Cholesterol modulates the physiological response to nanoparticles by changing the composition of protein corona

Biological barriers to drug transport prevent successful accumulation of nanotherapeutics specifically at diseased sites, limiting efficacious responses in disease processes ranging from cancer to inflammation. Although substantial research efforts have aimed to incorporate multiple functionalities and moieties within the overall nanoparticle design, many of these strategies fail to adequately address these barriers. Obstacles, such as nonspecific distribution and inadequate accumulation of therapeutics, remain formidable challenges to drug developers. A reimagining of conventional nanoparticles is needed to successfully negotiate these impediments to drug delivery. Site-specific delivery of therapeutics will remain a distant reality unless nanocarrier design takes into account the majority, if not all, of the biological barriers that a particle encounters upon intravenous administration. By successively addressing each of these barriers, innovative design features can be rationally incorporated that will create a new generation of nanotherapeutics, realizing a paradigmatic shift in nanoparticle-based drug delivery.

In-gel digestion of proteins isolated by gel electrophoresis is a cornerstone of mass spectrometry (MS)-driven proteomics. The 10-year-old recipe by Shevchenko et al. has been optimized to increase the speed and sensitivity of analysis. The protocol is for the in-gel digestion of both silver and Coomassie-stained protein spots or bands and can be followed by MALDI-MS or LC-MS/MS analysis to identify proteins at sensitivities better than a few femtomoles of protein starting material.

By removing the fastest degrees of freedom, constraints allow for an increase of the time step in molecular simulations. In the last decade parallel simulations have become commonplace. However, up till now efficient parallel constraint algorithms have not been used with domain decomposition. In this paper the parallel linear constraint solver (P-LINCS) is presented, which allows the constraining of all bonds in macromolecules. Additionally the energy conservation properties of (P-)LINCS are assessed in view of improvements in the accuracy of uncoupled angle constraints and integration in single precision.