Showing papers by "Clemencia Pinilla published in 2008"

Quantitative peptide binding motifs for 19 human and mouse MHC class I molecules derived using positional scanning combinatorial peptide libraries.

Abstract: Background: It has been previously shown that combinatorial peptide libraries are a useful tool to characterize the binding specificity of class I MHC molecules. Compared to other methodologies, such as pool sequencing or measuring the affinities of individual peptides, utilizing positional scanning combinatorial libraries provides a baseline characterization of MHC molecular specificity that is cost effective, quantitative and unbiased. Results: Here, we present a large-scale application of this technology to 19 different human and mouse class I alleles. These include very well characterized alleles (e.g. HLA A*0201), alleles with little previous data available (e.g. HLA A*3201), and alleles with conflicting previous reports on specificity (e.g. HLA A*3001). For all alleles, the positional scanning combinatorial libraries were able to elucidate distinct binding patterns defined with a uniform approach, which we make available here. We introduce a heuristic method to translate this data into classical definitions of main and secondary anchor positions and their preferred residues. Finally, we validate that these matrices can be used to identify candidate MHC binding peptides and T cell epitopes in the vaccinia virus and influenza virus systems, respectively. Conclusion: These data confirm, on a large scale, including 15 human and 4 mouse class I alleles, the efficacy of the positional scanning combinatorial library approach for describing MHC class I binding specificity and identifying high affinity binding peptides. These libraries were shown to be useful for identifying specific primary and secondary anchor positions, and thereby simpler motifs, analogous to those described by other approaches. The present study also provides matrices useful for predicting high affinity binders for several alleles for which detailed quantitative descriptions of binding specificity were previously unavailable, including A*3001, A*3201, B*0801, B*1501 and B*1503.

Visualization of the Chemical Space in Drug Discovery

Abstract: Chemical space has become a key concept in drug discovery. The continued growth in the number of molecules available raises the question regarding how many compounds may exist and which ones have the potential to become drugs. Analysis and visualization of the chemical space covered by public, commercial, in-house and virtual compound collections have found multiple applications in diversity analysis, in silico property profiling, data mining, virtual screening, library design, prioritization in screening campaigns, and acquisition of compound collections, among others. This review covers several techniques, computational programs and approaches that have been developed to visualize, navigate and study the chemical space of molecular databases. Techniques developed in our group are presented including a quantitative assessment of the multi-fusion similarity maps. Additionally an application of 3D-similarity, based on the overlay of chemical structures, to represent the chemical space is introduced. Several comparisons of the chemical space covered by compound collections from different sources such as combinatorial libraries, drugs and natural products, or directed to specific therapeutic areas are also discussed.

Strategies for the use of mixture-based synthetic combinatorial libraries: scaffold ranking, direct testing in vivo, and enhanced deconvolution by computational methods.

Abstract: Since its inception more than 20 years ago with highthroughput parallel synthesis for oligonucleotides and peptides, synthetic combinatorial methods have fundamentally advanced the ability to synthesize and screen large numbers of compounds because of improvements made in technology, instrumentation, and library design strategies. This discipline was readily accepted initially and is now an embedded component of the drug discovery process worldwide. While there are a range of combinatorial approaches, the use of mixture-based libraries made up of tens of thousands to billions of compounds is the approach that enables the most rapid and economical acquisition of chemical and biological information. Mixture-based libraries represent powerful tools that can be used for the identification of active individual compounds for a wide range of important targets, as reviewed. In the past decade, such approaches have been expanded to include the synthesis of low molecular weight acyclic and heterocyclic compounds. As with most innovations, synthetic combinatorial methods developed for the synthesis and screening of mixture-based libraries were slow to gain acceptance because of the conceptual distance between these approaches and the traditional methods previously used in the pharmaceutical industry. This was, and is, especially true for mixture-based libraries composed of tens of thousands to billions of different compounds, but such methods are now being used by an increasing number of groups for the identification of highly active, novel compounds in research and drug discovery programs. Mixture-based libraries are systematically arranged mixtures of synthetic compounds having both defined and mixture positions of diversity. This permits information to be gathered regarding both the activity and importance of every functionality at each position of the library. Post synthetic chemical modification of such existing mixturebased libraries using the “libraries from libraries” approach now enables the ever-increasing generation of low molecular weight compounds. Thus, for the last 16 years, we have successfully used this approach for the design and the generation of a range of peptidomimetic and small molecule libraries from resin-bound polyamides. We have also used this approach combining solidand solution-phase synthesis methods for the synthesis of a nitrosamine library and a platinum tetraamine coordination complex library. The power of synthetic mixture-based combinatorial libraries lies in their ability to accelerate the acquisition of information regarding specific functionalities at each variable position in the library that determines the activity of a specific chemical scaffold or pharmacophore. Another advantage of mixture-based libraries resides in the very high densities of compounds that can be synthesized in narrow areas of chemical space. When compared to existing high-throughput screening (HTS) programs, in which tens of thousands of individual compounds are screened against therapeutically important targets, millions of compounds formatted as mixtures can be examined using substantially less material and at much lower time/labor economics than if these same mixture-based diversities were made and screened as individual compounds. This unique combinatorial library approach can be applied to virtually any existing bioassay for the identification of novel ligands. For example, a novel, highly active tetrapeptide agonist for the κ-opioid receptor was identified from a positional scanning library of 6.25 * To whom correspondence should be addressed. Phone: 858-455-3805. Fax: 858-455-3804. E-mail: rhoughten@tpims.org. † Torrey Pines Institute for Molecular Studies. ‡ University of Arizona. § PsychoGenics, Inc. | Carnegie Mellon University. ⊥ Current address: College of Pharmaceutical Science, Zijin Campus, Zhejiang University, Hangzhou 310058, P. R. China. J. Comb. Chem. 2008, 10, 3–19 3

Monkeypox virus evades antiviral CD4+ and CD8+ T cell responses by suppressing cognate T cell activation.

