Barriers and facilitators to implementing medications for opioid use disorder and naloxone distribution in Veterans Affairs emergency departments.

OBJECTIVES: Safer opioid prescribing patterns, naloxone distribution, and medications for opioid use disorder (M-OUD) are an important part of decreasing opioid-related adverse events. Veterans are more likely to experience these adverse events compared to the general population. Despite treatment guidelines and ED-based opioid safety programs implemented throughout Veterans Affairs (VA) Medical Centers, many Veterans with OUD do not receive these harm reduction interventions. Prior research in other health care settings has identified barriers to M-OUD initiation and naloxone distribution; however, little is known about how this may be similar or different for health care professionals in VA ED and urgent care centers. METHODS: We conducted qualitative interviews with VA health care professionals and staff using a semistructured interview guide. We analyzed the data addressing barriers and facilitators to M-OUD treatment in the ED and naloxone distribution using descriptive matrix analysis, followed by team consensus. RESULTS: We interviewed 19 VA staff in various roles. Respondent concerns and considerations regarding the initiation of M-OUD in the ED included M-OUD initiation falling outside of ED's scope of providing acute treatment, lack of VA-approved M-OUD protocols and follow-up procedures, staffing concerns, and educational gaps. Respondents reported that naloxone was important but lacked clarity on who should prescribe it. Some respondents stated that an automated system to prescribe naloxone would be helpful, and others felt that it would not offer needed support and education to patients. Some respondents reported that naloxone would not address opioid misuse, which other respondents felt was a belief due to stigma around substance use and lack of education about treatment options. CONCLUSIONS: Our VA-based research highlights similarities of barriers and facilitators, seen in other health care settings, when implementing opioid safety initiatives. Education and training, destigmatizing substance use disorder care, and leveraging technology are important facilitators to increasing access to lifesaving therapies for OUD treatment and harm reduction.

OCRE Domains of Splicing Factors RBM5 and RBM10: Tyrosine Ring-Flip Frequencies Determined by Integrated Use of 1 H NMR Spectroscopy and Molecular Dynamics Simulations.

The 55-residue OCRE domains of the splicing factors RBM5 and RBM10 contain 15 tyrosines in compact, globular folds. At 25 °C, all 15 tyrosines show symmetric 1 H NMR spectra, with averaged signals for the pairs of δ- and ϵ-ring hydrogens. At 4 °C, two tyrosines were identified as showing 1 H NMR line-broadening due to lowered frequency of the ring-flipping. For the other 13 tyrosine rings, it was not evident, from the 1 H NMR data alone, whether they were either all flipping at high frequencies, or whether slowed flipping went undetected due to small chemical-shift differences between pairs of exchanging ring hydrogen atoms. Here, we integrate 1 H NMR spectroscopy and molecular dynamics (MD) simulations to determine the tyrosine ring-flip frequencies. In the RBM10-OCRE domain, we found that, for 11 of the 15 tyrosines, these frequencies are in the range 2.0×106 to 1.3×108  s-1 , and we established an upper limit of <1.0×106  s-1 for the remaining four residues. The experimental data and the MD simulation are mutually supportive, and their combined use extends the analysis of aromatic ring-flip events beyond the limitations of routine 1 H NMR line-shape analysis into the nanosecond frequency range.

A Kepler Workflow Tool for Reproducible AMBER GPU Molecular Dynamics.

With the drive toward high throughput molecular dynamics (MD) simulations involving ever-greater numbers of simulation replicates run for longer, biologically relevant timescales (microseconds), the need for improved computational methods that facilitate fully automated MD workflows gains more importance. Here we report the development of an automated workflow tool to perform AMBER GPU MD simulations. Our workflow tool capitalizes on the capabilities of the Kepler platform to deliver a flexible, intuitive, and user-friendly environment and the AMBER GPU code for a robust and high-performance simulation engine. Additionally, the workflow tool reduces user input time by automating repetitive processes and facilitates access to GPU clusters, whose high-performance processing power makes simulations of large numerical scale possible. The presented workflow tool facilitates the management and deployment of large sets of MD simulations on heterogeneous computing resources. The workflow tool also performs systematic analysis on the simulation outputs and enhances simulation reproducibility, execution scalability, and MD method development including benchmarking and validation.

