Relational community engagement within health interventions at varied outcome scales.

Relational community engagement may be a powerful approach with multiple health outcomes. Relational community engagement has the potential to promote health and involves collaborative efforts between multiple stakeholders. The COVID-19 pandemic further highlighted the centrality of community engagement in health crises. Challenges continue to persist, however, in genuinely engaging and empowering communities for better health outcomes. Understanding the multi-level and complex relational nature of community engagement is essential to comprehend its influence on health at micro, meso, and macro scales of influence. The purpose of this narrative review was to synthesize the literature on relational community engagement within varied health interventions at the three major system levels (micro, meso, and macro) to support the development of future research agendas. At the micro level, relational community engagement interventions demonstrated a range of positive outcomes including: increased sense of control, satisfaction, positive behavior, improved knowledge, behavior change, empowerment, and overall positive health and social outcomes. At the meso level, relational community engagement interventions resulted in increased trust between stakeholders and groups/teams, and increased community senses of ownership of interventions, decisions, structures. At the macro level, relational community engagement interventions influenced broader societal factors and had positive impacts on health policy and governance including collaboration between sectors and communities as well as increased access to services. The review highlights the potential versatility and effectiveness of interventions that prioritize relationships, health promotion, and social change while underscoring the significance of holistic and community-centered approaches in addressing diverse health and social challenges.

Key Factors Regulating the Interdomain Dynamics May Contribute to the Assembly of ASC.

The canonical ASC domains, PYD and CARD, are interconnected by a lengthy, semi-flexible linker. The molecular basis and purpose of ASC's highly dynamic feature remain elusive. In this study, all-atom molecular dynamics simulations were utilized to examine the role of the linker and the interdomain dynamics of the ASC monomer. As revealed in the principal component analysis (PCA), the flexible linker enables interdomain dynamics and rotation. The stumbling between domains is partially attributed to the helical portion of N-terminal residues in the linker. Additionally, the linker exhibits a certain structural preference due to the turn-type structural inclination of the N-terminal and the presence of several prolines on the linker. Such structural preferences lead to the unavailability of regions for PYD type I interactions to CARDs, as evidenced by the CARD spatial restraint analysis. In conclusion, the semi-flexible linker introduces functionally relevant interdomain dynamics, potentially enhancing PYD self-assembly and the subsequent assembly of the inflammasome complex.

Investigating the Mechanical Properties and Flexibility of N-BAR Domains in PICK1 by Molecular Dynamics Simulations.

INTRODUCTION: The proteins of the Bin/Amphiphysin/Rvs167 (BAR) domain superfamily are believed to induce membrane curvature. PICK1 is a distinctive protein that consists of both a BAR and a PDZ domain, and it has been associated with numerous diseases. It is known to facilitate membrane curvature during receptor-mediated endocytosis. In addition to understanding how the BAR domain facilitates membrane curvature, it's particularly interesting to unravel the hidden links between the structural and mechanical properties of the PICK1 BAR domain. METHODS: This paper employs steered molecular dynamics (SMD) to investigate the mechanical properties associated with structural changes in the PICK1 BAR domains. RESULTS: Our findings suggest that not only do helix kinks assist in generating curvature of BAR domains, but they may also provide the additional flexibility required to initiate the binding between BAR domains and the membrane. CONCLUSION: We have observed a complex interaction network within the BAR monomer and at the binding interface of the two BAR monomers. This network is crucial for maintaining the mechanical properties of the BAR dimer. Owing to this interaction network, the PICK1 BAR dimer exhibits different responses to external forces applied in opposite directions.

Emulsion-induced polymersomes taming tetrodotoxin for prolonged duration local anesthesia.

