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Journal Abstract Search

267 related items for PubMed ID: 19053518

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  • 2. Identification of novel antitubercular compounds through hybrid virtual screening approach.
    Muddassar M, Jang JW, Hong SK, Cho YS, Kim EE, Keum KC, Oh T, Cho SN, Pae AN.
    Bioorg Med Chem; 2010 Sep 15; 18(18):6914-21. PubMed ID: 20727773
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  • 3. Fishing the target of antitubercular compounds: in silico target deconvolution model development and validation.
    Prathipati P, Ma NL, Manjunatha UH, Bender A.
    J Proteome Res; 2009 Jun 15; 8(6):2788-98. PubMed ID: 19301903
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  • 7. Knowledge based identification of potent antitubercular compounds using structure based virtual screening and structure interaction fingerprints.
    Kumar A, Chaturvedi V, Bhatnagar S, Sinha S, Siddiqi MI.
    J Chem Inf Model; 2009 Jan 15; 49(1):35-42. PubMed ID: 19063713
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  • 10. Developing an antituberculosis compounds database and data mining in the search of a motif responsible for the activity of a diverse class of antituberculosis agents.
    Prakash O, Ghosh I.
    J Chem Inf Model; 2006 Jan 15; 46(1):17-23. PubMed ID: 16426035
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  • 11. Synthesis and evaluation of nitrofuranylamides as novel antituberculosis agents.
    Tangallapally RP, Yendapally R, Lee RE, Hevener K, Jones VC, Lenaerts AJ, McNeil MR, Wang Y, Franzblau S, Lee RE.
    J Med Chem; 2004 Oct 07; 47(21):5276-83. PubMed ID: 15456272
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  • 12. Prediction of tyrosinase inhibition activity using atom-based bilinear indices.
    Marrero-Ponce Y, Khan MT, Casañola Martín GM, Ather A, Sultankhodzhaev MN, Torrens F, Rotondo R.
    ChemMedChem; 2007 Apr 07; 2(4):449-78. PubMed ID: 17366651
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  • 13. QSAR classification model for antibacterial compounds and its use in virtual screening.
    Singh N, Chaudhury S, Liu R, AbdulHameed MD, Tawa G, Wallqvist A.
    J Chem Inf Model; 2012 Oct 22; 52(10):2559-69. PubMed ID: 23013546
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  • 14. Ligand-target prediction using Winnow and naive Bayesian algorithms and the implications of overall performance statistics.
    Nigsch F, Bender A, Jenkins JL, Mitchell JB.
    J Chem Inf Model; 2008 Dec 22; 48(12):2313-25. PubMed ID: 19055411
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  • 17. Ligand-based virtual screening, parallel solution-phase and microwave-assisted synthesis as tools to identify and synthesize new inhibitors of mycobacterium tuberculosis.
    Manetti F, Magnani M, Castagnolo D, Passalacqua L, Botta M, Corelli F, Saddi M, Deidda D, De Logu A.
    ChemMedChem; 2006 Sep 22; 1(9):973-89. PubMed ID: 16892466
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  • 19. Combinatorial QSAR modeling of specificity and subtype selectivity of ligands binding to serotonin receptors 5HT1E and 5HT1F.
    Wang XS, Tang H, Golbraikh A, Tropsha A.
    J Chem Inf Model; 2008 May 22; 48(5):997-1013. PubMed ID: 18470978
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