115 related articles for article (PubMed ID: 30037283)
1. A binary QSAR model for classifying neuraminidase inhibitors of influenza A viruses (H1N1) using the combined minimum redundancy maximum relevancy criterion with the sparse support vector machine.
Qasim MK; Algamal ZY; Ali HTM
SAR QSAR Environ Res; 2018 Jul; 29(7):517-527. PubMed ID: 30037283
[TBL] [Abstract][Full Text] [Related]
2. A QSAR classification model for neuraminidase inhibitors of influenza A viruses (H1N1) based on weighted penalized support vector machine.
Algamal ZY; Qasim MK; Ali HTM
SAR QSAR Environ Res; 2017 May; 28(5):415-426. PubMed ID: 28539063
[TBL] [Abstract][Full Text] [Related]
3. QSAR model for predicting neuraminidase inhibitors of influenza A viruses (H1N1) based on adaptive grasshopper optimization algorithm.
Algamal ZY; Qasim MK; Lee MH; Ali HTM
SAR QSAR Environ Res; 2020 Nov; 31(11):803-814. PubMed ID: 32938208
[TBL] [Abstract][Full Text] [Related]
4. Using Support Vector Machine (SVM) for Classification of Selectivity of H1N1 Neuraminidase Inhibitors.
Li Y; Kong Y; Zhang M; Yan A; Liu Z
Mol Inform; 2016 Apr; 35(3-4):116-24. PubMed ID: 27491921
[TBL] [Abstract][Full Text] [Related]
5. A robust quantitative structure-activity relationship modelling of influenza neuraminidase a/PR/8/34 (H1N1) inhibitors based on the rank-bridge estimator.
Al-Dabbagh ZT; Algamal ZY
SAR QSAR Environ Res; 2019 Jun; 30(6):417-428. PubMed ID: 31122071
[TBL] [Abstract][Full Text] [Related]
6. Discovery of Influenza A virus neuraminidase inhibitors using support vector machine and Naïve Bayesian models.
Lian W; Fang J; Li C; Pang X; Liu AL; Du GH
Mol Divers; 2016 May; 20(2):439-51. PubMed ID: 26689205
[TBL] [Abstract][Full Text] [Related]
7. QSAR study of flavonoids and biflavonoids as influenza H1N1 virus neuraminidase inhibitors.
Mercader AG; Pomilio AB
Eur J Med Chem; 2010 May; 45(5):1724-30. PubMed ID: 20116898
[TBL] [Abstract][Full Text] [Related]
8. Insights into susceptibility of antiviral drugs against the E119G mutant of 2009 influenza A (H1N1) neuraminidase by molecular dynamics simulations and free energy calculations.
Pan P; Li L; Li Y; Li D; Hou T
Antiviral Res; 2013 Nov; 100(2):356-64. PubMed ID: 24055835
[TBL] [Abstract][Full Text] [Related]
9. A new adaptive L1-norm for optimal descriptor selection of high-dimensional QSAR classification model for anti-hepatitis C virus activity of thiourea derivatives.
Algamal ZY; Lee MH
SAR QSAR Environ Res; 2017 Jan; 28(1):75-90. PubMed ID: 28176549
[TBL] [Abstract][Full Text] [Related]
10. Evaluation of the anti-neuraminidase activity of the traditional Chinese medicines and determination of the anti-influenza A virus effects of the neuraminidase inhibitory TCMs in vitro and in vivo.
Tian L; Wang Z; Wu H; Wang S; Wang Y; Wang Y; Xu J; Wang L; Qi F; Fang M; Yu D; Fang X
J Ethnopharmacol; 2011 Sep; 137(1):534-42. PubMed ID: 21699971
[TBL] [Abstract][Full Text] [Related]
11. Binding pattern of the long acting neuraminidase inhibitor laninamivir towards influenza A subtypes H5N1 and pandemic H1N1.
