Design of protease-resistant myelin basic protein-derived peptides by cleavage site directed amino acid substitutions

Multiple Sclerosis (MS) is considered to be a T cell-mediated autoimmune disease. An attractive strategy to prevent activation of autoaggressive T cells in MS, is the use of altered peptide ligands (APL), which bind to major histocompatibility complex class II (MHC II) molecules. To be of clinical use, APL must be capable of resisting hostile environments including the proteolytic machinery of antigen presenting cells (APC). The current design of APL relies on cost- and labour-intensive strategies. To overcome these major drawbacks, we used a deductive approach which involved modifying proteolytic cleavage sites in APL. Cleavage site-directed amino acid substitution of the autoantigen myelin basic protein (MBP) resulted in lysosomal protease-resistant, high-affinity binding peptides. In addition, these peptides mitigated T cell activation in a similar fashion as conventional APL. The strategy outlined allows the development of protease-resistant APL and provides a universal design strategy to improve peptide-based immunotherapeutics

Constrained Markovian dynamics of random graphs

We introduce a statistical mechanics formalism for the study of constrained graph evolution as a Markovian stochastic process, in analogy with that available for spin systems, deriving its basic properties and highlighting the role of the `mobility' (the number of allowed moves for any given graph). As an application of the general theory we analyze the properties of degree-preserving Markov chains based on elementary edge switchings. We give an exact yet simple formula for the mobility in terms of the graph's adjacency matrix and its spectrum. This formula allows us to define acceptance probabilities for edge switchings, such that the Markov chains become controlled Glauber-type detailed balance processes, designed to evolve to any required invariant measure (representing the asymptotic frequencies with which the allowed graphs are visited during the process). As a corollary we also derive a condition in terms of simple degree statistics, sufficient to guarantee that, in the limit where the number of nodes diverges, even for state-independent acceptance probabilities of proposed moves the invariant measure of the process will be uniform. We test our theory on synthetic graphs and on realistic larger graphs as studied in cellular biology.Comment: 28 pages, 6 figure

Structural analysis of phenothiazine derivatives as allosteric inhibitors of the MALT1 paracaspase.

Second site: In the crystal structure of human MALT1casp-Ig3 (mucosa-associated lymphoid tissue lymphoma translocation protein 1) in complex with the tricyclic phenothiazine derivative thioridazine (violet in the picture), the inhibitor is bound in a hydrophobic pocket far from the active site. This explains the action of phenothiazine derivatives as noncompetitive, reversible inhibitors

Activity-based probes for detection of active MALT1 paracaspase in immune cells and lymphomas.

MALT1 paracaspase is activated upon antigen receptor stimulation to promote lymphocyte activation. In addition, deregulated MALT1 protease activity drives survival of distinct lymphomas such as the activated B cell type of diffuse large B cell lymphoma (ABC-DLBCL). Here, we designed fluorophore or biotin-coupled activity based-probes (ABP) that covalently modify the active center of MALT1. MALT1-ABPs are exclusively labeling an active modified full length form of MALT1 upon T cell stimulation. Further, despite the CARMA1 requirement for initial MALT1 activation, the MALT1-ABPs show that protease activity is not confined to the high-molecular CARMA1-BCL10-MALT1 (CBM) complex. Using biotin-coupled ABPs, we developed a robust assay for sensitive and selective detection of active MALT1 in cell lines, primary lymphocytes, and DLBCL tumor biopsies. Taken together, MALT1-ABPs represent powerful chemical tools to measure cellular MALT1 activation, determine efficacy of small molecule inhibitors, and classify lymphomas based on MALT1 activity status

Multilevel and latent variable modeling with composite links and exploded likelihoods

composite link, exploded likelihood, unfolding, multilevel model, generalized linear mixed model, latent variable model, item response model, factor model, frailty, zero-inflated Poisson model, gllamm,