Molecular Simulations Reveal an Unresolved Conformation of the Type IA Protein Kinase A Regulatory Subunit and Suggest Its Role in the cAMP Regulatory Mechanism.

We identify a previously unresolved, unrecognized, and highly stable conformation of the protein kinase A (PKA) regulatory subunit RIα. This conformation, which we term the "Flipback" structure, bridges conflicting characteristics in crystallographic structures and solution experiments of the PKA RIα heterotetramer. Our simulations reveal a hinge residue, G235, in the B/C helix that is conserved through all isoforms of RI. Brownian dynamics simulations suggest that the Flipback conformation plays a role in cAMP association to the A domain of the R subunit.

Electrostatic Interactions as Mediators in the Allosteric Activation of Protein Kinase A RIα.

Close-range electrostatic interactions that form salt bridges are key components of protein stability. Here we investigate the role of these charged interactions in modulating the allosteric activation of protein kinase A (PKA) via computational and experimental mutational studies of a conserved basic patch located in the regulatory subunit's B/C helix. Molecular dynamics simulations evidenced the presence of an extended network of fluctuating salt bridges spanning the helix and connecting the two cAMP binding domains in its extremities. Distinct changes in the flexibility and conformational free energy landscape induced by the separate mutations of Arg239 and Arg241 suggested alteration of cAMP-induced allosteric activation and were verified through in vitro fluorescence polarization assays. These observations suggest a mechanical aspect to the allosteric transition of PKA, with Arg239 and Arg241 acting in competition to promote the transition between the two protein functional states. The simulations also provide a molecular explanation for the essential role of Arg241 in allowing cooperative activation, by evidencing the existence of a stable interdomain salt bridge with Asp267. Our integrated approach points to the role of salt bridges not only in protein stability but also in promoting conformational transition and function.

Determinants of Treatment Eligibility in Veterans With Hepatitis C Viral Infection.

PURPOSES: The objective of this study was to determine the percentage of veterans with active hepatitis C virus (HCV) infection who were deemed to be candidates for treatment and to identify factors associated with treatment ineligibility. METHODS: This was a multisite, retrospective cohort analysis of veterans with HCV infection within the Veteran Integrated Service Network 21. Patients evaluated between August and November 2015 who were viremic and not receiving HCV treatment were included in the analysis. Reasons for treatment exclusion were determined by an experienced clinician and recorded into a regional population management dashboard. Descriptive statistics were used to describe the population. The t test for normally distributed data, the Mann-Whitney rank sum test for data that failed normality testing, or the χ2 test were used to examine differences between the treatment eligible and ineligible cohorts. Generalized linear mixed-effects models were conducted to estimate patient outcomes relevant to various disease states and characteristics while controlling for interfacility variability. FINDINGS: The cohort included 1,003 veterans within 5 medical centers; 988 (98.5%) were male, and 625 (62%) had a fibrosis 4 score >3.25, indicating the presence of ALD. According to clinician classification, 478 (48%) were considered HCV treatment candidates, whereas 525 (52%) were determined to be treatment ineligible. The most common reasons documented by clinicians for treatment ineligibility included unstable or uncontrolled comorbidities (n = 118 [22.4%]), excessive alcohol use (n = 116 [22.1%]), and treatment refusal by the patient (n = 69 [13%]). On the basis of statistical modeling and reporting odds ratios (ORs) and 95% CIs, diagnoses of active alcohol use disorder (OR = 0.68; 95% CI, 0.47-0.98; P = 0.038), hepatocellular carcinoma (OR = 0.24; 95% CI, 0.13-0.47; P < 0.001), and palliative care status (OR = 0.21; 95% CI, 0.05-0.99; P = 0.049) were statistically associated with treatment ineligibility, whereas posttraumatic stress disorder (OR = 1.48; 95% CI, 1.01-2.18; P = 0.046) was associated with treatment eligibility. There were no statistically significant differences found for other psychiatric diagnoses or an encounter for homelessness. IMPLICATIONS: Results of this study indicate that a high percentage of patients may not be considered treatment eligible at initial clinical review. Within this veteran population, the presence of uncontrolled comorbidities and excessive alcohol use were the most commonly reported reasons for treatment ineligibility. On the basis of this analysis, processes could be established to address modifiable barriers to treatment, thus expanding the number of individuals receiving potentially curative therapy for HCV infection.