Injectable local anesthetics that can provide a continuous nerve block approximating the duration of a pain state would be a life-changing solution for patients experiencing post-operative pain or chronic pain. Tetrodotoxin (TTX) is a site 1 sodium channel blocker that is extremely potent compared to clinically used local anesthetics. Challengingly, TTX doses are limited by its associated systemic toxicity, thus shortening the achievable duration of nerve blocks. Here, we explore emulsion-induced polymersomes (EIP) as a drug delivery system to safely use TTX for local anesthesia. By emulsifying hyperbranched polyglycerol-poly (propylene glycol)-hyperbranched polyglycerol (HPG-PPG-HPG) in TTX aqueous solution, HPG-PPG-HPG self-assembled into micrometer-sized polymersomes within seconds. The formed polymersomes have microscopically visible internal aqueous pockets that encapsulate TTX with an encapsulation efficiency of up to 94%. Moreover, the polymersomes are structurally stable, enabling sustained TTX release. In vivo, the freshly prepared EIP/TTX formulation can be directly injected and increased the tolerated dose of TTX in Sprague-Dawley rats to 11.5 µg without causing any TTX-related systemic toxicity. In the presence of the chemical penetration enhancer (CPE) sodium octyl sulfate (SOS), a single perineural injection of EIP/TTX/SOS formulation produced a reliable sciatic nerve block for 22 days with minimal local toxicity.

Investigating the allosteric response of the PICK1 PDZ domain to different ligands with all-atom simulations.

The PDZ family is comprised of small modular domains that play critical roles in the allosteric modulation of many cellular signaling processes by binding to the C-terminal tail of different proteins. As dominant modular proteins that interact with a diverse set of peptides, it is of particular interest to explore how different binding partners induce different allosteric effects on the same PDZ domain. Because the PICK1 PDZ domain can bind different types of ligands, it is an ideal test case to answer this question and explore the network of interactions that give rise to dynamic allostery. Here, we use all-atom molecular dynamics simulations to explore dynamic allostery in the PICK1 PDZ domain by modeling two PICK1 PDZ systems: PICK1 PDZ-DAT and PICK1 PDZ-GluR2. Our results suggest that ligand binding to the PICK1 PDZ domain induces dynamic allostery at the αA helix that is similar to what has been observed in other PDZ domains. We found that the PICK1 PDZ-ligand distance is directly correlated with both dynamic changes of the αA helix and the distance between the αA helix and ßB strand. Furthermore, our work identifies a hydrophobic core between DAT/GluR2 and I35 as a key interaction in inducing such dynamic allostery. Finally, the unique interaction patterns between different binding partners and the PICK1 PDZ domain can induce unique dynamic changes to the PICK1 PDZ domain. We suspect that unique allosteric coupling patterns with different ligands may play a critical role in how PICK1 performs its biological functions in various signaling networks.

Recognizing the Binding Pattern and Dissociation Pathways of the p300 Taz2-p53 TAD2 Complex.

The dynamic association and dissociation between proteins are the basis of cellular signal transduction. This process becomes much more complicated if one or both interaction partners are intrinsically disordered because intrinsically disordered proteins can undergo disorder-to-order transitions upon binding to their partners. p53, a transcription factor with disordered regions, plays significant roles in many cellular signaling pathways. It is critical to understand the binding/unbinding mechanism involving these disordered regions of p53 at the residue level to reveal how p53 performs its biological functions. Here, we studied the dissociation process of the intrinsically disordered N-terminal transactivation domain 2 (TAD2) of p53 and the transcriptional adaptor zinc-binding 2 (Taz2) domain of transcriptional coactivator p300 using a combination of classical molecular dynamics, steered molecular dynamics, self-organizing maps, and time-resolved force distribution analysis (TRFDA). We observed two different dissociation pathways with different probabilities. One dissociation pathway starts from the TAD2 N-terminus and propagates to the α-helix and finally the C-terminus. The other dissociation pathway is in the opposite order. Subsequent TRFDA results reveal that key residues in TAD2 play critical roles. Besides the residues in agreement with previous experimental results, we also highlighted some other residues that play important roles in the disassociation process. In the dissociation process, non-native interactions were formed to partially compensate for the energy loss due to the breaking of surrounding native interactions. Moreover, our statistical analysis results of other experimentally determined complex structures involving either Taz2 or TAD2 suggest that the binding of the Taz2-TAD2 complex is mainly governed by the binding site of Taz2, which includes three main binding regions. Therefore, the complexes involving Taz2 may follow similar binding/unbinding behaviors, which could be studied together to generate common principles.

Three Binding Conformations of BIO124 in the Pocket of the PICK1 PDZ Domain.

