Signatures of T cell immunity revealed using sequence similarity with TCRDivER algorithm.

Changes in the T cell receptor (TCR) repertoires have become important markers for monitoring disease or therapy progression. With the rise of immunotherapy usage in cancer, infectious and autoimmune disease, accurate assessment and comparison of the "state" of the TCR repertoire has become paramount. One important driver of change within the repertoire is T cell proliferation following immunisation. A way of monitoring this is by investigating large clones of individual T cells believed to bind epitopes connected to the disease. However, as a single target can be bound by many different TCRs, monitoring individual clones cannot fully account for T cell cross-reactivity. Moreover, T cells responding to the same target often exhibit higher sequence similarity, which highlights the importance of accounting for TCR similarity within the repertoire. This complexity of binding relationships between a TCR and its target convolutes comparison of immune responses between individuals or comparisons of TCR repertoires at different timepoints. Here we propose TCRDivER algorithm (T cell Receptor Diversity Estimates for Repertoires), a global method of T cell repertoire comparison using diversity profiles sensitive to both clone size and sequence similarity. This approach allowed for distinction between spleen TCR repertoires of immunised and non-immunised mice, showing the need for including both facets of repertoire changes simultaneously. The analysis revealed biologically interpretable relationships between sequence similarity and clonality. These aid in understanding differences and separation of repertoires stemming from different biological context. With the rise of availability of sequencing data we expect our tool to find broad usage in clinical and research applications.

T Cell Epitope Prediction and Its Application to Immunotherapy.

T cells play a crucial role in controlling and driving the immune response with their ability to discriminate peptides derived from healthy as well as pathogenic proteins. In this review, we focus on the currently available computational tools for epitope prediction, with a particular focus on tools aimed at identifying neoepitopes, i.e. cancer-specific peptides and their potential for use in immunotherapy for cancer treatment. This review will cover how these tools work, what kind of data they use, as well as pros and cons in their respective applications.

T cell receptor sequence clustering and antigen specificity.

There has been increasing interest in the role of T cells and their involvement in cancer, autoimmune and infectious diseases. However, the nature of T cell receptor (TCR) epitope recognition at a repertoire level is not yet fully understood. Due to technological advances a plethora of TCR sequences from a variety of disease and treatment settings has become readily available. Current efforts in TCR specificity analysis focus on identifying characteristics in immune repertoires which can explain or predict disease outcome or progression, or can be used to monitor the efficacy of disease therapy. In this context, clustering of TCRs by sequence to reflect biological similarity, and especially to reflect antigen specificity have become of paramount importance. We review the main TCR sequence clustering methods and the different similarity measures they use, and discuss their performance and possible improvement. We aim to provide guidance for non-specialists who wish to use TCR repertoire sequencing for disease tracking, patient stratification or therapy prediction, and to provide a starting point for those aiming to develop novel techniques for TCR annotation through clustering.

Exploring the applicability of density functional tight binding to transition metal ions. Parameterization for nickel with the spin-polarized DFTB3 model.

In this work, we explore the applicability and limitations of the current third order density functional tight binding (DFTB3) formalism for treating transition metal ions using nickel as an example. To be consistent with recent parameterization of DFTB3 for copper, the parametrization for nickel is conducted in a spin-polarized formulation and with orbital-resolved Hubbard parameters and their charge derivatives. The performance of the current parameter set is evaluated based on structural and energetic properties of a set of nickel-containing compounds that involve biologically relevant ligands. Qualitatively similar to findings in previous studies of copper complexes, the DFTB3 results are more reliable for nickel complexes with neutral ligands than for charged ligands; nevertheless, encouraging agreement is noted in comparison to the reference method, B3LYP/aug-cc-pVTZ, especially for structural properties, including cases that exhibit Jahn-Teller distortions; the structures also compare favorably to available X-ray data in the Cambridge Crystallographic Database for a number of nickel-containing compounds. As to limitations, we find it is necessary to use different d shell Hubbard charge derivatives for Ni(I) and Ni(II), due to the distinct electronic configurations for the nickel ion in the respective complexes, and substantial errors are observed for ligand binding energies, especially for charged ligands, d orbital splitting energies and splitting between singlet and triplet spin states for Ni(II) compounds. These observations highlight that future improvement in intra-d correlation and ligand polarization is required to enable the application of the DFTB3 model to complex transition metal ions. © 2018 Wiley Periodicals, Inc.

in/out Isomerism of cyclophanes: a theoretical account of 2,6,15-trithia-[34,10][7]metacyclophane and [34,10][7]metacyclophane as well as their halogen substituted analogues.

A detailed theoretical investigation of cyclophanes with a divergent set of methods ranging from molecular mechanics through semiempirical to ab initio is presented. Cyclophanes have attracted interest over the years due to their unusual chemistry and increasing applications. There has been previous debate over the effects contributing to the greater stability of more-crowded in isomers of certain cyclophanes, and a higher strain in the out isomer was the prevailing explanation. Application of EDA-NOCV and SAPT analysis has enabled us to distinguish between different effects controlling isomer stability and determine the significance of all effects involved. Our results show that, although strain has a large significance, orbital stabilization within the molecule from the aromatic electron density is crucial. Furthermore, we analysed halogen-substituted cyclophanes in order to further understand these subtle effects.

A Comparative Study of Chromatographic Behavior and Lipophilicity of Selected Imidazoline Derivatives.

Chromatographic behavior and lipophilicity of 20 selected imidazoline derivatives were examined by thin-layer chromatography using CN, RP-2, RP-8 and RP-18 as the stationary phases and a mixture of methanol, water and ammonia as the mobile phase. In all examined chromatographic systems, linear relationships were established between retention parameters and the volume fraction of methanol in the mobile phase (r > 0.985, 0.978, 0.981, 0.988 for the CN, RP-2, RP-8 and RP-18, respectively). The highest correlation between the obtained [Formula: see text] values was observed for RP-2 and RP-8 stationary phases. The experimental lipophilicity indices ([Formula: see text], m and C0) obtained from the retention data were used in correlation study with the calculated logP values. Experimentally determined [Formula: see text] values for all investigated chromatographic systems exhibited the highest correlation with the calculated ClogP values (r: 0.880, 0.872, 0.897 and 0.889 for the CN, RP-2, RP-8 and RP-18 stationary phases, respectively). In addition, principal component analysis enables new information about similarity and differences between tested compounds as well as experimental lipophilicity indices and calculated logP values. Performed QSRR analysis showed that the frequency of C-C at topological distance 1 and CATS2D Lipophilic-Lipophilic at lag 01 were important descriptors with influence on the [Formula: see text] values in all the examined chromatographic systems, while the differences in the retention behavior of compounds on the examined stationary phases can be distinguished based on their specific geometrical, electronic and constitutional properties.