Cancer is a major cause of morbidity and mortality worldwide due to its ability to evade immune surveillance and metastasize from its origin to a secondary point of contact. Though several treatment techniques have been developed to suppress or manage cancer spread, a strategy for total control over the disease continues to evade researchers. In considering ways to control or prevent cancer from metastasizing to the bone, we analyze the impact of the calcium-sensing receptor (CaSR), whose primary role is to maintain calcium (Ca2+) homeostasis in cellular and systemic physiological processes. Selleckchem JAK inhibitor CaSR is a pleiotropic receptor capable of enhancing the proliferation of some cancers such as breast, lung, prostate and kidney cancers at its primary site(s) and stimulating bone metastasis, while exerting a suppressive effect in others such as colon cancer. The activity of CaSR not only increases cancer cell proliferation, migration and suppression of apoptosis in the organs indicated, but also increases the secretion of parathyroid hormone-related protein (PTHrP) and epiregulin, which induce osteolytic activity and osteoblastic suppression. In addition, released cytokines and Ca2+ from bone resorption are critical factors that further promote cancer proliferation. In this review, we seek to highlight previous viewpoints on CaSR, discuss its role in a new context, and consider its potential clinical application in cancer treatment.Preferential lipid solvation of the G-protein-coupled A2A adenosine receptor (A2AR) is evaluated from 35 μs of all-atom molecular dynamics simulation. A coarse-grained transition matrix algorithm is developed to overcome slow equilibration of the first solvation shell, obtaining estimates of the free energy of solvation by different lipids for the receptor in different activation states. Results indicate preference for solvation by unsaturated chains, which favors the active receptor. A model for lipid-dependent G-protein-coupled receptor activity is proposed in which the chemical potential of lipids in the bulk membrane modulates receptor activity. The entropies associated with moving saturated and unsaturated lipids from bulk to A2AR’s first solvation shell are evaluated. Overall, the acyl chains are more disordered (i.e., obtain a favorable entropic contribution) when partitioning to the receptor surface, and this effect is augmented for the saturated chains, which are relatively more ordered in bulk.Living organisms typically store their genomic DNA in a condensed form. Mechanistically, DNA condensation can be driven by macromolecular crowding, multivalent cations, or positively charged proteins. At low DNA concentration, condensation triggers the conformational change of individual DNA molecules into a compacted state, with distinct morphologies. Above a critical DNA concentration, condensation goes along with phase separation into a DNA-dilute and a DNA-dense phase. The latter DNA-dense phase can have different material properties and has been reported to be rather liquid-like or solid-like depending on the characteristics of the DNA and the solvent composition. Here, we systematically assess the influence of DNA length on the properties of the resulting condensates. We show that short DNA molecules with sizes below 1 kb can form dynamic liquid-like assemblies when condensation is triggered by polyethylene glycol and magnesium ions, binding of linker histone H1, or nucleosome reconstitution in combinate our understanding of biomolecular condensates involving DNA.Cholesterol is an integral component of mammalian membranes. It has been shown to modulate membrane fluidity and dynamics and alter integral membrane protein function. However, understanding the molecular mechanisms of how cholesterol impacts protein function is complicated by limited and conflicting structural data. Because of the nature of the crystallization and cryo-EM structure determination, it is difficult to distinguish between specific and biologically relevant interactions and a nonspecific association. The only widely recognized search algorithm for cholesterol-integral-membrane-protein interaction sites is sequence based, i.e., searching for the so-called “Cholesterol Recognition/interaction Amino acid Consensus” motif. Although these motifs are present in numerous integral membrane proteins, there is inconclusive evidence to support their necessity or sufficiency for cholesterol binding. Here, we leverage the increasing number of experimental cholesterol-integral-membrane-protein structures to systematically analyze putative interaction sites based on their spatial arrangement and evolutionary conservation. This analysis creates three-dimensional representations of general cholesterol interaction sites that form clusters across multiple integral membrane protein classes. We also classify cholesterol-integral-membrane-protein interaction sites as either likely-specific or nonspecific. Information gleaned from our characterization will eventually enable a structure-based approach to predict and design cholesterol-integral-membrane-protein interaction sites.

Since COVID-19 was identified, its clinical and biological heterogeneity has been recognized. Identifying COVID-19 phenotypes might help guide basic, clinical, and translational research efforts.

Does the clinical spectrum of patients with COVID-19 contain distinct phenotypes and subphenotypes?

We included adult patients (≥ 18 years) positive for laboratory-confirmed SARS-CoV-2 infection from a prospective COVID-19 registry database in the Cleveland Clinic Health System in Ohio and Florida. The patients were split into training and testing sets. Using latent class analysis (LCA), we first identified phenotypic clusters of patients with COVID-19 based on demographics, comorbidities, and presenting symptoms. We then identified subphenotypes of hospitalized patients with additional blood biomarker data measured on hospital admission. The associations of phenotypes/subphenotypes and clinical outcomes were investigated. Multivariable prediction models were established to predict assignment to the LCA-defined phenotypes and subphenotypes and then evaluated on an independent testing set.