163 related articles for article (PubMed ID: 16256072)
1. Non-linear quantitative structure-activity relationship for adenine derivatives as competitive inhibitors of adenosine deaminase.
Sadat Hayatshahi SH; Abdolmaleki P; Safarian S; Khajeh K
Biochem Biophys Res Commun; 2005 Dec; 338(2):1137-42. PubMed ID: 16256072
[TBL] [Abstract][Full Text] [Related]
2. QSARs and activity predicting models for competitive inhibitors of adenosine deaminase.
Sadat Hayatshahi SH; Abdolmaleki P; Ghiasi M; Safarian S
FEBS Lett; 2007 Feb; 581(3):506-14. PubMed ID: 17250831
[TBL] [Abstract][Full Text] [Related]
3. QSAR analysis for ADA upon interaction with a series of adenine derivatives as inhibitors.
Moosavi-Movahedi AA; Safarian S; Hakimelahi GH; Ataei G; Ajloo D; Panjehpour S; Riahi S; Mousavi MF; Mardanyan S; Soltani N; Khalafi-Nezhad A; Sharghi H; Moghadamnia H; Saboury AA
Nucleosides Nucleotides Nucleic Acids; 2004; 23(3):613-24. PubMed ID: 15113027
[TBL] [Abstract][Full Text] [Related]
4. Anticancer activity of selected phenolic compounds: QSAR studies using ridge regression and neural networks.
Nandi S; Vracko M; Bagchi MC
Chem Biol Drug Des; 2007 Nov; 70(5):424-36. PubMed ID: 17949360
[TBL] [Abstract][Full Text] [Related]
5. Predictive QSAR modeling of HIV reverse transcriptase inhibitor TIBO derivatives.
Mandal AS; Roy K
Eur J Med Chem; 2009 Apr; 44(4):1509-24. PubMed ID: 18760864
[TBL] [Abstract][Full Text] [Related]
6. QSAR modeling of the inhibition of glycogen synthase kinase-3.
Katritzky AR; Pacureanu LM; Dobchev DA; Fara DC; Duchowicz PR; Karelson M
Bioorg Med Chem; 2006 Jul; 14(14):4987-5002. PubMed ID: 16650999
[TBL] [Abstract][Full Text] [Related]
7. A neural networks-based drug discovery approach and its application for designing aldose reductase inhibitors.
Hu L; Chen G; Chau RM
J Mol Graph Model; 2006 Jan; 24(4):244-53. PubMed ID: 16226911
[TBL] [Abstract][Full Text] [Related]
8. QSAR modeling of human serum protein binding with several modeling techniques utilizing structure-information representation.
Votano JR; Parham M; Hall LM; Hall LH; Kier LB; Oloff S; Tropsha A
J Med Chem; 2006 Nov; 49(24):7169-81. PubMed ID: 17125269
[TBL] [Abstract][Full Text] [Related]
9. Conformational change of adenosine deaminase during ligand-exchange in a crystal.
Kinoshita T; Tada T; Nakanishi I
Biochem Biophys Res Commun; 2008 Aug; 373(1):53-7. PubMed ID: 18549808
[TBL] [Abstract][Full Text] [Related]
10. Development of linear, ensemble, and nonlinear models for the prediction and interpretation of the biological activity of a set of PDGFR inhibitors.
Guha R; Jurs PC
J Chem Inf Comput Sci; 2004; 44(6):2179-89. PubMed ID: 15554688
[TBL] [Abstract][Full Text] [Related]
11. Structure-activity relationships in purine-based inhibitor binding to HSP90 isoforms.
Wright L; Barril X; Dymock B; Sheridan L; Surgenor A; Beswick M; Drysdale M; Collier A; Massey A; Davies N; Fink A; Fromont C; Aherne W; Boxall K; Sharp S; Workman P; Hubbard RE
Chem Biol; 2004 Jun; 11(6):775-85. PubMed ID: 15217611
[TBL] [Abstract][Full Text] [Related]
12. Feature selection and linear/nonlinear regression methods for the accurate prediction of glycogen synthase kinase-3beta inhibitory activities.
Goodarzi M; Freitas MP; Jensen R
J Chem Inf Model; 2009 Apr; 49(4):824-32. PubMed ID: 19338295
[TBL] [Abstract][Full Text] [Related]
13. A highly potent non-nucleoside adenosine deaminase inhibitor: efficient drug discovery by intentional lead hybridization.
Terasaka T; Kinoshita T; Kuno M; Nakanishi I
J Am Chem Soc; 2004 Jan; 126(1):34-5. PubMed ID: 14709046
[TBL] [Abstract][Full Text] [Related]
14. A rapid computational filter for cytochrome P450 1A2 inhibition potential of compound libraries.
Chohan KK; Paine SW; Mistry J; Barton P; Davis AM
J Med Chem; 2005 Aug; 48(16):5154-61. PubMed ID: 16078835
[TBL] [Abstract][Full Text] [Related]
15. QSAR models for 2-amino-6-arylsulfonylbenzonitriles and congeners HIV-1 reverse transcriptase inhibitors based on linear and nonlinear regression methods.
Hu R; Doucet JP; Delamar M; Zhang R
Eur J Med Chem; 2009 May; 44(5):2158-71. PubMed ID: 19054595
[TBL] [Abstract][Full Text] [Related]
16. QSAR study of heparanase inhibitors activity using artificial neural networks and Levenberg-Marquardt algorithm.
Jalali-Heravi M; Asadollahi-Baboli M; Shahbazikhah P
Eur J Med Chem; 2008 Mar; 43(3):548-56. PubMed ID: 17602800
[TBL] [Abstract][Full Text] [Related]
17. Benchmarking of linear and nonlinear approaches for quantitative structure-property relationship studies of metal complexation with ionophores.
Tetko IV; Solov'ev VP; Antonov AV; Yao X; Doucet JP; Fan B; Hoonakker F; Fourches D; Jost P; Lachiche N; Varnek A
J Chem Inf Model; 2006; 46(2):808-19. PubMed ID: 16563012
[TBL] [Abstract][Full Text] [Related]
18. Unified QSAR approach to antimicrobials. Part 3: first multi-tasking QSAR model for input-coded prediction, structural back-projection, and complex networks clustering of antiprotozoal compounds.
Prado-Prado FJ; González-Díaz H; de la Vega OM; Ubeira FM; Chou KC
Bioorg Med Chem; 2008 Jun; 16(11):5871-80. PubMed ID: 18485714
[TBL] [Abstract][Full Text] [Related]
19. Structure-based approach to pharmacophore identification, in silico screening, and three-dimensional quantitative structure-activity relationship studies for inhibitors of Trypanosoma cruzi dihydrofolate reductase function.
Schormann N; Senkovich O; Walker K; Wright DL; Anderson AC; Rosowsky A; Ananthan S; Shinkre B; Velu S; Chattopadhyay D
Proteins; 2008 Dec; 73(4):889-901. PubMed ID: 18536013
[TBL] [Abstract][Full Text] [Related]
20. QSAR modeling of anti-invasive activity of organic compounds using structural descriptors.
Katritzky AR; Kuanar M; Dobchev DA; Vanhoecke BW; Karelson M; Parmar VS; Stevens CV; Bracke ME
Bioorg Med Chem; 2006 Oct; 14(20):6933-9. PubMed ID: 16908166
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]