227 related articles for article (PubMed ID: 33734039)
41. Targeting the NF-κB/IκBα complex via fragment-based E-Pharmacophore virtual screening and binary QSAR models.
Kanan T; Kanan D; Erol I; Yazdi S; Stein M; Durdagi S
J Mol Graph Model; 2019 Jan; 86():264-277. PubMed ID: 30415122
[TBL] [Abstract][Full Text] [Related]
42. Discovery of newer pyrazole derivatives with potential anti-tubercular activity via 3D-QSAR based pharmacophore modelling, virtual screening, molecular docking and molecular dynamics simulation studies.
Modi P; Patel S; Chhabria M
Mol Divers; 2023 Aug; 27(4):1547-1566. PubMed ID: 35969333
[TBL] [Abstract][Full Text] [Related]
43. Combinatorial Pharmacophore-Based 3D-QSAR Analysis and Virtual Screening of FGFR1 Inhibitors.
Zhou N; Xu Y; Liu X; Wang Y; Peng J; Luo X; Zheng M; Chen K; Jiang H
Int J Mol Sci; 2015 Jun; 16(6):13407-26. PubMed ID: 26110383
[TBL] [Abstract][Full Text] [Related]
44. Screening of inhibitors as potential remedial against Ebolavirus infection: pharmacophore-based approach.
Sankar M; K L; Jeyachandran S; Pandi B
J Biomol Struct Dyn; 2021 Feb; 39(2):395-408. PubMed ID: 31928158
[TBL] [Abstract][Full Text] [Related]
45. Pharmacophore-based drug design for the identification of novel butyrylcholinesterase inhibitors against Alzheimer's disease.
Jiang Y; Gao H
Phytomedicine; 2019 Feb; 54():278-290. PubMed ID: 30668379
[TBL] [Abstract][Full Text] [Related]
46. Investigation of non-hydroxamate scaffolds against HDAC6 inhibition: A pharmacophore modeling, molecular docking, and molecular dynamics simulation approach.
Zeb A; Park C; Son M; Rampogu S; Alam SI; Park SJ; Lee KW
J Bioinform Comput Biol; 2018 Jun; 16(3):1840015. PubMed ID: 29945500
[TBL] [Abstract][Full Text] [Related]
47. Ligand-based pharmacophore modelling and virtual screening for the identification of amyloid-beta diagnostic molecules.
Marondedze EF; Govender KK; Govender PP
J Mol Graph Model; 2020 Dec; 101():107711. PubMed ID: 32898834
[TBL] [Abstract][Full Text] [Related]
48. Structure-guided Design and Optimization of small Molecules as Pancreatic Lipase Inhibitors using Pharmacophore, 3D-QSAR, Molecular Docking, and Molecular Dynamics Simulation Studies.
Modanwal S; Mulpuru V; Mishra N
Curr Comput Aided Drug Des; 2023; 19(4):258-277. PubMed ID: 36597611
[TBL] [Abstract][Full Text] [Related]
49. A mechanistic approach to explore novel HDAC1 inhibitor using pharmacophore modeling, 3D- QSAR analysis, molecular docking, density functional and molecular dynamics simulation study.
Choubey SK; Jeyaraman J
J Mol Graph Model; 2016 Nov; 70():54-69. PubMed ID: 27668885
[TBL] [Abstract][Full Text] [Related]
50. An insight into selective and potent inhibition of histone deacetylase 8 through induced-fit docking, pharmacophore modeling and QSAR studies.
Kashyap K; Kakkar R
J Biomol Struct Dyn; 2020 Jan; 38(1):48-65. PubMed ID: 30633630
[TBL] [Abstract][Full Text] [Related]
51. Estrogen receptor potentially stable conformations from molecular dynamics as a structure-based pharmacophore model for mapping, screening, and identifying ligands-a new paradigm shift in pharmacophore screening.
Shanmugarajan D; David C
J Biomol Struct Dyn; 2023 Jul; 41(11):4939-4948. PubMed ID: 35543232
[TBL] [Abstract][Full Text] [Related]
52. 3D QSAR, Docking, Molecular Dynamics Simulations and MM-GBSA studies of Extended Side Chain of the Antitubercular Drug (6S) 2-Nitro-6- {[4-(trifluoromethoxy) benzyl] oxy}-6,7-dihydro-5H-imidazo[2,1-b] [1,3] oxazine.
Chaudhari HK; Pahelkar A
Infect Disord Drug Targets; 2019; 19(2):145-166. PubMed ID: 30324898
[TBL] [Abstract][Full Text] [Related]
53. Proposing novel TNFα direct inhibitor Scaffolds using fragment-docking based e-pharmacophore modeling and binary QSAR-based virtual screening protocols pipeline.
Zaka M; Abbasi BH; Durdagi S
J Mol Graph Model; 2018 Oct; 85():111-121. PubMed ID: 30149308
[TBL] [Abstract][Full Text] [Related]
54. 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]
55. Discovery of potent Camkk1 kinase inhibitors through e-pharmacophore and molecular screening approaches.
Prajisha J; Biswal J; Jeyakanthan J
J Biomol Struct Dyn; 2022 Apr; 40(6):2740-2756. PubMed ID: 33155526
[TBL] [Abstract][Full Text] [Related]
56. In silico analysis of marine natural product for protein arginine methyltransferase 5(PRMT5) inhibitors based on pharmacophore and molecular docking.
Luo L; Tan H; Liao Y
J Biomol Struct Dyn; 2023; 41(22):13180-13197. PubMed ID: 36856049
[TBL] [Abstract][Full Text] [Related]
57. Ligand-based pharmacophore modeling of TNF-α to design novel inhibitors using virtual screening and molecular dynamics.
Jade DD; Pandey R; Kumar R; Gupta D
J Biomol Struct Dyn; 2022 Mar; 40(4):1702-1718. PubMed ID: 33034255
[TBL] [Abstract][Full Text] [Related]
58.
Hammoudi NE; Benguerba Y; Attoui A; Hognon C; Lemaoui T; Sobhi W; Benaicha M; Badawi M; Monari A
J Biomol Struct Dyn; 2022 Feb; 40(2):886-902. PubMed ID: 32948119
[TBL] [Abstract][Full Text] [Related]
59.
Akabli T; Toufik H; Lamchouri F
J Biomol Struct Dyn; 2022 Jun; 40(9):3965-3978. PubMed ID: 33252029
[TBL] [Abstract][Full Text] [Related]
60. Pharmacophore-guided fragment-based design of novel mammalian target of rapamycin inhibitors: extra precision docking, fingerprint-based 2D and atom-based 3D-QSAR modelling.
Kumar A; Rai S; Rathi E; Agarwal P; Kini SG
J Biomol Struct Dyn; 2021 Mar; 39(4):1155-1173. PubMed ID: 32037974
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]