Pharmacophore modeling and virtual screening for designing potential PLK1 inhibitors. Wang HY; Cao ZX; Li LL; Jiang PD; Zhao YL; Luo SD; Yang L; Wei YQ; Yang SY Bioorg Med Chem Lett; 2008 Sep; 18(18):4972-7. PubMed ID: 18762425 [TBL] [Abstract][Full Text] [Related]
20. Basis for antifolate action and resistance in malaria. Yuthavong Y Microbes Infect; 2002 Feb; 4(2):175-82. PubMed ID: 11880049 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]