531 related articles for article (PubMed ID: 27981900)
1. Pharmacophore and Docking Guided Virtual Screening Study for Discovery of Type I Inhibitors of VEGFR-2 Kinase.
Bhojwani HR; Joshi UJ
Curr Comput Aided Drug Des; 2017; 13(3):186-207. PubMed ID: 27981900
[TBL] [Abstract][Full Text] [Related]
2. In silico exploration of c-KIT inhibitors by pharmaco-informatics methodology: pharmacophore modeling, 3D QSAR, docking studies, and virtual screening.
Chaudhari P; Bari S
Mol Divers; 2016 Feb; 20(1):41-53. PubMed ID: 26416560
[TBL] [Abstract][Full Text] [Related]
3. Molecular dynamics guided insight, binding free energy calculations and pharmacophore-based virtual screening for the identification of potential VEGFR2 inhibitors.
Rathi E; Kumar A; Kini SG
J Recept Signal Transduct Res; 2019; 39(5-6):415-433. PubMed ID: 31755336
[TBL] [Abstract][Full Text] [Related]
4. 3D-QSAR pharmacophore modelling, virtual screening and docking studies for lead discovery of a novel scaffold for VEGFR 2 inhibitors: Design, synthesis and biological evaluation.
Sobhy MK; Mowafy S; Lasheen DS; Farag NA; Abouzid KAM
Bioorg Chem; 2019 Aug; 89():102988. PubMed ID: 31146197
[TBL] [Abstract][Full Text] [Related]
5. Ligand-based and e-pharmacophore modeling, 3D-QSAR and hierarchical virtual screening to identify dual inhibitors of spleen tyrosine kinase (Syk) and janus kinase 3 (JAK3).
Kaur M; Silakari O
J Biomol Struct Dyn; 2017 Nov; 35(14):3043-3060. PubMed ID: 27678281
[TBL] [Abstract][Full Text] [Related]
6. Structural Investigation of Vinca Domain Tubulin Binders by Pharmacophore, Atom based QSAR, Docking and Molecular Dynamics Simulations.
Athar M; Lone MY; Khedkar VM; Radadiya A; Shah A; Jha PC
Comb Chem High Throughput Screen; 2017; 20(8):682-695. PubMed ID: 28486912
[TBL] [Abstract][Full Text] [Related]
7. Identification of potential PKC inhibitors through pharmacophore designing, 3D-QSAR and molecular dynamics simulations targeting Alzheimer's disease.
Iqbal S; Anantha Krishnan D; Gunasekaran K
J Biomol Struct Dyn; 2018 Nov; 36(15):4029-4044. PubMed ID: 29182053
[TBL] [Abstract][Full Text] [Related]
8. Pharmacophore based virtual screening for identification of effective inhibitors to combat HPV 16 E6 driven cervical cancer.
Mohan A; Krishnamoorthy S; Sabanayagam R; Schwenk G; Feng E; Ji HF; Muthusami S
Eur J Pharmacol; 2023 Oct; 957():175961. PubMed ID: 37549730
[TBL] [Abstract][Full Text] [Related]
9. Recent advances in structure-based drug design and virtual screening of VEGFR tyrosine kinase inhibitors.
Hoi PM; Li S; Vong CT; Tseng HH; Kwan YW; Lee SM
Methods; 2015 Jan; 71():85-91. PubMed ID: 25239735
[TBL] [Abstract][Full Text] [Related]
10. In silico insights into the identification of potential novel angiogenic inhibitors against human VEGFR-2: a new SAR-based hierarchical clustering approach.
Konidala KK; Bommu UD; Pabbaraju N
J Recept Signal Transduct Res; 2018 Aug; 38(4):372-383. PubMed ID: 30396316
[TBL] [Abstract][Full Text] [Related]
11. Pharmacophore modeling, virtual screening, docking and in silico ADMET analysis of protein kinase B (PKB β) inhibitors.
Vyas VK; Ghate M; Goel A
J Mol Graph Model; 2013 May; 42():17-25. PubMed ID: 23507201
[TBL] [Abstract][Full Text] [Related]
12. Discovery of Camptothecin Based Topoisomerase I Inhibitors: Identification Using an Atom Based 3D-QSAR, Pharmacophore Modeling, Virtual Screening and Molecular Docking Approach.
Dev S; Dhaneshwar SR; Mathew B
Comb Chem High Throughput Screen; 2016; 19(9):752-763. PubMed ID: 27515040
[TBL] [Abstract][Full Text] [Related]
13. Pharmacophore generation, atom-based 3D-QSAR, molecular docking and molecular dynamics simulation studies on benzamide analogues as FtsZ inhibitors.
Tripathy S; Azam MA; Jupudi S; Sahu SK
J Biomol Struct Dyn; 2018 Sep; 36(12):3218-3230. PubMed ID: 28938860
[TBL] [Abstract][Full Text] [Related]
14. Pharmacophore modeling, multiple docking, and molecular dynamics studies on Wee1 kinase inhibitors.
Hu Y; Zhou L; Zhu X; Dai D; Bao Y; Qiu Y
J Biomol Struct Dyn; 2019 Jul; 37(10):2703-2715. PubMed ID: 30052133
[TBL] [Abstract][Full Text] [Related]
15. Pharmacophore modeling and virtual screening studies for new VEGFR-2 kinase inhibitors.
Lee K; Jeong KW; Lee Y; Song JY; Kim MS; Lee GS; Kim Y
Eur J Med Chem; 2010 Nov; 45(11):5420-7. PubMed ID: 20869793
[TBL] [Abstract][Full Text] [Related]
16. Structure-based identification of potent VEGFR-2 inhibitors from in vivo metabolites of a herbal ingredient.
Dash R; Junaid M; Mitra S; Arifuzzaman M; Hosen SMZ
J Mol Model; 2019 Mar; 25(4):98. PubMed ID: 30904971
[TBL] [Abstract][Full Text] [Related]
17. Exploration of the structural requirements of HIV-protease inhibitors using pharmacophore, virtual screening and molecular docking approaches for lead identification.
Islam MA; Pillay TS
J Mol Graph Model; 2015 Mar; 56():20-30. PubMed ID: 25541527
[TBL] [Abstract][Full Text] [Related]
18. An integrated virtual screening approach for VEGFR-2 inhibitors.
Zhang Y; Yang S; Jiao Y; Liu H; Yuan H; Lu S; Ran T; Yao S; Ke Z; Xu J; Xiong X; Chen Y; Lu T
J Chem Inf Model; 2013 Dec; 53(12):3163-77. PubMed ID: 24266594
[TBL] [Abstract][Full Text] [Related]
19. Identification of novel PI3Kδ inhibitors by docking, ADMET prediction and molecular dynamics simulations.
Liu YY; Feng XY; Jia WQ; Jing Z; Xu WR; Cheng XC
Comput Biol Chem; 2019 Feb; 78():190-204. PubMed ID: 30557817
[TBL] [Abstract][Full Text] [Related]
20. Epidermal growth factor receptor (EGFR) structure-based bioactive pharmacophore models for identifying next-generation inhibitors against clinically relevant EGFR mutations.
Panicker PS; Melge AR; Biswas L; Keechilat P; Mohan CG
Chem Biol Drug Des; 2017 Oct; 90(4):629-636. PubMed ID: 28303669
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]