Capturing Invisible Motions in the Transition from Ground to Rare Excited States of T4 Lysozyme L99A.

Proteins commonly sample a number of conformational states to carry out their biological function, often requiring transitions from the ground state to higher-energy states. Characterizing the mechanisms that guide these transitions at the atomic level promises to impact our understanding of functional protein dynamics and energy landscapes. The leucine-99-to-alanine (L99A) mutant of T4 lysozyme is a model system that has an experimentally well characterized excited sparsely populated state as well as a ground state. Despite the exhaustive study of L99A protein dynamics, the conformational changes that permit transitioning to the experimentally detected excited state (∼3%, ΔG ∼2 kcal/mol) remain unclear. Here, we describe the transitions from the ground state to this sparsely populated excited state of L99A as observed through a single molecular dynamics (MD) trajectory on the Anton supercomputer. Aside from detailing the ground-to-excited-state transition, the trajectory samples multiple metastates and an intermediate state en route to the excited state. Dynamic motions between these states enable cavity surface openings large enough to admit benzene on timescales congruent with known rates for benzene binding. Thus, these fluctuations between rare protein states provide an atomic description of the concerted motions that illuminate potential path(s) for ligand binding. These results reveal, to our knowledge, a new level of complexity in the dynamics of buried cavities and their role in creating mobile defects that affect protein dynamics and ligand binding.

Model of the Ankyrin and SOCS Box Protein, ASB9, E3 Ligase Reveals a Mechanism for Dynamic Ubiquitin Transfer.

Cullin-RING E3 ligases (CRLs) are elongated and bowed protein complexes that transfer ubiquitin over 60 Å to proteins targeted for proteasome degradation. One such CRL contains the ankyrin repeat and SOCS box protein 9 (ASB9), which binds to and partially inhibits creatine kinase (CK). While current models for the ASB9-CK complex contain some known interface residues, the overall structure and precise interface of the ASB9-CK complex remains unknown. Through an integrative modeling approach, we report a third-generation model that reveals precisely the interface interactions and also fits the shape of the ASB9-CK complex as determined by small-angle X-ray scattering. We constructed an atomic model for the entire CK-targeting CRL to uncover dominant modes of motion that could permit ubiquitin transfer. Remarkably, only the correctly docked CK-containing E3 ligase and not incorrectly docked structures permitted close approach of ubiquitin to the CK substrate.

Emerging Computational Methods for the Rational Discovery of Allosteric Drugs.

Allosteric drug development holds promise for delivering medicines that are more selective and less toxic than those that target orthosteric sites. To date, the discovery of allosteric binding sites and lead compounds has been mostly serendipitous, achieved through high-throughput screening. Over the past decade, structural data has become more readily available for larger protein systems and more membrane protein classes (e.g., GPCRs and ion channels), which are common allosteric drug targets. In parallel, improved simulation methods now provide better atomistic understanding of the protein dynamics and cooperative motions that are critical to allosteric mechanisms. As a result of these advances, the field of predictive allosteric drug development is now on the cusp of a new era of rational structure-based computational methods. Here, we review algorithms that predict allosteric sites based on sequence data and molecular dynamics simulations, describe tools that assess the druggability of these pockets, and discuss how Markov state models and topology analyses provide insight into the relationship between protein dynamics and allosteric drug binding. In each section, we first provide an overview of the various method classes before describing relevant algorithms and software packages.

Bridging scales through multiscale modeling: a case study on protein kinase A.