The PDZ family has drawn attention as possible drug targets because of the domains' wide ranges of function and highly conserved binding pockets. The PICK1 PDZ domain has been proposed as a possible drug target because the interactions between the PICK1 PDZ domain and the GluA2 subunit of the AMPA receptor have been shown to progress neurodegenerative diseases. BIO124 has been identified as a sub µM inhibitor of the PICK1-GluA2 interaction. Here, we use all-atom molecular dynamics simulations to reveal the atomic-level interaction pattern between the PICK1 PDZ domain and BIO124. Our simulations reveal three unique binding conformations of BIO124 in the PICK1 PDZ binding pocket, referred to here as state 0, state 1, and state 2. Each conformation is defined by a unique hydrogen bonding network and a unique pattern of hydrophobic interactions between BIO124 and the PICK1 PDZ domain. Interestingly, each conformation of BIO124 results in different dynamic changes to the PICK1 PDZ domain. Unlike states 1 and 2, state 0 induces dynamic coupling between BIO124 and the αA helix. Notably, this dynamic coupling with the αA helix is similar to what has been observed in other PDZ-ligand complexes. Our analysis indicates that the interactions formed between BIO124 and I35 may be the key to inducing dynamic coupling with the αA helix. Lastly, we suspect that the conformational shifts observed in our simulations may affect the stability and thus the overall effectiveness of BIO124. We propose that a physically larger inhibitor may be necessary to ensure sufficient interactions that permit stable binding between a drug and the PICK1 PDZ domain.

Benchmarking the Accuracy of AlphaFold 2 in Loop Structure Prediction.

The inhibition of protein-protein interactions is a growing strategy in drug development. In addition to structured regions, many protein loop regions are involved in protein-protein interactions and thus have been identified as potential drug targets. To effectively target such regions, protein structure is critical. Loop structure prediction is a challenging subgroup in the field of protein structure prediction because of the reduced level of conservation in protein sequences compared to the secondary structure elements. AlphaFold 2 has been suggested to be one of the greatest achievements in the field of protein structure prediction. The AlphaFold 2 predicted protein structures near the X-ray resolution in the Critical Assessment of protein Structure Prediction (CASP 14) competition in 2020. The purpose of this work is to survey the performance of AlphaFold 2 in specifically predicting protein loop regions. We have constructed an independent dataset of 31,650 loop regions from 2613 proteins (deposited after the AlphaFold 2 was trained) with both experimentally determined structures and AlphaFold 2 predicted structures. With extensive evaluation using our dataset, the results indicate that AlphaFold 2 is a good predictor of the structure of loop regions, especially for short loop regions. Loops less than 10 residues in length have an average Root Mean Square Deviation (RMSD) of 0.33 Å and an average the Template Modeling score (TM-score) of 0.82. However, we see that as the number of residues in a given loop increases, the accuracy of AlphaFold 2's prediction decreases. Loops more than 20 residues in length have an average RMSD of 2.04 Å and an average TM-score of 0.55. Such a correlation between accuracy and length of the loop is directly linked to the increase in flexibility. Moreover, AlphaFold 2 does slightly over-predict α-helices and ß-strands in proteins.

AlphaFold illuminates half of the dark human proteins.

We investigate the use of confidence scores to evaluate the accuracy of a given AlphaFold (AF2) protein model for drug discovery. Prediction of accuracy is improved by not considering confidence scores below 80 due to the effects of disorder. On a set of recent crystal structures, 95% are likely to have accurate folds. Conformational discordance in the training set has a much more significant effect on accuracy than sequence divergence. We propose criteria for models and residues that are possibly useful for virtual screening. Based on these criteria, AF2 provides models for half of understudied (dark) human proteins and two-thirds of residues in those models.

Allosterism in the PDZ Family.

