Fucosylated inhibitors of recently identified bangle lectin from Photorhabdus asymbiotica

Glycocalix[4]arenes and their affinity to a library of galectins: the linker matters

Galectins are lectins that bind β-galactosides. They are involved in important extra- and intracellular biological processes such as apoptosis, and regulation of the immune system or the cell cycle. High-affinity ligands of galectins may introduce new therapeutic approaches or become new tools for biomedical research. One way of increasing the low affinity of β-galactoside ligands to galectins is their multivalent presentation, e.g., using calixarenes. We report on the synthesis of glycocalix[4]arenes in cone, partial cone, 1,2-alternate, and 1,3-alternate conformations carrying a lactosyl ligand on three different linkers. The affinity of the prepared compounds to a library of human galectins was determined using competitive ELISA assay and biolayer interferometry. Structure-affinity relationships regarding the influence of the linker and the core structure were formulated. Substantial differences were found between various linker lengths and the position of the triazole unit. The formation of supramolecular clusters was detected by atomic force microscopy. The present work gives a systematic insight into prospective galectin ligands based on the calix[4]arene core.

Prediction of protein-carbohydrate complex binding affinity using structural features

Protein-carbohydrate interactions play a major role in several cellular and biological processes. Elucidating the factors influencing the binding affinity of protein-carbohydrate complexes and predicting their free energy of binding provide deep insights for understanding the recognition mechanism. In this work, we have collected the experimental binding affinity data for a set of 389 protein-carbohydrate complexes and derived several structure-based features such as contact potentials, interaction energy, number of binding residues and contacts between different types of atoms. Our analysis on the relationship between binding affinity and structural features revealed that the important factors depend on the type of the complex based on number of carbohydrate and protein chains. Specifically, binding site residues, accessible surface area, interactions between various atoms and energy contributions are important to understand the binding affinity. Further, we have developed multiple regression equations for predicting the binding affinity of protein-carbohydrate complexes belonging to six categories of protein-carbohydrate complexes. Our method showed an average correlation and mean absolute error of 0.731 and 1.149 kcal/mol, respectively, between experimental and predicted binding affinities on a jackknife test. We have developed a web server PCA-Pred, Protein-Carbohydrate Affinity Predictor, for predicting the binding affinity of protein-carbohydrate complexes. The web server is freely accessible at https://web.iitm.ac.in/bioinfo2/pcapred/. The web server is implemented using HTML and Python and supports recent versions of major browsers such as Chrome, Firefox, IE10 and Opera.