The goal of multiscale modeling in biology is to use structurally based physico-chemical models to integrate across temporal and spatial scales of biology and thereby improve mechanistic understanding of, for example, how a single mutation can alter organism-scale phenotypes. This approach may also inform therapeutic strategies or identify candidate drug targets that might otherwise have been overlooked. However, in many cases, it remains unclear how best to synthesize information obtained from various scales and analysis approaches, such as atomistic molecular models, Markov state models (MSM), subcellular network models, and whole cell models. In this paper, we use protein kinase A (PKA) activation as a case study to explore how computational methods that model different physical scales can complement each other and integrate into an improved multiscale representation of the biological mechanisms. Using measured crystal structures, we show how molecular dynamics (MD) simulations coupled with atomic-scale MSMs can provide conformations for Brownian dynamics (BD) simulations to feed transitional states and kinetic parameters into protein-scale MSMs. We discuss how milestoning can give reaction probabilities and forward-rate constants of cAMP association events by seamlessly integrating MD and BD simulation scales. These rate constants coupled with MSMs provide a robust representation of the free energy landscape, enabling access to kinetic, and thermodynamic parameters unavailable from current experimental data. These approaches have helped to illuminate the cooperative nature of PKA activation in response to distinct cAMP binding events. Collectively, this approach exemplifies a general strategy for multiscale model development that is applicable to a wide range of biological problems.

Conversion from thrice- to twice-daily pregabalin dosing for pain: Economic and clinical outcomes in a veteran population.

PURPOSE: Results of a study analyzing economic and clinical outcomes one year after conversion from thrice- to twice-daily pregabalin dosing for pain are presented. METHODS: A retrospective chart review was conducted at two Veterans Affairs facilities. The analyzed population included all patients receiving pregabalin for pain whose dosing was converted from thrice- to twice-daily pregabalin dosing during a one-year period. The primary endpoint was the economic impact of the conversion. Secondary endpoints included reversion to thrice-daily pregabalin dosing, pregabalin discontinuation, addition of medications for pain, and unscheduled neuropathy-related visits. RESULTS: Among the 57 patients included in the data analysis, 41 continued to take pregabalin twice daily, 10 had pregabalin discontinued, and 6 had dosing reverted to thrice daily. The mean age of patients and the distribution of add-on pain medications did not differ significantly between patients whose pregabalin dosing frequency remained at twice daily and patients whose frequency reverted to thrice daily. The costs associated with pregabalin therapy differed significantly between the preconversion and postconversion periods. A savings of $115,867 was realized from this conversion for both facilities combined over the course of one year. CONCLUSION: In patients receiving pregabalin for pain, conversion from thrice- to twice-daily pregabalin dosing-while maintaining the same daily dose-resulted in substantial cost savings while having little effect on clinical outcomes.

Allostery through the computational microscope: cAMP activation of a canonical signalling domain.

Ligand-induced protein allostery plays a central role in modulating cellular signalling pathways. Here using the conserved cyclic nucleotide-binding domain of protein kinase A's (PKA) regulatory subunit as a prototype signalling unit, we combine long-timescale, all-atom molecular dynamics simulations with Markov state models to elucidate the conformational ensembles of PKA's cyclic nucleotide-binding domain A for the cAMP-free (apo) and cAMP-bound states. We find that both systems exhibit shallow free-energy landscapes that link functional states through multiple transition pathways. This observation suggests conformational selection as the general mechanism of allostery in this canonical signalling domain. Further, we expose the propagation of the allosteric signal through key structural motifs in the cyclic nucleotide-binding domain and explore the role of kinetics in its function. Our approach integrates disparate lines of experimental data into one cohesive framework to understand structure, dynamics and function in complex biological systems.

On the Application of Molecular-Dynamics Based Markov State Models to Functional Proteins.

Owing to recent developments in computational algorithms and architectures, it is now computationally tractable to explore biologically relevant, equilibrium dynamics of realistically-sized functional proteins using all-atom molecular dynamics simulations. Molecular dynamics simulations coupled with Markov state models is a nascent but rapidly growing technology that is enabling robust exploration of equilibrium dynamics. The objective of this work is to explore the challenges of coupling molecular dynamics simulations and Markov state models in the study of functional proteins. Using recent studies as a framework, we explore progress in sampling, model building, model selection, and coarse-grained analysis of models. Our goal is to highlight some of the current challenges in applying Markov state models to realistically-sized proteins and spur discussion on advances in the field.

Progress towards automated Kepler scientific workflows for computer-aided drug discovery and molecular simulations.