Meeprasert A; Khuntawee W; Kamlungsua K; Nunthaboot N; Rungrotmongkol T; Hannongbua S
J Mol Graph Model; 2012 Sep; 38():148-54. PubMed ID: 23079644
[TBL] [Abstract][Full Text] [Related]
12. Different neuraminidase inhibitor susceptibilities of human H1N1, H1N2, and H3N2 influenza A viruses isolated in Germany from 2001 to 2005/2006.
Bauer K; Richter M; Wutzler P; Schmidtke M
Antiviral Res; 2009 Apr; 82(1):34-41. PubMed ID: 19428593
[TBL] [Abstract][Full Text] [Related]
13. 3D QSAR and docking study of flavone derivatives as potent inhibitors of influenza H1N1 virus neuraminidase.
Gao L; Zu M; Wu S; Liu AL; Du GH
Bioorg Med Chem Lett; 2011 Oct; 21(19):5964-70. PubMed ID: 21843936
[TBL] [Abstract][Full Text] [Related]
14. QSAR study of neuraminidase inhibitors based on heuristic method and radial basis function network.
Lü WJ; Chen YL; Ma WP; Zhang XY; Luan F; Liu MC; Chen XG; Hu ZD
Eur J Med Chem; 2008 Mar; 43(3):569-76. PubMed ID: 18255197
[TBL] [Abstract][Full Text] [Related]
15. Impact assessment of the rational selection of training and test sets on the predictive ability of QSAR models.
Andrada MF; Vega-Hissi EG; Estrada MR; Garro Martinez JC
SAR QSAR Environ Res; 2017 Dec; 28(12):1011-1023. PubMed ID: 29135323
[TBL] [Abstract][Full Text] [Related]
16. On three-dimensional holographic vector of atomic interaction field analysis for influenza neuraminidase inhibitors.
Li ZS; Sun JY; Liang GZ; Lu FL; Zhu WP; Zhang MJ; Zhang Y; Yang SB; Shu M; Chen GH; Lu TT
Chem Biol Drug Des; 2009 Feb; 73(2):236-43. PubMed ID: 19207426
[TBL] [Abstract][Full Text] [Related]
17. Binding interaction analysis of the active site and its inhibitors for neuraminidase (N1 subtype) of human influenza virus by the integration of molecular docking, FMO calculation and 3D-QSAR CoMFA modeling.
Zhang Q; Yang J; Liang K; Feng L; Li S; Wan J; Xu X; Yang G; Liu D; Yang S
J Chem Inf Model; 2008 Sep; 48(9):1802-12. PubMed ID: 18707092
[TBL] [Abstract][Full Text] [Related]
18. Binding mode analysis of anti-influenza drugs in H1N1 (2009) and H5N1 influenza A virus and designing of potential H1N1 inhibitors.
Singh KhD; Kirubakaran P; Nagamani S; Karthikeyan M
Int J Comput Biol Drug Des; 2015; 8(1):1-18. PubMed ID: 25869316
[TBL] [Abstract][Full Text] [Related]
19. Promising Anti-influenza Properties of Active Constituent of Withania somnifera Ayurvedic Herb in Targeting Neuraminidase of H1N1 Influenza: Computational Study.
Cai Z; Zhang G; Tang B; Liu Y; Fu X; Zhang X
Cell Biochem Biophys; 2015 Jul; 72(3):727-39. PubMed ID: 25627548
[TBL] [Abstract][Full Text] [Related]
20. Design, in silico studies, synthesis and in vitro evaluation of oseltamivir derivatives as inhibitors of neuraminidase from influenza A virus H1N1.
Neri-Bazán RM; García-Machorro J; Méndez-Luna D; Tolentino-López LE; Martínez-Ramos F; Padilla-Martínez II; Aguilar-Faisal L; Soriano-Ursúa MA; Trujillo-Ferrara JG; Fragoso-Vázquez MJ; Barrón BL; Correa-Basurto J
Eur J Med Chem; 2017 Mar; 128():154-167. PubMed ID: 28182988
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]