The budding of membranes and curvature generation is common to many forms of trafficking in cells. Clathrin-mediated endocytosis, as a prototypical example of trafficking, has been studied in great detail using a variety of experimental systems and methods. Recently, advances in experimental methods have led to great strides in insights on the molecular mechanisms and the spatiotemporal dynamics of the protein machinery associated with membrane curvature generation. These advances have been ably supported by computational models, which have given us insights into the underlying mechanical principles of clathrin-mediated endocytosis. On the other hand, targeted experimental perturbation of membranes has lagged behind that of proteins in cells. In this area, modeling is especially critical to interpret experimental measurements in a mechanistic context. Here, we discuss the contributions made by these models to our understanding of endocytosis and identify opportunities to strengthen the connections between models and experiments.

Biomembranes adopt varying morphologies that are vital to cellular functions. Many studies use computational modeling to understand how various mechanochemical factors contribute to membrane shape transformations. Compared with approximation-based methods (e.g., finite element method [FEM]), the class of discrete mesh models offers greater flexibility to simulate complex physics and shapes in three dimensions; its formulation produces an efficient algorithm while maintaining coordinate-free geometric descriptions. However, ambiguities in geometric definitions in the discrete context have led to a lack of consensus on which discrete mesh model is theoretically and numerically optimal; a bijective relationship between the terms contributing to both the energy and forces from the discrete and smooth geometric theories remains to be established. We address this and present an extensible framework, Mem3DG, for modeling 3D mechanochemical dynamics of membranes based on discrete differential geometry (DDG) on triangulated meshes. The formalism of DDG resolves the inconsistency and provides a unifying perspective on how to relate the smooth and discrete energy and forces. To demonstrate, Mem3DG is used to model a sequence of examples with increasing mechanochemical complexity: recovering classical shape transformations such as 1) biconcave disk, dumbbell, and unduloid; and 2) spherical bud on spherical, flat-patch membrane; investigating how the coupling of membrane mechanics with protein mobility jointly affects phase and shape transformation. As high-resolution 3D imaging of membrane ultrastructure becomes more readily available, we envision Mem3DG to be applied as an end-to-end tool to simulate realistic cell geometry under user-specified mechanochemical conditions.

Efficient prediction and ranking of small molecule binders by their kinetic ( k_on and k_off) and thermodynamic ( Δ G) properties can be a valuable metric for drug lead optimization, as these quantities are often indicators of in vivo efficacy. We have previously described a hybrid molecular dynamics, Brownian dynamics, and milestoning model, Simulation Enabled Estimation of Kinetic Rates (SEEKR), that can predict k_on's, k_off's, and Δ G's. Here we demonstrate the effectiveness of this approach for ranking a series of seven small molecule compounds for the model system, β-cyclodextrin, based on predicted k_on's and k_off's. We compare our results using SEEKR to experimentally determined rates as well as rates calculated using long time scale molecular dynamics simulations and show that SEEKR can effectively rank the compounds by k_off and Δ G with reduced computational cost. We also provide a discussion of convergence properties and sensitivities of calculations with SEEKR to establish "best practices" for its future use.

CC chemokine receptor 2 (CCR2) is a part of the chemokine receptor family, an important class of therapeutic targets. These class A G-protein coupled receptors (GPCRs) are involved in mammalian signaling pathways and control cell migration toward endogenous CC chemokine ligands, named for the adjacent cysteine motif on their N terminus. Chemokine receptors and their associated ligands are involved in a wide range of diseases and thus have become important drug targets. CCR2, in particular, promotes the metastasis of cancer cells and is also implicated in autoimmunity-driven type-1 diabetes, diabetic nephropathy, multiple sclerosis, asthma, atherosclerosis, neuropathic pain, and rheumatoid arthritis. Although promising, CCR2 antagonists have been largely unsuccessful to date. Here, we investigate the effect of an orthosteric and an allosteric antagonist on CCR2 dynamics by coupling long-timescale molecular dynamics simulations with Markov-state model theory. We find that the antagonists shift CCR2 into several stable inactive conformations that are distinct from the crystal structure conformation and disrupt a continuous internal water and sodium ion pathway, preventing transitions to an active-like state. Several metastable conformations present a cryptic drug-binding pocket near the allosteric site that may be amenable to targeting with small molecules. Without antagonists, the apo dynamics reveal intermediate conformations along the activation pathway that provide insight into the basal dynamics of CCR2 and may also be useful for future drug design.

We introduce CASC: a new, modern, and header-only C++ library which provides a data structure to represent arbitrary dimension abstract simplicial complexes (ASC) with user-defined classes stored directly on the simplices at each dimension. This is accomplished by using the latest C++ language features including variadic template parameters introduced in C++11 and automatic function return type deduction from C++14. Effectively CASC decouples the representation of the topology from the interactions of user data. We present the innovations and design principles of the data structure and related algorithms. This includes a metadata aware decimation algorithm which is general for collapsing simplices of any dimension. We also present an example application of this library to represent an orientable surface mesh.

