Accelerated Molecular Dynamics for Peptide Folding: Benchmarking Different Combinations of Force Fields and Explicit Solvent Models.

Accelerated molecular dynamics (aMD) protocols were assessed on predicting the secondary structure of eight peptides, of which two are helical, three are ß-hairpins, and three are disordered. Protocols consisted of combinations of three force fields (ff99SB, ff14SB, ff19SB) and two explicit solvation models (TIP3P and OPC), and were evaluated in two independent aMD simulations, one starting from an extended conformation, the other starting from a misfolded conformation. The results of these analyses indicate that all three combinations performed well on helical peptides. As for ß-hairpins, ff19SB performed well with both solvation methods, with a slight preference for the TIP3P solvation model, even though performance was dependent on both peptide sequence and initial conformation. The ff19SB/OPC combination had the best performance on intrinsically disordered peptides. In general, ff14SB/TIP3P suffered the strongest helical bias.

Caught between Scylla and Charybdis: How Economic Stressors and Occupational Risk Factors Influence Workers' Occupational Health Reactions to COVID-19.

Workers and their families bear much of the economic burden of COVID-19. Even though they have declined somewhat, unemployment rates are considerably higher than before the start of the pandemic. Many workers also face uncertainty about their future employment prospects and increasing financial strain. At the same time, the workplace is a common source of transmission of COVID-19 and many jobs previously seen as relatively safe are now viewed as potentially hazardous. Thus, many workers face dual threats of economic stress and COVID-19 exposure. This paper develops a model of workers' responses to these dual threats, including risk perception and resource depletion as mediating factors that influence the relationship of economic stress and occupational risk factors with COVID-19 compliance-related attitudes, safe behavior at work, and physical and mental health outcomes. The paper also describes contextual moderators of these relationships at the individual, unit, and regional level. Directions for future research are discussed.

Using homology modeling to interrogate binding affinity in neutralization of ricin toxin by a family of single domain antibodies.

In this report we investigated, within a group of closely related single domain camelid antibodies (VH Hs), the relationship between binding affinity and neutralizing activity as it pertains to ricin, a fast-acting toxin and biothreat agent. The V1C7-like VH Hs (V1C7, V2B9, V2E8, and V5C1) are similar in amino acid sequence, but differ in their binding affinities and toxin-neutralizing activities. Using the X-ray crystal structure of V1C7 in complex with ricin's enzymatic subunit (RTA) as a template, Rosetta-based homology modeling coupled with energetic decomposition led us to predict that a single pairwise interaction between Arg29 on V5C1 and Glu67 on RTA was responsible for the difference in ricin toxin binding affinity between V1C7, a weak neutralizer, and V5C1, a moderate neutralizer. This prediction was borne out experimentally: substitution of Arg for Gly at position 29 enhanced V1C7's binding affinity for ricin, whereas the reverse (ie, Gly for Arg at position 29) diminished V5C1's binding affinity by >10 fold. As expected, the V5C1R29G mutant was largely devoid of toxin-neutralizing activity (TNA). However, the TNA of the V1C7G29R mutant was not correspondingly improved, indicating that in the V1C7 family binding affinity alone does not account for differences in antibody function. V1C7 and V5C1, as well as their respective point mutants, recognized indistinguishable epitopes on RTA, at least at the level of sensitivity afforded by hydrogen-deuterium mass spectrometry. The results of this study have implications for engineering therapeutic antibodies because they demonstrate that even subtle differences in epitope specificity can account for important differences in antibody function.

"Solvent hydrogen-bond occlusion": A new model of polar desolvation for biomolecular energetics.

Water engages in two important types of interactions near biomolecules: it forms ordered "cages" around exposed hydrophobic regions, and it participates in hydrogen bonds with surface polar groups. Both types of interaction are critical to biomolecular structure and function, but explicitly including an appropriate number of solvent molecules makes many applications computationally intractable. A number of implicit solvent models have been developed to address this problem, many of which treat these two solvation effects separately. Here, we describe a new model to capture polar solvation effects, called SHO ("solvent hydrogen-bond occlusion"); our model aims to directly evaluate the energetic penalty associated with displacing discrete first-shell water molecules near each solute polar group. We have incorporated SHO into the Rosetta energy function, and find that scoring protein structures with SHO provides superior performance in loop modeling, virtual screening, and protein structure prediction benchmarks. These improvements stem from the fact that SHO accurately identifies and penalizes polar groups that do not participate in hydrogen bonds, either with solvent or with other solute atoms ("unsatisfied" polar groups). We expect that in future, SHO will enable higher-resolution predictions for a variety of molecular modeling applications. © 2017 Wiley Periodicals, Inc.

