BioTherapi: Bioinformatics for Therapeutic Peptides and Proteins

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1. Introduction [Peptides:Chemistry and Biology ISBN: 978-3-527-31867-4]
2. Opportunities and Challenges of Developing Peptide Drugs in the Pharmaceutical Industry [Peptides for Youth 611 : 467-469]
3. New descriptors of amino acids and their application to peptide QSAR study [Peptides 2008, 29(10):1798-1805]
4. Pharmacological Profiles of Peptide Drug Candidates for the Treatment of Alzheimers Disease [J Biol. Chem. 2003, 278(16) :13905:13911]
5. Synthetic hydrophobic peptides are substrates for P-glycoprotein and stimulate drug transport [Biochem J. 1996, 320: 421-428]
6. Application of Inductive QSAR Descriptors for Quantification of Antibacterial Activity of Cationic Polypeptides [Molecules 2004 9:1034-1052]
7. Peptide design by artificial neural networks and computer-based evolutionary search [Proc. Natl. Acad. Sci. 1998, 95:12179-12184]
9. Using multidimensional patterns of amino acid attributes for QSAR analysis of peptides [Amino Acids 2009, 37:583-591]
10. Multivariate design and evaluation of a set of RGRPQ-derived innate immunity peptides [J Biol. Chem. 2006, 281:15164-15171]
11.Development of potent gastrin-releasing peptide antagonists having a D-Pro-1I(CH2NH)-Phe-NH2 C terminus [Proc. Natl. Acad. Sci. 1993, 90:1922-1926]
12. Correlation between simulated physicochemical properties and hemolycity of protegrin-like antimicrobial peptides: Predicting experimental toxicity [Peptides 2008, 29(7):1085-1093]
13. In silico panning for a non-competitive peptide inhibitor [BMC Bioinformatics 2007, 8:1-11]
14. Identification and Rational Redesign of Peptide Ligands to CRIP1, A Novel Biomarker for Cancers [PLoS Comput Biol. 2008, 4(8)]
15. Identification of novel peptide hormones in the human proteome by hidden Markov model screening [Genome Res. 2007, 17(3):320-327]
16. A simple, yet highly accurate, QSAR model captures the complement inhibitory activity of compstatin [Bioorg Med Chem. 2007, 15(4):1638-1644]
17. On the hydrophobicity of peptides: Comparing empirical predictions of peptide log P values [Bioinformation 2006, 1(7):237-241]
18. Peptide delivery systems [Letters in Peptide Science 2002, 8: 289-294]