Dendritic spines act as biochemical computational units and must adapt their responses according to their activation history. Calcium influx acts as the first signaling step during postsynaptic activation and is a determinant of synaptic weight change. Dendritic spines also come in a variety of sizes and shapes. To probe the relationship between calcium dynamics and spine morphology, we used a stochastic reaction-diffusion model of calcium dynamics in idealized and realistic geometries. We show that despite the stochastic nature of the various calcium channels, receptors, and pumps, spine size and shape can modulate calcium dynamics and subsequently synaptic weight updates in a deterministic manner. Through a series of exhaustive simulations and analyses, we found that the calcium dynamics and synaptic weight change depend on the volume-to-surface area of the spine. The relationships between calcium dynamics and spine morphology identified in idealized geometries also hold in realistic geometries, suggesting that there are geometrically determined deterministic relationships that may modulate synaptic weight change.

In this perspective, we examine three key aspects of an end-to-end pipeline for realistic cellular simulations: reconstruction and segmentation of cellular structures; generation of cellular structures; and mesh generation, simulation, and data analysis. We highlight some of the relevant prior work in these distinct but overlapping areas, with a particular emphasis on current use of machine learning technologies, as well as on future opportunities.

The protein, azurin, has enabled the study of the tryptophan radical. Upon UV excitation of tyrosine-deficient apoazurin and in the presence of a Co(III) electron acceptor, the neutral radical (W48•) is formed. The lifetime of W48• in apoazurin is 41 s, which is shorter than the lifetime of several hours in Zn-substituted azurin. Molecular dynamics simulations revealed enhanced fluctuations of apoazurin which likely destabilize W48•. The photophysics of W48 was investigated to probe the precursor state for ET. The phosphorescence intensity was eliminated in the presence of an electron acceptor while the fluorescence was unchanged; this quenching of the phosphorescence is attributed to ET. The kinetics associated with W48• were examined with a model that incorporates intersystem crossing, ET, deprotonation, and decay of the cation radical. The estimated rate constants for ET (6 × 10⁶ s^-1) and deprotonation (3 × 10⁵ s^-1) are in agreement with a photoinduced mechanism where W48• is derived from the triplet state. The triplet as the precursor state for ET was supported by photolysis of apoazurin with 280 nm in the absence and presence of triplet-absorbing 405 nm light. Absorption bands from the neutral radical were observed only in the presence of blue light.

Objective

The median age of single homeless adults is over 50, yet little is known about their emergency department (ED) use. We describe use of and factors associated with ED use in a sample of homeless adults 50 and older.

Methods

We recruited 350 participants who were homeless and 50 or older in Oakland, California. We interviewed participants about residential history in the prior 6 months, health status, health-related behaviors, and health services use and assessed cognition and mobility. Our primary outcome was the number of ED visits in the prior 6 months based on medical record review. We used negative binomial regression to examine factors associated with ED use.

Results

In the 6 months prior to enrollment, 46.3% of participants spent the majority of their time unsheltered; 25.1% cycled through multiple institutions including shelters, hospitals, and jails; 16.3% primarily stayed with family or friends; and 12.3% had become homeless recently after spending much of the prior 6 months housed. Half (49.7%) of participants made at least one ED visit in the past 6 months; 6.6% of participants accounted for 49.9% of all visits. Most (71.8%) identified a regular non-ED source of healthcare; 7.3% of visits resulted in hospitalization. In multivariate models, study participants who used multiple institutions (incidence rate ratio [IRR] = 2.27; 95% confidence interval [CI] = 1.08 to 4.77) and who were unsheltered (IRR = 2.29; 95% CI = 1.17 to 4.48) had higher ED use rates than participants who had been housed for most of the prior 6 months. In addition, having health insurance/coverage (IRR = 2.6; CI = 1.5 to 4.4), a history of psychiatric hospitalization (IRR = 1.80; 95% CI = 1.09 to 2.99), and severe pain (IRR = 1.72; 95% CI = 1.07 to 2.76) were associated with higher ED visit rates.

Conclusions

A sample of adults aged 50 and older who were homeless at study entry had higher rates of ED use in the prior 6 months than the general U.S. age-matched population. Within the sample, ED use rates varied based on individuals' residential histories, suggesting that individuals' ED use is related to exposure to homelessness.

Individuals experiencing homelessness in the United States are aging; little is known about chronic pain in this population. In a cross-sectional, population-based study, we interviewed 350 homeless individuals aged 50 years and older to describe pain experienced by older persons experiencing homelessness and to assess factors associated with chronic moderate to severe pain, defined as pain lasting ≥3 months, with a past week average severity score of 5 to 10 (scale 0-10). The median age of participants was 58 years. Participants were predominantly African American (79.6%) and male (77.3%). Overall, 46.8% reported chronic moderate to severe pain. Almost half of participants reported a diagnosis of arthritis (44.3%) and one-third reported symptoms consistent with post-traumatic stress disorder (PTSD; 32.8%). Three-quarters (75.3%) endorsed a personal history of abuse. In multivariate analyses, PTSD (adjusted odds ratio [AOR]: 2.2, 95% confidence interval [CI], 1.4-3.7), arthritis (AOR: 4.8, 95% CI, 3.0-7.8), and history of experiencing abuse (AOR: 2.4, 95% CI, 1.3-4.3) were associated with chronic moderate to severe pain. HIV status, diabetes, depressive symptoms, and substance use were not associated with pain. Clinicians should consider the management of associated mental health conditions and the sequelae of experiencing abuse in the treatment of chronic pain in older adults experiencing homelessness.

Perspective

This article describes the prevalence and factors associated with chronic pain in older homeless adults. Almost half report chronic pain, which was associated with PTSD, arthritis, and personal history of abuse. Clinicians should address chronic pain, trauma, and the associated mental health conditions in this high-risk population.