We describe the development of automated workflows that support computed-aided drug discovery (CADD) and molecular dynamics (MD) simulations and are included as part of the National Biomedical Computational Resource (NBCR). The main workflow components include: file-management tasks, ligand force field parameterization, receptor-ligand molecular dynamics (MD) simulations, job submission and monitoring on relevant high-performance computing (HPC) resources, receptor structural clustering, virtual screening (VS), and statistical analyses of the VS results. The workflows aim to standardize simulation and analysis and promote best practices within the molecular simulation and CADD communities. Each component is developed as a stand-alone workflow, which allows easy integration into larger frameworks built to suit user needs, while remaining intuitive and easy to extend.

Therapeutic options in docetaxel-refractory metastatic castration-resistant prostate cancer: a cost-effectiveness analysis.

BACKGROUND: Docetaxel is an established first-line therapy to treat metastatic castration-resistant prostate cancer (mCRPC). Recently, abiraterone and cabazitaxel were approved for use after docetaxel failure, with improved survival. National Institute for Health and Clinical Excellence (NICE) preliminary recommendations were negative for both abiraterone (now positive in final recommendation) and cabazitaxel (negative in final recommendation). OBJECTIVE: To evaluate the cost-effectiveness of abiraterone, cabazitaxel, mitoxantrone and prednisone for mCRPC treatment in US. METHODS: A decision-tree model was constructed to compare the two mCRPC treatments versus two placebos over 18 months from a societal perspective. Chance nodes include baseline pain as a severity indicator, grade III/IV side-effects, and survival at 18 months. Probabilities, survival and health utilities were from published studies. Model cost inputs included drug treatment, side-effect management and prevention, radiation for pain, and death associated costs in 2010 US dollars. RESULTS: Abiraterone is a cost-effective choice at $94K/QALY (quality adjusted life years) compared to placebo in our base-case analysis. Cabazitaxel and abiraterone are the most effective, yet also most expensive agents. The incremental cost-effectiveness ratios (ICER) at base-case are $101K/QALY (extended dominated) for mitoxantrone vs. placebo, $91K/QALY for abiraterone vs. mitoxantrone, $956K/QALY for cabazitaxel vs. abiraterone. Abiraterone becomes less cost-effective as its AWP increases, or if the cost of mitoxantrone side-effect management decreases. Increases in the percentage of patients with baseline pain leads to an increased ICER for both mitoxantrone and abiraterone, but mitoxantrone does relatively better. Cabazitaxel remains not cost-effective. CONCLUSION: Our base case model suggests that abiraterone is a cost-effective option in docetaxel-refractory mCRPC patients. Newer treatments will also need a CEA assessment compared to abiraterone.

Cytotoxicity of selected medicinal and nonmedicinal plant extracts to microbial and cervical cancer cells.

This study investigated the cytotoxicity of 55 species of plants. Each plant was rated as medicinal, or nonmedicinal based on the existing literature. About 79% of the medicinal plants showed some cytotoxicity, while 75% of the nonmedicinal plants showed bioactivity. It appears that Asteraceae, Labiatae, Pinaceae, and Chenopodiaceae were particularly active against human cervical cancer cells. Based on the literature, only three of the 55 plants have been significantly investigated for cytotoxicity. It is clear that there is much toxicological work yet to be done with both medicinal and nonmedicinal plants.

Comparative efficacy of ezetimibe/simvastatin, rosuvastatin, and atorvastatin in uncontrolled hyperlipidemia patients.

OBJECTIVE: Treatment of dyslipidemia in high-risk patients specifies a low-density lipoprotein (LDL) cholesterol <100 mg/dL. The efficacy of higher-potency regimens in clinical practice in patients who have not achieved their LDL goal on generic therapy is not well characterized. The primary objective of this study was to determine the LDL-lowering efficacy of higher-potency strategies (ezetimibe/simvastatin, rosuvastatin, and atorvastatin) in high-risk patients who were switched from simvastatin therapy. Secondary objectives were to evaluate patient adherence to these therapies, determine the efficacy of these interventions on other lipid parameters, and define the incidence of adverse effects. STUDY DESIGN: Retrospective data analysis derived from the Veterans Affairs Health Care System VISN 21 over a 3-year time period. METHODS: Lipid data were assessed prior to and within 2 to 6 months following the conversion from simvastatin. Adherence to therapy was determined by medication refill data. RESULTS: Treatment with ezetimibe/simvastatin resulted in significantly greater reductions in LDL compared with rosuvastatin or atorvastatin (37 vs 25 and 26 mg/dL, respectively; P <0.05). Adherence to therapy was 51% of all patients studied. All treatments significantly lowered total cholesterol, high-density lipoprotein, and triglycerides when compared with simvastatin. There was no difference between treatment groups in the number of adverse events. CONCLUSIONS: At the doses used in this population, ezetimibe/simvastatin resulted in greater LDL reductions than rosuvastatin or atorvastatin. The clinical impact of these differences is as yet undetermined.

