The use of synthetic peptide combinatorial libraries for the identification of bioactive peptides.
ABSTRACT The systematic preparation of synthetic peptide combinatorial libraries (SPCLs), each composed of tens of millions of peptides that can be screened in existing diagnostically or pharmacologically relevant in vitro assay systems, is reviewed. The identification of optimal peptide sequences has been achieved through the screening in solution of SPCLs, each element of which is composed of more than 100,000 nonsupport-bound peptides in equimolar representation, along with an iterative synthesis and screening process. Examples are presented in which an SPCL, composed in total of 52,128,400 acetylated hexa-peptides, is used along with an iterative selection process to precisely identify the antigenic determinant of a peptide recognized by a monoclonal antibody using competitive enzyme-linked immunosorbent assay. This same library was also used to develop highly potent antimicrobial peptides in bacterial growth inhibition assays. A separate non-acetylated SPCL was used to screen and identify high affinity peptide ligands using an opiate radio-receptor binding assay.
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ABSTRACT: The use of the harmonic mean model for predicting the activities of a given mixture and its constituents has not previously been explored in the context of combinatorial libraries and drug discovery. Herein, the analyses of historical data confirm the harmonic mean as an accurate predictor of mixture activity. The implications of these results are discussed.ACS combinatorial science. 03/2011; 13(3):337-44.
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ABSTRACT: Plasmacytoid dendritic cells (pDCs) play a major role in shaping both innate and adaptive immune responses, mainly via their production of large amounts of type I IFNs. pDCs are considered to primarily present endogenous Ags and are thought not to participate in the uptake and presentation of Ags from the extracellular environment, in contrast to their myeloid counterparts, which efficiently endocytose extracellular particulates. In this study, we show that human pDCs are able to phagocytose and process particulate forms of Ag entrapped in poly(lactic-coglycolic acid) microparticles. Furthermore, pDCs were also able to sense TLR ligands (TLR-Ls) incorporated in these particles, resulting in rapid pDC activation and high IFN-alpha secretion. Combining a tetanus toxoid peptide and TLR-Ls (CpG C and R848) in these microparticles resulted in efficient pDC activation and concomitant Ag-specific T cell stimulation. Moreover, particulate Ag was phagocytosed and presented more efficiently than soluble Ag, indicating that microparticles can be exploited to facilitate efficient delivery of antigenic cargo and immunostimulatory molecules to pDCs. Together, our results show that in addition to their potency to stimulate innate immunity, pDCs can polarize adaptive immune responses against exogenous particulate Ag. These results may have important consequences for the development of new immunotherapeutic strategies exploiting Ag and TLR-Ls encapsulated in microparticles to target APC subsets.The Journal of Immunology 03/2010; 184(8):4276-83. · 5.52 Impact Factor
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ABSTRACT: New biomarkers are urgently needed to accelerate efforts in developing new drugs and treatments of known diseases. New clinical and translational proteomics studies emerge almost every day. However, discovery of new diagnostic biomarkers lags behind because of variability at every step in proteomics studies (e.g., assembly of a cohort of patients, sample preparation and the nature of body fluids, selection of a profiling method and uniform protocols for data analysis).Quite often, the validation step that follows the discovery phase does not reach desired levels of sensitivity and specificity or reproducibility between laboratories. Mass spectrometry and gel-based methods do not provide enough throughput for screening thousands of clinical samples. Further development of protein arrays may address this issue.Despite many obstacles, proteomics delivers vast amounts of information useful for understanding the molecular mechanisms underlying diseases.TrAC Trends in Analytical Chemistry 02/2010; 29(2):128. · 6.35 Impact Factor