Investigating the Impact of Occupational Technostress and Psychological Restorativeness of Natural Spaces on Work Engagement and Work-Life Balance Satisfaction.

The COVID-19 pandemic has necessitated lockdowns and mandatory working from home, as well as restrictions on travel and recreation. As a result, many people have had to use their home as an office and have increased their use of Information Communications Technology (ICT) for work purposes. Nature and accessing natural spaces are known to be beneficial for human health and wellbeing, as a result of their restorative properties. Access to local outdoor spaces was permitted under restrictions, and use of such spaces increased during lockdown. This survey study investigated whether the perceived restorativeness of natural spaces and exposure to technostress predicted the levels of work engagement and work-life balance satisfaction (WLBS) during the period of COVID-19 restrictions adopted in 2020. Analyses conducted on a sample of 109 people employed in the UK revealed that technostress negatively impacted WLBS, whilst perceived psychological restorativeness positively predicted work engagement. The study highlights the benefits of having access to natural spaces to improve employees' work engagement and potentially negate the negative effects of technostress, particularly during a period of intensive working from home. The results contribute to the understanding of the linkages between restorativeness and work engagement, paving the way for synergies across these research fields.

COVID-19 moral disengagement and prevention behaviors: The impact of perceived workplace COVID-19 safety climate and employee job insecurity.

In response to the COVID-19 pandemic, the U.S. Centers for Disease Control and Prevention developed recommendations for individual COVID-19 prevention behaviors, as well as guidance for the safe reopening of businesses. Drawing from previous research on occupational safety, business ethics, and economic stressors, we tested the hypothesis that more positive perceptions of the workplace COVID-19 safety climate would be associated with lower employee COVID-19 related moral disengagement. In turn, we predicted that higher COVID-19 moral disengagement would be associated with lower enactment of preventive behaviors both at work and in nonwork settings (i.e., a spillover effect). Further, we investigated whether employee job insecurity would impact organizational socialization processes, such that the relationship between the perceived COVID-19 safety climate and moral disengagement would be weaker at higher levels of job insecurity. By analyzing a three-wave lagged dataset of U.S. employees working on-site during the pandemic using a Bayesian multilevel framework, we found empirical support for the hypothesized moderated mediation model. We discuss the relevance of these findings (i.e., the spillover effect and the role of job insecurity) in light of the extant safety climate literature and outline how our findings have several implications for the scope and conceptualization of safety climate in light of the surge of new working arrangements, infectious diseases, and continuing employment instability.

A Latent Profile Analysis of Precarity and Its Associated Outcomes: The Haves and the Have-Nots.

A continuing debate on the nature of precarity surrounds its defining characteristics and identification of what constitutes precarity. While early sociological work argued that people either experience precarity or they do not (i.e., the haves and the have-nots), subsequent researchers have gone to great lengths to argue for a more nuanced approach with multiple distinct classes of precarity. Using cross-lagged data from n = 315 U.S. employees collected during the COVID-19 pandemic, we took a person-centered approach to address this central question and uncover latent subpopulations of precarity. Specifically, we conducted a latent profile analysis of precarity using various objective and subjective indicators including perceptions of job insecurity, financial insecurity, prior unemployment experiences, per capita household income, skill-based underemployment, and time-based underemployment. While we anticipated different profiles based on income- vs. employment-based sources of precarity, the best-fitting solution surprisingly comported with Standing's proposed two-class model. Moreover, membership in the precarious profile was associated with consistently more adverse subsequent outcomes across work, health, and life domains adding to the validity of the obtained two-profile structure. We discuss these results in light of potential loss spirals that can co-occur with the experience of precarity.

Technology Advancements and Employees' Qualitative Job Insecurity in the Republic of Korea: Does Training Help? Employer-Provided vs. Self-Paid Training.

While technological advancements have proliferated in our daily lives, they also pose threats to the job security of employees. Despite these growing concerns about technology-related job insecurity, little research has been carried out on the antecedents and outcomes of tech-related job insecurity. Using a cross-sectional, nationally representative survey sample of 28,989 Korean workers drawn from the Korean Working Conditions Survey, we examined the impacts of technology advancements on employee perceptions of technology-related qualitative job insecurity (i.e., perceived technology-related threat to the continued existence of valued job features) and subsequent effects on employees' work (i.e., work engagement, job satisfaction), health (i.e., sleep), and life (i.e., work-to-family conflict) outcomes. Furthermore, we investigated the extent to which employer-provided (versus self-funded) training buffers the adverse impacts of technology advancements and associated job insecurity. The path analysis results showed more technology changes were associated with higher job insecurity, which subsequently related to adverse outcomes. While employer-provided training helped workers to reduce the negative impacts of tech changes on job insecurity, workers who paid for their training reported more adverse outcomes in face of job insecurity. We discuss these results in light of the job demands-resources theory and practical implications to buffer the adverse impacts of technology advancements.

