108 related articles for article (PubMed ID: 20728251)
1. 3D-QSAR pharmacophore modeling and in silico screening of new Bcl-xl inhibitors.
Almerico AM; Tutone M; Lauria A
Eur J Med Chem; 2010 Nov; 45(11):4774-82. PubMed ID: 20728251
[TBL] [Abstract][Full Text] [Related]
2. Exploration of new scaffolds as potential MAO-A inhibitors using pharmacophore and 3D-QSAR based in silico screening.
Shelke SM; Bhosale SH; Dash RC; Suryawanshi MR; Mahadik KR
Bioorg Med Chem Lett; 2011 Apr; 21(8):2419-24. PubMed ID: 21397504
[TBL] [Abstract][Full Text] [Related]
3. Discovery of potential new InhA direct inhibitors based on pharmacophore and 3D-QSAR analysis followed by in silico screening.
Lu XY; Chen YD; Jiang YJ; You QD
Eur J Med Chem; 2009 Sep; 44(9):3718-30. PubMed ID: 19428156
[TBL] [Abstract][Full Text] [Related]
4. Targeting the BH3 domain mediated protein-protein interaction of Bcl-xL through virtual screening.
Mukherjee P; Desai P; Zhou YD; Avery M
J Chem Inf Model; 2010 May; 50(5):906-23. PubMed ID: 20392095
[TBL] [Abstract][Full Text] [Related]
5. Rational design of new class of BH3-mimetics as inhibitors of the Bcl-xL protein.
Pinto M; Orzaez Mdel M; Delgado-Soler L; Perez JJ; Rubio-Martinez J
J Chem Inf Model; 2011 Jun; 51(6):1249-58. PubMed ID: 21528891
[TBL] [Abstract][Full Text] [Related]
6. 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]
7. Pharmacophore and docking-based combined in-silico study of KDR inhibitors.
Pasha FA; Muddassar M; Neaz MM; Cho SJ
J Mol Graph Model; 2009 Aug; 28(1):54-61. PubMed ID: 19447057
[TBL] [Abstract][Full Text] [Related]
8. Pharmacophore modeling and in silico screening for new KDR kinase inhibitors.
Yu H; Wang Z; Zhang L; Zhang J; Huang Q
Bioorg Med Chem Lett; 2007 Apr; 17(8):2126-33. PubMed ID: 17306530
[TBL] [Abstract][Full Text] [Related]
9. Combined 3D-QSAR modeling and molecular docking study on 1,4-dihydroindeno[1,2-c]pyrazoles as VEGFR-2 kinase inhibitors.
Zeng H; Zhang H
J Mol Graph Model; 2010 Aug; 29(1):54-71. PubMed ID: 20471293
[TBL] [Abstract][Full Text] [Related]
10. Pharmacophore modeling and virtual screening for the discovery of new transforming growth factor-beta type I receptor (ALK5) inhibitors.
Ren JX; Li LL; Zou J; Yang L; Yang JL; Yang SY
Eur J Med Chem; 2009 Nov; 44(11):4259-65. PubMed ID: 19640613
[TBL] [Abstract][Full Text] [Related]
11. Combined 3D-QSAR modeling and molecular docking study on indolinone derivatives as inhibitors of 3-phosphoinositide-dependent protein kinase-1.
AbdulHameed MD; Hamza A; Liu J; Zhan CG
J Chem Inf Model; 2008 Sep; 48(9):1760-72. PubMed ID: 18717540
[TBL] [Abstract][Full Text] [Related]
12. Design, synthesis, and interaction study of quinazoline-2(1H)-thione derivatives as novel potential Bcl-xL inhibitors.
Feng Y; Ding X; Chen T; Chen L; Liu F; Jia X; Luo X; Shen X; Chen K; Jiang H; Wang H; Liu H; Liu D
J Med Chem; 2010 May; 53(9):3465-79. PubMed ID: 20405848
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. Pharmacophore filtering and 3D-QSAR in the discovery of new JAK2 inhibitors.
Dhanachandra Singh Kh; Karthikeyan M; Kirubakaran P; Nagamani S
J Mol Graph Model; 2011 Sep; 30():186-97. PubMed ID: 21831680
[TBL] [Abstract][Full Text] [Related]
15. Discovery of new MurF inhibitors via pharmacophore modeling and QSAR analysis followed by in-silico screening.
Taha MO; Atallah N; Al-Bakri AG; Paradis-Bleau C; Zalloum H; Younis KS; Levesque RC
Bioorg Med Chem; 2008 Feb; 16(3):1218-35. PubMed ID: 17988876
[TBL] [Abstract][Full Text] [Related]
16. A combination of in silico and SAR studies to identify binding hot spots of Bcl-xL inhibitors.
Levoin N; Vo DD; Gautier F; Barillé-Nion S; Juin P; Tasseau O; Grée R
Bioorg Med Chem; 2015 Apr; 23(8):1747-57. PubMed ID: 25797160
[TBL] [Abstract][Full Text] [Related]
17. Discovery of a potent inhibitor of the antiapoptotic protein Bcl-xL from NMR and parallel synthesis.
Petros AM; Dinges J; Augeri DJ; Baumeister SA; Betebenner DA; Bures MG; Elmore SW; Hajduk PJ; Joseph MK; Landis SK; Nettesheim DG; Rosenberg SH; Shen W; Thomas S; Wang X; Zanze I; Zhang H; Fesik SW
J Med Chem; 2006 Jan; 49(2):656-63. PubMed ID: 16420051
[TBL] [Abstract][Full Text] [Related]
18. Discovery of new renin inhibitory leads via sequential pharmacophore modeling, QSAR analysis, in silico screening and in vitro evaluation.
Al-Nadaf AH; Taha MO
J Mol Graph Model; 2011 Apr; 29(6):843-64. PubMed ID: 21376648
[TBL] [Abstract][Full Text] [Related]
19. Elucidating inhibitory models of the inhibitors of epidermal growth factor receptor by docking and 3D-QSAR.
Chen G; Luo X; Zhu W; Luo C; Liu H; Puah CM; Chen K; Jiang H
Bioorg Med Chem; 2004 May; 12(9):2409-17. PubMed ID: 15080937
[TBL] [Abstract][Full Text] [Related]
20. Modeling of diarylalkyl-imidazole and diarylalkyl-triazole derivatives as potent aromatase inhibitors for treatment of hormone-dependent cancer.
Nagar S; Saha A
J Comput Chem; 2010 Sep; 31(12):2342-53. PubMed ID: 20340106
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
