214 related articles for article (PubMed ID: 38245752)
1. Lead generation of UPPS inhibitors targeting MRSA: Using 3D-QSAR pharmacophore modeling, virtual screening, molecular docking, and molecular dynamic simulations.
Qandeel BM; Mowafy S; Abouzid K; Farag NA
BMC Chem; 2024 Jan; 18(1):14. PubMed ID: 38245752
[TBL] [Abstract][Full Text] [Related]
2. Lead generation of cysteine based mesenchymal epithelial transition (c-Met) kinase inhibitors: Using structure-based scaffold hopping, 3D-QSAR pharmacophore modeling, virtual screening, molecular docking, and molecular dynamics simulation.
Raafat A; Mowafy S; Abouseri SM; Fouad MA; Farag NA
Comput Biol Med; 2022 Jul; 146():105526. PubMed ID: 35487125
[TBL] [Abstract][Full Text] [Related]
3. 3D-QSAR pharmacophore modeling, virtual screening, molecular docking, MD simulations, in vitro and in vivo studies to identify potential anti-hyperplasia drugs.
Khan MZI; Khan D; Akbar MY; Wang H; Haq IU; Chen JZ
Biotechnol J; 2024 Feb; 19(2):e2300437. PubMed ID: 38403464
[TBL] [Abstract][Full Text] [Related]
4. Anthranilic Acid Inhibitors of Undecaprenyl Pyrophosphate Synthase (UppS), an Essential Enzyme for Bacterial Cell Wall Biosynthesis.
Jukič M; Rožman K; Sova M; Barreteau H; Gobec S
Front Microbiol; 2018; 9():3322. PubMed ID: 30692977
[TBL] [Abstract][Full Text] [Related]
5. 3D QSAR pharmacophore, CoMFA and CoMSIA based design and docking studies on phenyl alkyl ketones as inhibitors of phosphodiesterase 4.
Gaurav A; Singh R
Med Chem; 2012 Sep; 8(5):894-912. PubMed ID: 22741782
[TBL] [Abstract][Full Text] [Related]
6. Pharmacophore-based virtual screening approach for identification of potent natural modulatory compounds of human Toll-like receptor 7.
Gupta CL; Babu Khan M; Ampasala DR; Akhtar S; Dwivedi UN; Bajpai P
J Biomol Struct Dyn; 2019 Nov; 37(18):4721-4736. PubMed ID: 30661449
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. Novel chemical scaffolds of the tumor marker AKR1B10 inhibitors discovered by 3D QSAR pharmacophore modeling.
Kumar R; Son M; Bavi R; Lee Y; Park C; Arulalapperumal V; Cao GP; Kim HH; Suh JK; Kim YS; Kwon YJ; Lee KW
Acta Pharmacol Sin; 2015 Aug; 36(8):998-1012. PubMed ID: 26051108
[TBL] [Abstract][Full Text] [Related]
9. 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]
10. Identification of coumarin derivatives targeting acetylcholinesterase for Alzheimer's disease by field-based 3D-QSAR, pharmacophore model-based virtual screening, molecular docking, MM/GBSA, ADME and MD Simulation study.
Saha B; Das A; Jangid K; Kumar A; Kumar V; Jaitak V
Curr Res Struct Biol; 2024; 7():100124. PubMed ID: 38292820
[TBL] [Abstract][Full Text] [Related]
11. 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]
12. Exploration of New and Potent Lead Molecules Against CAAX Prenyl Protease I of Leishmania donovani Through Pharmacophore Based Virtual Screening Approach.
Prabhu SV; Tiwari K; Suryanarayanan V; Dubey VK; Singh SK
Comb Chem High Throughput Screen; 2017; 20(3):255-271. PubMed ID: 28116998
[TBL] [Abstract][Full Text] [Related]
13. Discovery of potential Aurora-A kinase inhibitors by 3D QSAR pharmacophore modeling, virtual screening, docking, and MD simulation studies.
Swamy P M G; Abbas N; Dhiwar PS; Singh E; Ghara A; Das A
J Biomol Struct Dyn; 2023 Jan; 41(1):125-146. PubMed ID: 34809538
[TBL] [Abstract][Full Text] [Related]
14. Identification of novel leads as potent inhibitors of HDAC3 using ligand-based pharmacophore modeling and MD simulation.
Kumbhar N; Nimal S; Barale S; Kamble S; Bavi R; Sonawane K; Gacche R
Sci Rep; 2022 Feb; 12(1):1712. PubMed ID: 35110603
[TBL] [Abstract][Full Text] [Related]
15. 3D QSAR pharmacophore-based virtual screening for the identification of potential inhibitors of tyrosinase.
Ghayas S; Ali Masood M; Parveen R; Aquib M; Farooq MA; Banerjee P; Sambhare S; Bavi R
J Biomol Struct Dyn; 2020 Jul; 38(10):2916-2927. PubMed ID: 31334690
[TBL] [Abstract][Full Text] [Related]
16. Tubulin inhibitors: pharmacophore modeling, virtual screening and molecular docking.
Niu MM; Qin JY; Tian CP; Yan XF; Dong FG; Cheng ZQ; Fida G; Yang M; Chen HY; Gu YQ
Acta Pharmacol Sin; 2014 Jul; 35(7):967-79. PubMed ID: 24909516
[TBL] [Abstract][Full Text] [Related]
17.
Vaghefinezhad N; Farsani SF; Gharaghani S
Curr Drug Discov Technol; 2021; 18(1):139-157. PubMed ID: 31721705
[TBL] [Abstract][Full Text] [Related]
18. Ligand Based Pharmacophore Modeling and Virtual Screening Studies to Design Novel HDAC2 Inhibitors.
Kandakatla N; Ramakrishnan G
Adv Bioinformatics; 2014; 2014():812148. PubMed ID: 25525429
[TBL] [Abstract][Full Text] [Related]
19. 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]
20. Discovery of novel NAMPT inhibitors based on pharmacophore modeling and virtual screening techniques.
Yi Q; Zhou L; Shao X; Wang T; Bao G; Shi H; Zhou S; Li X; Tian Y
Comb Chem High Throughput Screen; 2014; 17(10):868-78. PubMed ID: 25413783
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]