Economic Stressors, COVID-19 Attitudes, Worry, and Behaviors among U.S. Working Adults: A Mixture Analysis.

Since the unfolding of the novel coronavirus global pandemic, public health research has increasingly suggested that certain groups of individuals may be more exposed to the virus. The aim of this contribution was to investigate whether workers grouped into several latent classes, based on two perceived economic stressors, would report different levels of enactment of the Centers for Disease Control (CDC) recommended behaviors to prevent the spread of such virus. We also tested propositions regarding the potential differential predictors of compliance behavior, differentiating between cognitive (i.e., attitudes toward the CDC guidelines) and affective (i.e., COVID-specific worry) predictors. Using a longitudinal dataset of 419 U.S. workers, we did not find significant differences among the levels of CDC guidelines enactment across three latent classes, representing a range of economic vulnerability. We found that cognitive attitudes were a significantly stronger predictor of compliance with CDC guidelines for workers in the most economically secure class, whereas worry was a significantly stronger predictor of compliance for the most vulnerable counterpart. We discuss these findings in light of the Conservation of Resources theory and other health behavior theories, being mindful of the need to further understand the differential impact of this health and economic crisis on employees facing economic stressors.

Coping with job insecurity: Employees with grit create I-deals.

Although job insecurity has been shown to predict numerous adverse outcomes, more is yet to be known about the mechanisms that explain when and why these effects will occur. Using social exchange as our theoretical foundation and three-wave lagged survey data collected from N = 300 employees within the United States, the current study found support for the contention that individuals with greater job insecurity pursue fewer idiosyncratic deals (I-Deals) with their employers. Fewer I-Deals in turn were associated with lower affective commitment, and higher turnover intentions, perceived psychological contract breach, and psychological contract violation. However, these indirect effects were conditional upon employee levels of grit (specifically, perseverance of effort), such that higher grit attenuated the negative relationship between job insecurity and the pursuit of I-Deals. Given that employees often have little control over the source of their experienced job insecurity (e.g., impending layoffs, a poor economy, announced merger or acquisition), these findings hold promise in potentially alleviating the well-documented negative outcomes of job insecurity through interventions designed to increase employee levels of grit and facilitate the creation of I-Deals. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Work and Non-Work Sickness Presenteeism: The Role of Workplace COVID-19 Climate.

OBJECTIVE: To test the role of workplace coronavirus disease (COVID-19) climate in shaping employee attitudes toward the CDC prevention guidelines and subsequent levels of work and non-work sickness presenteeism. METHODS: Three waves of anonymous survey data were collected in October and December 2020 and February 2021. Participants were 304 employed adults in the U.S., of whom half were working onsite. RESULTS: Time 1 workplace COVID-19 climate was positively associated with Time 2 employee attitudes toward the CDC prevention guidelines, which in turn predicted Time 3 levels of non-work and work sickness presenteeism. CONCLUSIONS: The workplace can shape employee attitudes toward the CDC COVID-19 prevention guidelines and their work and non-work sickness presenteeism, thus highlighting the important role companies have in reducing community spread of the novel coronavirus in work and non-work settings.

Economic stressors and the enactment of CDC-recommended COVID-19 prevention behaviors: The impact of state-level context.

In order to combat the spread of the novel coronavirus, the Centers for Disease Control and Prevention (CDC) has developed a list of recommended preventative health behaviors for Americans to enact, including social distancing, frequent handwashing, and limiting nonessential trips from home. Drawing upon scarcity theory, the purpose of this study was to examine whether the economic stressors of perceived job insecurity and perceived financial insecurity are related to employee self-reports of enacting such behaviors. Moreover, we tested propositions regarding the impact of two state-level contextual variables that may moderate those relationships: the generosity of unemployment insurance benefits and extensiveness of statewide COVID-19-related restrictions. Using a multilevel data set of N = 745 currently employed U.S. workers nested within 43 states, we found that both job insecurity and financial insecurity were negatively related to the enactment of the CDC-recommended guidelines. However, the state-level variables acted as cross-level moderators, such that the negative relationship between job insecurity and compliance with the CDC guidelines was attenuated within states that have a more robust unemployment system. However, working in a state with more extensive COVID-19 restrictions seemed to primarily benefit more financially secure workers. When statewide policies were more restrictive, employees reporting more financial security were more likely to enact the CDC-recommended guidelines compared to their financially insecure counterparts. We discuss these findings in light of the continuing need to develop policies to address the public health crisis while also protecting employees facing economic stressors. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Computational Design of an Allosteric Antibody Switch by Deletion and Rescue of a Complex Structural Constellation.

