159 related articles for article (PubMed ID: 11784144)
1. New approach to pharmacophore mapping and QSAR analysis using inductive logic programming. Application to thermolysin inhibitors and glycogen phosphorylase B inhibitors.
Marchand-Geneste N; Watson KA; Alsberg BK; King RD
J Med Chem; 2002 Jan; 45(2):399-409. PubMed ID: 11784144
[TBL] [Abstract][Full Text] [Related]
2. The discovery of indicator variables for QSAR using inductive logic programming.
King RD; Srinivasan A
J Comput Aided Mol Des; 1997 Nov; 11(6):571-80. PubMed ID: 9491349
[TBL] [Abstract][Full Text] [Related]
3. DrugScore meets CoMFA: adaptation of fields for molecular comparison (AFMoC) or how to tailor knowledge-based pair-potentials to a particular protein.
Gohlke H; Klebe G
J Med Chem; 2002 Sep; 45(19):4153-70. PubMed ID: 12213058
[TBL] [Abstract][Full Text] [Related]
4. Three-dimensional quantitative structure-activity relationship of angiotesin-converting enzyme and thermolysin inhibitors. II. A comparison of CoMFA models incorporating molecular orbital fields and desolvation free energies based on active-analog and complementary-receptor-field alignment rules.
Waller CL; Marshall GR
J Med Chem; 1993 Aug; 36(16):2390-403. PubMed ID: 8360884
[TBL] [Abstract][Full Text] [Related]
5. Structural investigations of anthranilimide derivatives by CoMFA and CoMSIA 3D-QSAR studies reveal novel insight into their structures toward glycogen phosphorylase inhibition.
Saqib U; Kumar B; Siddiqi MI
SAR QSAR Environ Res; 2011; 22(5-6):411-49. PubMed ID: 21607894
[TBL] [Abstract][Full Text] [Related]
6. Local indices for similarity analysis (LISA)-a 3D-QSAR formalism based on local molecular similarity.
Verma J; Malde A; Khedkar S; Iyer R; Coutinho E
J Chem Inf Model; 2009 Dec; 49(12):2695-707. PubMed ID: 19994892
[TBL] [Abstract][Full Text] [Related]
7. Quantitative structure-based design: formalism and application of receptor-dependent RD-4D-QSAR analysis to a set of glucose analogue inhibitors of glycogen phosphorylase.
Pan D; Tseng Y; Hopfinger AJ
J Chem Inf Comput Sci; 2003; 43(5):1591-607. PubMed ID: 14502494
[TBL] [Abstract][Full Text] [Related]
8. Inhibitory mode of indole-2-carboxamide derivatives against HLGPa: molecular docking and 3D-QSAR analyses.
Liu G; Zhang Z; Luo X; Shen J; Liu H; Shen X; Chen K; Jiang H
Bioorg Med Chem; 2004 Aug; 12(15):4147-57. PubMed ID: 15246091
[TBL] [Abstract][Full Text] [Related]
9. Evaluation of designed ligands by a multiple screening method: application to glycogen phosphorylase inhibitors constructed with a variety of approaches.
So SS; Karplus M
J Comput Aided Mol Des; 2001 Jul; 15(7):613-47. PubMed ID: 11688944
[TBL] [Abstract][Full Text] [Related]
10. How good are ensembles in improving QSAR models? The case with eCoRIA.
Khedkar VM; Joseph J; Pissurlenkar R; Saran A; Coutinho EC
J Biomol Struct Dyn; 2015; 33(4):749-69. PubMed ID: 24754910
[TBL] [Abstract][Full Text] [Related]
11. Rational procedure for 3D-QSAR analysis using TRNOE experiments and computational methods: application to thermolysin inhibitors.
Radwan AA; Gouda H; Yamaotsu N; Torigoe H; Hirono S
Drug Des Discov; 2001; 17(3):265-81. PubMed ID: 11469756
[TBL] [Abstract][Full Text] [Related]
12. Mapping the binding site of a large set of quinazoline type EGF-R inhibitors using molecular field analyses and molecular docking studies.
Hou T; Zhu L; Chen L; Xu X
J Chem Inf Comput Sci; 2003; 43(1):273-87. PubMed ID: 12546563
[TBL] [Abstract][Full Text] [Related]
13. A general approach for developing system-specific functions to score protein-ligand docked complexes using support vector inductive logic programming.
Amini A; Shrimpton PJ; Muggleton SH; Sternberg MJ
Proteins; 2007 Dec; 69(4):823-31. PubMed ID: 17910057
[TBL] [Abstract][Full Text] [Related]
14. Ligand-based modelling followed by synthetic exploration unveil novel glycogen phosphorylase inhibitory leads.
Habash M; Taha MO
Bioorg Med Chem; 2011 Aug; 19(16):4746-71. PubMed ID: 21788139
[TBL] [Abstract][Full Text] [Related]
15. Outliers in SAR and QSAR: 4. effects of allosteric protein-ligand interactions on the classical quantitative structure-activity relationships.
Kim KH
Mol Divers; 2022 Dec; 26(6):3057-3092. PubMed ID: 35192113
[TBL] [Abstract][Full Text] [Related]
16. Prediction of ligand-receptor binding thermodynamics by free energy force field three-dimensional quantitative structure-activity relationship analysis: applications to a set of glucose analogue inhibitors of glycogen phosphorylase.
Venkatarangan P; Hopfinger AJ
J Med Chem; 1999 Jun; 42(12):2169-79. PubMed ID: 10377222
[TBL] [Abstract][Full Text] [Related]
17. Identification of pentacyclic triterpenes derivatives as potent inhibitors against glycogen phosphorylase based on 3D-QSAR studies.
Liang Z; Zhang L; Li L; Liu J; Li H; Zhang L; Chen L; Cheng K; Zheng M; Wen X; Zhang P; Hao J; Gong Y; Zhang X; Zhu X; Chen J; Liu H; Jiang H; Luo C; Sun H
Eur J Med Chem; 2011 Jun; 46(6):2011-21. PubMed ID: 21439694
[TBL] [Abstract][Full Text] [Related]
18. Discovering benzamide derivatives as glycogen phosphorylase inhibitors and their binding site at the enzyme.
Chen L; Li H; Liu J; Zhang L; Liu H; Jiang H
Bioorg Med Chem; 2007 Nov; 15(21):6763-74. PubMed ID: 17719791
[TBL] [Abstract][Full Text] [Related]
19. Fuzzy tricentric pharmacophore fingerprints. 2. Application of topological fuzzy pharmacophore triplets in quantitative structure-activity relationships.
Bonachéra F; Horvath D
J Chem Inf Model; 2008 Feb; 48(2):409-25. PubMed ID: 18254617
[TBL] [Abstract][Full Text] [Related]
20. A comparative study of ligand-receptor complex binding affinity prediction methods based on glycogen phosphorylase inhibitors.
So SS; Karplus M
J Comput Aided Mol Des; 1999 May; 13(3):243-58. PubMed ID: 10216832
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]