Bioactive sucralfate-based microneedles promote wound healing through reprogramming macrophages and protecting endogenous growth factors.

Impaired wound healing due to insufficient cell proliferation and angiogenesis is a significant physical and psychological burden to patients worldwide. Therapeutic delivery of exogenous growth factors (GFs) at high doses for wound repair is non-ideal as GFs have poor stability in proteolytic wound environments. Here, we present a two-stage strategy using bioactive sucralfate-based microneedle (SUC-MN) for delivering interleukin-4 (IL-4) to accelerate wound healing.

Correction: Predicting small molecules solubility on endpoint devices using deep ensemble neural networks.

[This corrects the article DOI: 10.1039/D3DD00217A.].

Predicting small molecules solubility on endpoint devices using deep ensemble neural networks.

Aqueous solubility is a valuable yet challenging property to predict. Computing solubility using first-principles methods requires accounting for the competing effects of entropy and enthalpy, resulting in long computations for relatively poor accuracy. Data-driven approaches, such as deep learning, offer improved accuracy and computational efficiency but typically lack uncertainty quantification.

pyPolyBuilder: Automated Preparation of Molecular Topologies and Initial Configurations for Molecular Dynamics Simulations of Arbitrary Supramolecules.

The construction of a molecular topology file is a prerequisite for any classical molecular dynamics simulation. However, the generation of such a file may be very challenging at times, especially for large supramolecules. While many tools are available to provide topologies for large proteins and other biomolecules, the scientific community researching nonbiological systems is not equally well equipped.

Drug-Loading Capacity of PAMAM Dendrimers Encapsulating Quercetin Molecules: A Molecular Dynamics Study with the 2016H66 Force Field.

The complexation of quercetin molecules with poly(amidoamine) (PAMAM) dendrimers of generation 0-3 was studied by molecular dynamics simulations. Three main points were addressed: (i) the effect of starting from different initial structures; (ii) the performance of the 2016H66 force field (recently validated in the context of dendrimer simulations) in predicting the experimental drug(quercetin)-loading capacity of PAMAM dendrimers; and (iii) the stability of quercetin-PAMAM complexes and their interactions. Initial structures generated by different restraint protocols led to faster convergence compared to initial structures generated by randomly placing the drug molecules in the simulation box.

Molecular Dynamics Simulations of PAMAM and PPI Dendrimers Using the GROMOS-Compatible 2016H66 Force Field.

A systematic evaluation of the accuracy of the GROMOS-compatible 2016H66 force field in the simulation of dendrimers is performed. More specifically, the poly(amido amine) (PAMAM) and the poly(propyleneimine) (PPI) are considered because of the availability of experimental data and simulation results in the literature. A total of 36 molecular systems are simulated and the radius of gyration, asphericity, density profiles, and the self-diffusion coefficient are monitored in terms of the generation number and pH (low, medium, and high) condition.