Using free energy of binding calculations to improve the accuracy of virtual screening predictions.

Virtual screening of small molecule databases against macromolecular targets was used to identify binding ligands and predict their lowest energy bound conformation (i.e., pose). AutoDock4-generated poses were rescored using mean-field pathway decoupling free energy of binding calculations and evaluated if these calculations improved virtual screening discrimination between bound and nonbound ligands. Two small molecule databases were used to evaluate the effectiveness of the rescoring algorithm in correctly identifying binders of L99A T4 lysozyme. Self-dock calculations of a database containing compounds with known binding free energies and cocrystal structures largely reproduced experimental measurements, although the mean difference between calculated and experimental binding free energies increased as the predicted bound poses diverged from the experimental poses. In addition, free energy rescoring was more accurate than AutoDock4 scores in discriminating between known binders and nonbinders, suggesting free energy rescoring could be a useful approach to reduce false positive predictions in virtual screening experiments.

Structural basis for substrate specificity of alphavirus nsP2 proteases.

The alphavirus nsP2 protease is essential for correct processing of the alphavirus nonstructural polyprotein (nsP1234) and replication of the viral genome. We have combined molecular dynamics simulations with our structural studies to reveal features of the nsP2 protease catalytic site and S1'-S4 subsites that regulate the specificity of the protease. The catalytic mechanism of the nsP2 protease appears similar to the papain-like cysteine proteases, with the conserved catalytic dyad forming a thiolate-imidazolium ion pair in the nsP2-activated state. Substrate binding likely stabilizes this ion pair. Analysis of bimolecular complexes of Venezuelan equine encephalitis virus (VEEV) nsP2 protease with each of the nsP1234 cleavage sites identified protease residues His(510), Ser(511), His(546) and Lys(706) as critical for cleavage site recognition. Homology modelling and molecular dynamics simulations of diverse alphaviruses and their cognate cleavage site sequences revealed general features of substrate recognition that operate across alphavirus strains as well as strain specific covariance between binding site and cleavage site residues. For instance, compensatory changes occurred in the P3 and S3 subsite residues to maintain energetically favourable complementary binding surfaces. These results help explain how alphavirus nsP2 proteases recognize different cleavage sites within the nonstructural polyprotein and discriminate between closely related cleavage targets.

Structure-based discovery of dengue virus protease inhibitors.

Dengue virus belongs to the family Flaviviridae and is a major emerging pathogen for which the development of vaccines and antiviral therapy has seen little success. The NS3 viral protease is a potential target for antiviral drugs since it is required for virus replication. The goal of this study was to identify novel dengue virus (type 2; DEN2V) protease inhibitors for eventual development as effective anti-flaviviral drugs. The EUDOC docking program was used to computationally screen a small-molecule library for compounds that dock into the P1 pocket and the catalytic site of the DEN2V NS3 protease domain apo-structure [Murthy, K., Clum, S., Padmanabhan, R., 1999. Crystal structure and insights into interaction of the active site with substrates by molecular modeling and structural analysis of mutational effects. J. Biol. Chem. 274, 5573-5580] and the Bowman-Birk inhibitor-bound structure [Murthy, K., Judge, K., DeLucas, L., Padmanabhan, R., 2000. Crystal structure of dengue virus NS3 protease in complex with a Bowman-Birk inhibitor: implications for flaviviral polyprotein processing and drug design. J. Mol. Biol. 301, 759-767]. The top 20 computer-identified hits that demonstrated the most favorable scoring "energies" were selected for in vitro assessment of protease inhibition. Preliminary protease activity assays demonstrated that more than half of the tested compounds were soluble and exhibited in vitro inhibition of the DEN2V protease. Two of these compounds also inhibited viral replication in cell culture experiments, and thus are promising compounds for further development.