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Journal Abstract Search
176 related items for PubMed ID: 20094871
1. Computer-based analysis, visualization, and interpretation of antimicrobial peptide activities. Mikut R. Methods Mol Biol; 2010; 618():287-99. PubMed ID: 20094871 [Abstract] [Full Text] [Related]
2. Methods for building quantitative structure-activity relationship (QSAR) descriptors and predictive models for computer-aided design of antimicrobial peptides. Taboureau O. Methods Mol Biol; 2010; 618():77-86. PubMed ID: 20094859 [Abstract] [Full Text] [Related]
3. Short linear cationic antimicrobial peptides: screening, optimizing, and prediction. Hilpert K, Fjell CD, Cherkasov A. Methods Mol Biol; 2008; 494():127-59. PubMed ID: 18726572 [Abstract] [Full Text] [Related]
4. Sequence requirements and an optimization strategy for short antimicrobial peptides. Hilpert K, Elliott MR, Volkmer-Engert R, Henklein P, Donini O, Zhou Q, Winkler DF, Hancock RE. Chem Biol; 2006 Oct; 13(10):1101-7. PubMed ID: 17052614 [Abstract] [Full Text] [Related]
5. Design of novispirin antimicrobial peptides by quantitative structure-activity relationship. Taboureau O, Olsen OH, Nielsen JD, Raventos D, Mygind PH, Kristensen HH. Chem Biol Drug Des; 2006 Jul; 68(1):48-57. PubMed ID: 16923026 [Abstract] [Full Text] [Related]
6. QSAR modeling and computer-aided design of antimicrobial peptides. Jenssen H, Fjell CD, Cherkasov A, Hancock RE. J Pept Sci; 2008 Jan; 14(1):110-4. PubMed ID: 17847019 [Abstract] [Full Text] [Related]
8. Quantitative sequence-activity modeling of antimicrobial hexapeptides using a segmented principal component strategy: an approach to describe and predict activities of peptide drugs containing L/D and unnatural residues. Yousefinejad S, Bagheri M, Moosavi-Movahedi AA. Amino Acids; 2015 Jan; 47(1):125-34. PubMed ID: 25323737 [Abstract] [Full Text] [Related]
9. Coupling molecular dynamics simulations with experiments for the rational design of indolicidin-analogous antimicrobial peptides. Tsai CW, Hsu NY, Wang CH, Lu CY, Chang Y, Tsai HH, Ruaan RC. J Mol Biol; 2009 Sep 25; 392(3):837-54. PubMed ID: 19576903 [Abstract] [Full Text] [Related]
10. Strategies for transformation of naturally-occurring amphibian antimicrobial peptides into therapeutically valuable anti-infective agents. Conlon JM, Al-Ghaferi N, Abraham B, Leprince J. Methods; 2007 Aug 25; 42(4):349-57. PubMed ID: 17560323 [Abstract] [Full Text] [Related]
11. Structure-activity relations of parasin I, a histone H2A-derived antimicrobial peptide. Koo YS, Kim JM, Park IY, Yu BJ, Jang SA, Kim KS, Park CB, Cho JH, Kim SC. Peptides; 2008 Jul 25; 29(7):1102-8. PubMed ID: 18406495 [Abstract] [Full Text] [Related]
12. The expanding scope of antimicrobial peptide structures and their modes of action. Nguyen LT, Haney EF, Vogel HJ. Trends Biotechnol; 2011 Sep 25; 29(9):464-72. PubMed ID: 21680034 [Abstract] [Full Text] [Related]
16. Optimal selection of molecular descriptors for antimicrobial peptides classification: an evolutionary feature weighting approach. Beltran JA, Aguilera-Mendoza L, Brizuela CA. BMC Genomics; 2018 Sep 24; 19(Suppl 7):672. PubMed ID: 30255784 [Abstract] [Full Text] [Related]
17. Convergent evolution-guided design of antimicrobial peptides derived from influenza A virus hemagglutinin. Zhu S, Aumelas A, Gao B. J Med Chem; 2011 Feb 24; 54(4):1091-5. PubMed ID: 21222457 [Abstract] [Full Text] [Related]
18. Identification of novel antibacterial peptides by chemoinformatics and machine learning. Fjell CD, Jenssen H, Hilpert K, Cheung WA, Panté N, Hancock RE, Cherkasov A. J Med Chem; 2009 Apr 09; 52(7):2006-15. PubMed ID: 19296598 [Abstract] [Full Text] [Related]