Dynamic allosterism allows the propagation of signal throughout a protein. The PDZ (PSD-95/Dlg1/ZO-1) family has been named as a classic example of dynamic allostery in small modular domains. While the PDZ family consists of more than 200 domains, previous efforts have primarily focused on a few well-studied PDZ domains, including PTP-BL PDZ2, PSD-95 PDZ3, and Par6 PDZ. Taken together, experimental and computational studies have identified regions of these domains that are dynamically coupled to ligand binding. These regions include the αA helix, the αB lower-loop, and the αC helix. In this review, we summarize the specific residues on the αA helix, the αB lower-loop, and the αC helix of PTP-BL PDZ2, PSD-95 PDZ3, and Par6 PDZ that have been identified as participants in dynamic allostery by either experimental or computational approaches. This review can serve as an index for researchers to look back on the previously identified allostery in the PDZ family. Interestingly, our summary of previous work reveals clear consistencies between the domains. While the PDZ family has a low sequence identity, we show that some of the most consistently identified allosteric residues within PTP-BL PDZ2 and PSD-95 PDZ3 domains are evolutionarily conserved. These residues include A46/A347, V61/V362, and L66/L367 on PTP-BL PDZ2 and PSD-95 PDZ3, respectively. Finally, we expose a need for future work to explore dynamic allostery within (1) PDZ domains with multiple binding partners and (2) multidomain constructs containing a PDZ domain.

Correlates of solitary alcohol and cannabis use among American Indian adolescents.

BACKGROUND: Solitary substance use, or using substances while alone, is common among adolescents but understudied. This is the first study to examine solitary substance use among American Indian (AI) adolescents. The objective was to examine correlates of solitary alcohol use and solitary cannabis use that occur within the individual, family, school, peer, and cultural domains of the social ecology. METHOD: Data were from the 2009-2013 Drug Use Among Young American Indians Study, a cross-sectional cohort study. Two sets of hierarchical logistic regressions were conducted to examine solitary alcohol use (getting drunk) among lifetime alcohol users (n = 2082; Mage = 15.12 years; SD = 1.68; 54.2% female) and solitary cannabis use among lifetime cannabis users (n = 2085; Mage = 14.99 years; SD = 1.69; 50.5% female), including adjustment for level of substance involvement. RESULTS: Prevalence of solitary alcohol use among lifetime drinkers was 24.9%. Among lifetime cannabis users, 53.6% reported solitary cannabis use. Regression analyses for solitary alcohol use showed statistically significant positive associations with coping motive, descriptive norms, violent behavior, depression, peer models for use, and (unexpectedly) peer sanctions against use and a negative association with family sanctions against use. Regression analyses for solitary cannabis use showed statistically significant positive associations with coping motive, violent behavior, and peer models for use and a negative association with family sanctions against use. CONCLUSIONS: Solitary alcohol and cannabis use are prevalent among AI adolescents and might, in particular, reflect attempts to cope with adversity. Findings could help guide the development of screening and prevention efforts.

The experiences of socially vulnerable groups in England during the COVID-19 pandemic: A rapid health needs assessment.

OBJECTIVES: This rapid health needs assessment was undertaken to urgently identify the needs of socially vulnerable groups arising during the first wave of cases of the COVID-19 pandemic in England. The objective was to develop recommendations for policy makers and stakeholders to mitigate adverse impacts on socially vulnerable groups throughout the COVID-19 response and recovery period. STUDY DESIGN: Rapid health needs assessment. METHODS: The needs assessment employed qualitative methods to systematically collect data about the knowledge and views of key informants through semi-structured interviews and focus groups. Participants were either topic experts providing services to socially vulnerable groups who routinely face barriers to healthcare access or experts by experience. Participants included people experiencing homelessness, sex workers, people from Gypsy, Roma and Traveller communities and people facing challenges due to their immigration status. Data was collected over a week period in April/May 2020 and followed by thematic analysis to examine interview transcripts. RESULTS: Forty-two participants were included in the study, half of whom were experts by experience. Challenges with accessing and following COVID-19 information and government guidance were described as affecting all groups, due to exclusion from digital technology, translated resources, tailored support and adequate housing. Altered delivery of healthcare services, such as the closure of outreach and drop-in services, remote consultations, and online patient registration, were noted by interviewees as worsening existing barriers to accessing healthcare. Being charged for NHS care remained a key fear for migrants. All groups' access to income, education and social support were reported as being impacted by service closures and job losses, putting them at higher risk of destitution. Isolation, loneliness and deteriorating mental health were frequently reported. CONCLUSIONS: This assessment has highlighted the disproportionate impact of the COVID-19 pandemic on socially vulnerable groups and demonstrated a plethora of unmet needs. As the effects of COVID-19 continue, it is imperative that the needs of these groups are urgently and explicitly addressed and prioritised. This is essential to promote engagement with test and trace services, enable isolation adherence, and achieve high vaccine uptake in socially vulnerable populations.