Conformational constraints on side chains in protein residues increase their information content

Like all other complex biological systems, proteins exhibit properties not seen in free amino acids (i.e., emergent properties). The present investigation arose from the deduction that proteins should offer a good model to approach the reverse phenomenon, namely top-down constraints experienced by protein residues compared to free amino acids. The crystalline structure of profilin Ib, a contractile protein of Acanthamoeba castellanii, was chosen as the object of study and submitted to 2-ns molecular dynamics simulation. The results revealed strong conformational constraints on the side chain of residues compared to the respective free amino acids. A Shannon entropy (SE) analysis of the conformational behavior of the side chains showed in most cases a strong decrease in the SE of the χ1 and χ2 dihedral angles compared to free amino acids. This is equivalent to stating that conformational constraints on the side chain of residues increase their information content and hence recognition specificity compared to free amino acids. In other words, the vastly increased information content of a protein relative to its free monomers is embedded not only in the tertiary structure of the backbone, but also in the conformational behavior of the side chains. The postulated implication is that both backbone and side chains, by virtue of being conformationally constrained, contribute to the recognition specificity of the protein toward other macromolecules and ligand

The age of data-driven proteomics : how machine learning enables novel workflows

A lot of energy in the field of proteomics is dedicated to the application of challenging experimental workflows, which include metaproteomics, proteogenomics, data independent acquisition (DIA), non-specific proteolysis, immunopeptidomics, and open modification searches. These workflows are all challenging because of ambiguity in the identification stage; they either expand the search space and thus increase the ambiguity of identifications, or, in the case of DIA, they generate data that is inherently more ambiguous. In this context, machine learning-based predictive models are now generating considerable excitement in the field of proteomics because these predictive models hold great potential to drastically reduce the ambiguity in the identification process of the above-mentioned workflows. Indeed, the field has already produced classical machine learning and deep learning models to predict almost every aspect of a liquid chromatography-mass spectrometry (LC-MS) experiment. Yet despite all the excitement, thorough integration of predictive models in these challenging LC-MS workflows is still limited, and further improvements to the modeling and validation procedures can still be made. In this viewpoint we therefore point out highly promising recent machine learning developments in proteomics, alongside some of the remaining challenges

Expression of tricellular tight junction proteins and the paracellular macromolecule barrier are recovered in remission of ulcerative colitis

Background: Ulcerative colitis (UC) has a relapsing and remitting pattern, wherein the underlying mechanisms of the relapse might involve an enhanced uptake of luminal antigens which stimulate the immune response. The tricellular tight junction protein, tricellulin, takes charge of preventing paracellular passage of macromolecules. It is characterized by downregulated expression in active UC and its correct localization is regulated by angulins. We thus analyzed the tricellulin and angulin expression as well as intestinal barrier function and aimed to determine the role of tricellulin in the mechanisms of relapse. Methods: Colon biopsies were collected from controls and UC patients who underwent colonoscopy at the central endoscopy department of Campus Benjamin Franklin, Charite - Universitatsmedizin Berlin. Remission of UC was defined basing on the clinical appearance and a normal Mayo endoscopic subscore. Intestinal barrier function was evaluated by electrophysiological and paracellular flux measurements on biopsies mounted in Ussing chambers. Results: The downregulated tricellulin expression in active UC was recovered in remission UC to control values. Likewise, angulins were in remission UC at the same levels as in controls. Also, the epithelial resistance which was decreased in active UC was restored in remission to the same range as in controls, along with the unaltered paracellular permeabilities for fluorescein and FITC-dextran 4 kDa. Conclusions: In remission of UC, tricellulin expression level as well as intestinal barrier functions were restored to normal, after they were impaired in active UC. This points toward a re-sealing of the impaired tricellular paracellular pathway and abated uptake of antigens to normal rates in remission of UC

The stability for the Cauchy problem for elliptic equations

We discuss the ill-posed Cauchy problem for elliptic equations, which is pervasive in inverse boundary value problems modeled by elliptic equations. We provide essentially optimal stability results, in wide generality and under substantially minimal assumptions. As a general scheme in our arguments, we show that all such stability results can be derived by the use of a single building brick, the three-spheres inequality.Comment: 57 pages, review articl

General Spectral Flow Formula for Fixed Maximal Domain

We consider a continuous curve of linear elliptic formally self-adjoint differential operators of first order with smooth coefficients over a compact Riemannian manifold with boundary together with a continuous curve of global elliptic boundary value problems. We express the spectral flow of the resulting continuous family of (unbounded) self-adjoint Fredholm operators in terms of the Maslov index of two related curves of Lagrangian spaces. One curve is given by the varying domains, the other by the Cauchy data spaces. We provide rigorous definitions of the underlying concepts of spectral theory and symplectic analysis and give a full (and surprisingly short) proof of our General Spectral Flow Formula for the case of fixed maximal domain. As a side result, we establish local stability of weak inner unique continuation property (UCP) and explain its role for parameter dependent spectral theory.Comment: 22 page

Low-basicity 5-HT7 receptor agonists synthesized using the van Leusen multicomponent protocol

A series of 5-aryl-1-alkylimidazole derivatives was synthesized using the van Leusen multicomponent reaction. The chemotype is the first example of low-basicity scaffolds exhibiting high affinity for 5-HT7 receptor together with agonist function. The chosen lead compounds 3-(1-ethyl-1H-imidazol-5-yl)-5- iodo-1H-indole (AGH-107, 1o, Ki 5-HT7=6nM, EC50=19nM, 176-fold selectivity over 5-HT1AR) and 1e (5-methoxy analogue, Ki 5-HT7=30nM, EC50=60nM) exhibited high selectivity over related CNS targets, high metabolic stability and low toxicity in HEK-293 and HepG2 cell cultures. A rapid absorption to the blood, high blood-brain barrier permeation and a very high peak concentration in the brain (Cmax=2723 ng/g) were found for 1o after i.p. (5mg/kg) administration in mice. The compound was found active in novel object recognition test in mice, at 0.5, 1 and 5mg/kg. Docking to 5-HT7R homology models indicated a plausible binding mode which explain the unusually high selectivity over the related CNS targets. Halogen bond formation between the most potent derivatives and the receptor is consistent with both the docking results and SAR. 5-Chlorine, bromine and iodine substitution resulted in a 13, 27 and 89-fold increase in binding affinities, respectively, and in enhanced 5-HT1AR selectivity