Xanthan Gum-Iron System: Natural, Mechanically Tunable, Bioactive, and Magnetic-Responsive Hydrogels for Biomedical Engineering Applications.

Xanthan gum (XG) has performed far better than other polysaccharides for industrial purposes, e.g., food, pharmaceutical, and cosmetic applications, due to its outstanding thickening effect, pseudoplastic rheological properties, and non-toxicity.

Unraveling and Harnessing the Immune Response at the Cell-Biomaterial Interface for Tissue Engineering Purposes.

Biomaterials are defined as "engineered materials" and include a range of natural and synthetic products, designed for their introduction into and interaction with living tissues. Biomaterials are considered prominent tools in regenerative medicine that support the restoration of tissue defects and retain physiologic functionality. Although commonly used in the medical field, these constructs are inherently foreign toward the host and induce an immune response at the material-tissue interface, defined as the foreign body response (FBR).

Development of a biomimetic arch-like 3D bioprinted construct for cartilage regeneration using gelatin methacryloyl and silk fibroin-gelatin bioinks.

In recent years, engineering biomimetic cellular microenvironments have been a top priority for regenerative medicine. Collagen II, which is arranged in arches, forms the predominant fiber network in articular cartilage. Due to the shortage of suitable microfabrication techniques capable of producing 3D fibrous structures,replication of the arch-like cartilaginous tissue constitutes one of the major challenges.

Culturing of Cardiac Fibroblasts in Engineered Heart Matrix Reduces Myofibroblast Differentiation but Maintains Their Response to Cyclic Stretch and Transforming Growth Factor β1.

Isolation and culturing of cardiac fibroblasts (CF) induces rapid differentiation toward a myofibroblast phenotype, which is partly mediated by the high substrate stiffness of the culture plates. In the present study, a 3D model of Engineered Heart Matrix (EHM) of physiological stiffness (Youngs modulus ~15 kPa) was developed using primary adult rat CF and a natural hydrogel collagen type 1 matrix. CF were equally distributed, viable and quiescent for at least 13 days in EHM and the baseline gene expression of myofibroblast-markers alfa-smooth muscle actin (Acta2), and connective tissue growth factor (Ctgf) was significantly lower, compared to CF cultured in 2D monolayers.

On-the-Fly Integration of Data from a Spin-Diffusion-Based NMR Experiment into Protein-Ligand Docking.

INPHARMA (interligand nuclear Overhauser enhancement for pharmacophore mapping) determines the relative orientation of two competitive ligands in the protein binding pocket. It is based on the observation of interligand transferred NOEs mediated by spin diffusion through protons of the protein and is, therefore, sensitive to the specific interactions of each of the two ligands with the protein. We show how this information can be directly included into a protein-ligand docking program to guide the prediction of the complex structures.

Performance of protein-ligand docking with simulated chemical shift perturbations.

Protein chemical shift perturbations (CSPs) that result from the binding of a ligand to the protein contain structural information about the complex. Therefore, the CSP data, typically obtained during library screening from two-dimensional (2D) nuclear magnetic resonance (NMR) spectra, are often available before attempts to solve the experimental structure of the complex are started, and can be used to solve the complex structure with CSP-based docking. Here, we compare the performance of the post-docking filter and the guided-docking approaches using either amide or α-proton CSPs with 10 protein-ligand complexes.

Protein-ligand structure guided by backbone and side-chain proton chemical shift perturbations.

The fragment-based drug design approach consists of screening libraries of fragment-like ligands, to identify hits that typically bind the protein target with weak affinity (100 μM-5 mM). The determination of the protein-fragment complex 3D structure constitutes a crucial step for uncovering the key interactions responsible for the protein-ligand recognition, and for growing the initial fragment into potent active compounds. The vast majority of fragments are aromatic compounds that induce chemical shift perturbations (CSP) on protein NMR spectra.

Comparing binding modes of analogous fragments using NMR in fragment-based drug design: application to PRDX5.

Fragment-based drug design is one of the most promising approaches for discovering novel and potent inhibitors against therapeutic targets. The first step of the process consists of identifying fragments that bind the protein target. The determination of the fragment binding mode plays a major role in the selection of the fragment hits that will be processed into drug-like compounds.

BcL-xL conformational changes upon fragment binding revealed by NMR.

Protein-protein interactions represent difficult but increasingly important targets for the design of therapeutic compounds able to interfere with biological processes. Recently, fragment-based strategies have been proposed as attractive approaches for the elaboration of protein-protein surface inhibitors from fragment-like molecules. One major challenge in targeting protein-protein interactions is related to the structural adaptation of the protein surface upon molecular recognition.

Are predefined decoy sets of ligand poses able to quantify scoring function accuracy?

Due to the large number of different docking programs and scoring functions available, researchers are faced with the problem of selecting the most suitable one when starting a structure-based drug discovery project. To guide the decision process, several studies comparing different docking and scoring approaches have been published. In the context of comparing scoring function performance, it is common practice to use a predefined, computer-generated set of ligand poses (decoys) and to reevaluate their score using the set of scoring functions to be compared.

pK(a) based protonation states and microspecies for protein-ligand docking.

In this paper we present our reworked approach to generate ligand protonation states with our structure preparation tool SPORES (Structure PrOtonation and REcognition System). SPORES can be used for the preprocessing of proteins and protein-ligand complexes as e.g.

Influence of protonation, tautomeric, and stereoisomeric states on protein-ligand docking results.

In this work, we present a systematical investigation of the influence of ligand protonation states, stereoisomers, and tautomers on results obtained with the two protein-ligand docking programs GOLD and PLANTS. These different states were generated with a fully automated tool, called SPORES (Structure PrOtonation and Recognition System). First, the most probable protonations, as defined by this rule based system, were compared to the ones stored in the well-known, manually revised CCDC/ASTEX data set.