Abstract: Monkeypox virus (MPV) is a virulent human pathogen that has gained increased attention because of its potential use as a bioterrorism agent and inadvertent introduction into North America in 2003. The US outbreak also provided an important opportunity to study MPV-specific T cell immunity. Although MPV-specific CD4+ and CD8+ T cells could recognize vaccinia virus (VV)-infected monocytes and produce inflammatory cytokines such as IFNγ and TNFα, they were largely incapable of responding to autologous MPV-infected cells. Further analysis revealed that, unlike cowpox virus (CPV), MPV did not interfere with MHC expression or intracellular transport of MHC molecules. Instead, MPV-infected cells were capable of preventing T cell receptor (TcR)-mediated T cell activation in trans. The ability to trigger a state of nonresponsiveness represents a unique MHC-independent mechanism for blocking antiviral T cell activation and inflammatory cytokine production and is likely an important attribute involved with viral dissemination in the infected host.

Thyroglobulin Peptides Associate In Vivo to HLA-DR in Autoimmune Thyroid Glands

Abstract: Endocrine epithelial cells, targets of the autoimmune response in thyroid and other organ-specific autoimmune diseases, express HLA class II (HLA-II) molecules that are presumably involved in the maintenance and regulation of the in situ autoimmune response. HLA-II molecules thus expressed by thyroid cells have the "compact" conformation and are therefore expected to stably bind autologous peptides. Using a new approach to study in situ T cell responses without the characterization of self-reactive T cells and their specificity, we have identified natural HLA-DR-associated peptides in autoimmune organs that will allow finding peptide-specific T cells in situ. This study reports a first analysis of HLA-DR natural ligands from ex vivo Graves' disease-affected thyroid tissue. Using mass spectrometry, we identified 162 autologous peptides from HLA-DR-expressing cells, including thyroid follicular cells, with some corresponding to predominant molecules of the thyroid colloid. Most interestingly, eight of the peptides were derived from a major autoantigen, thyroglobulin. In vitro binding identified HLA-DR3 as the allele to which one of these peptides likely associates in vivo. Computer modeling and bioinformatics analysis suggested other HLA-DR alleles for binding of other thyroglobulin peptides. Our data demonstrate that although the HLA-DR-associated peptide pool in autoimmune tissue mostly belongs to abundant ubiquitous proteins, peptides from autoantigens are also associated to HLA-DR in vivo and therefore may well be involved in the maintenance and the regulation of the autoimmune response.

Degenerate TCR recognition and dual DR2 restriction of autoreactive T cells: Implications for the initiation of the autoimmune response in multiple sclerosis

Abstract: TCR degeneracy may facilitate self-reactive T cell activation and the initiation of an autoimmune response in multiple sclerosis (MS). MHC class II alleles of the DR2 haplotype DR2a (DRB5*0101) and DR2b (DRB1*1501) are associated with an increased risk for MS in Caucasian populations. In order to selectively expand and characterize T cells with a high degree of TCR degeneracy that recognize peptides in the context of disease-associated DR2 alleles, we developed DR2-anchored peptide mixtures (APM). We report here that DR2-APM have a high stimulatory potency and can selectively expand T cells with a degenerate TCR (TCR(deg)). Due to the low concentration of individual peptides in the mixtures, T cell clones' proliferative response to DR2-APM implies that multiple peptides stimulate the TCR, which is a characteristic of TCR(deg). The frequency of DR2-APM-reactive T cells is significantly higher in MS patients than in healthy controls, suggesting that they may play a role in the development of the autoimmune response in MS. DR2-APM-reactive cells have a dual DR2 restriction: they recognize DR2-APM in the context of both DR2a and DR2b molecules. The DR2-APM-reactive cells' IL-17 secretion, together with cross-reactivity against myelin peptides, may contribute to their role in the development of autoimmune response in MS.

Characterization of Melan-A reactive memory CD8+ T cells in a healthy donor

Abstract: Melan-A specific CD8+ T cells are thought to play an important role against the development of melanoma. Their in vivo expansion is often observed with advanced disease. In recent years, low levels of Melan-A reactive CD8+ T cells have also been found in HLA-A2 healthy donors, but these cells harbor naive characteristics and are thought to be mostly cross-reactive for the Melan-A antigen. Here, we report on a large population of CD8+ T cells reactive for the Melan-A antigen, identified in one donor with no evidence of melanoma. Interestingly, this population is oligoclonal and displays a clear memory phenotype. However, a detailed study of these cells indicated that they are unlikely to be directly specific for melanoma, so that their in vivo expansion may have been driven by an exogenous antigen. Screening of a Melan-A cross-reactive peptide library suggested that these cells may be specific for an epitope derived from a Mycobacterium protein, which would provide a further example of CD8+ T cell cross-reactivity between a pathogen antigen and a tumor antigen. Finally, we discuss potential perspectives regarding the role of such cells in heterologous immunity, by influencing the balance between protective immunity and pathology, e.g. in the case of melanoma development.