Therapeutic monoclonal antibodies have transformed medicine, especially with regards to treating cancers and disorders of the immune system. More than 50 antibody-derived drugs have already reached the clinic, the majority of which target cytokines or cell-surface receptors. Unfortunately, many of these targets have pleiotropic functions: they serve multiple different roles, and often not all of these roles are disease-related. This can be problematic because antibodies act throughout the body, and systemic neutralization of such targets can lead to safety concerns. To address this, we have developed a strategy whereby an antibody's ability to recognize its antigen is modulated by a second layer of control, relying on addition of an exogenous small molecule. In previous studies, we began to explore this idea by introducing a deactivating tryptophan-to-glycine mutation in the domain-domain interface of a single-chain variable fragment (scFv), and then restoring activity by adding back indole to fit the designed cavity. Here, we now describe a novel computational strategy for enumerating larger cavities that can be formed by simultaneously introducing multiple adjacent large-to-small mutations; we then carry out a complementary virtual screen to identify druglike compounds to match each candidate cavity. We first demonstrate the utility of this strategy in a fluorescein-binding single-chain variable fragment (scFv) and experimentally characterize a triple mutant with reduced antigen-binding (Rip-3) that can be rescued using a complementary ligand (Stitch-3). Because our design is built upon conserved residues in the antibody framework, we then show that the same mutation/ligand pair can also be used to modulate antigen-binding in an scFv build from a completely unrelated framework. This set of residues is present in many therapeutic antibodies as well, suggesting that this mutation/ligand pair may serve as a general starting point for introducing ligand-dependence into many clinically relevant antibodies.

Enhancements to the Rosetta Energy Function Enable Improved Identification of Small Molecules that Inhibit Protein-Protein Interactions.

Protein-protein interactions are among today's most exciting and promising targets for therapeutic intervention. To date, identifying small-molecules that selectively disrupt these interactions has proven particularly challenging for virtual screening tools, since these have typically been optimized to perform well on more "traditional" drug discovery targets. Here, we test the performance of the Rosetta energy function for identifying compounds that inhibit protein interactions, when these active compounds have been hidden amongst pools of "decoys." Through this virtual screening benchmark, we gauge the effect of two recent enhancements to the functional form of the Rosetta energy function: the new "Talaris" update and the "pwSHO" solvation model. Finally, we conclude by developing and validating a new weight set that maximizes Rosetta's ability to pick out the active compounds in this test set. Looking collectively over the course of these enhancements, we find a marked improvement in Rosetta's ability to identify small-molecule inhibitors of protein-protein interactions.

Computational protein design and large-scale assessment by I-TASSER structure assembly simulations.

Protein design aims at designing new protein molecules of desired structure and functionality. One of the major obstacles to large-scale protein design are the extensive time and manpower requirements for experimental validation of designed sequences. Recent advances in protein structure prediction have provided potentials for an automated assessment of the designed sequences via folding simulations. We present a new protocol for protein design and validation. The sequence space is initially searched by Monte Carlo sampling guided by a public atomic potential, with candidate sequences selected by the clustering of sequence decoys. The designed sequences are then assessed by I-TASSER folding simulations, which generate full-length atomic structural models by the iterative assembly of threading fragments. The protocol is tested on 52 nonhomologous single-domain proteins, with an average sequence identity of 24% between the designed sequences and the native sequences. Despite this low sequence identity, three-dimensional models predicted for the first designed sequence have an RMSD of <2 Å to the target structure in 62% of cases. This percentage increases to 77% if we consider the three-dimensional models from the top 10 designed sequences. Such a striking consistency between the target structure and the structural prediction from nonhomologous sequences, despite the fact that the design and folding algorithms adopt completely different force fields, indicates that the design algorithm captures the features essential to the global fold of the target. On average, the designed sequences have a free energy that is 0.39 kcal/(mol residue) lower than in the native sequences, potentially affording a greater stability to synthesized target folds.

Prediction of inhibitory activity of epidermal growth factor receptor inhibitors using grid search-projection pursuit regression method.

The epidermal growth factor receptor (EGFR) protein tyrosine kinase (PTK) is an important protein target for anti-tumor drug discovery. To identify potential EGFR inhibitors, we conducted a quantitative structure-activity relationship (QSAR) study on the inhibitory activity of a series of quinazoline derivatives against EGFR tyrosine kinase. Two 2D-QSAR models were developed based on the best multi-linear regression (BMLR) and grid-search assisted projection pursuit regression (GS-PPR) methods. The results demonstrate that the inhibitory activity of quinazoline derivatives is strongly correlated with their polarizability, activation energy, mass distribution, connectivity, and branching information. Although the present investigation focused on EGFR, the approach provides a general avenue in the structure-based drug development of different protein receptor inhibitors.