Unfolding Simulations Research Articles

Collision induced unfolding and molecular dynamics simulations of norovirus capsid dimers reveal strain-specific stability profiles.

Collision induced unfolding (CIU) is a method used with ion mobility mass spectrometry to examine protein structures and their stability. Such experiments yield information about higher order protein structures, yet are unable to provide details about the underlying processes. That information can however be provided using molecular dynamics simulations. Here, we investigate the gas-phase unfolding of norovirus capsid dimers from the Norwalk and Kawasaki strains by employing molecular dynamics simulations over a range of temperatures, representing different levels of activation, together with CIU experiments. The dimers have highly similar structures, but their CIU reveals different stability that can be explained by the different dynamics that arises in response to the activation seen in the simulations, including a part of the sequence with previously observed strain-specific dynamics in solution. Our findings show how similar protein variants can be examined using mass spectrometric techniques in conjunction with atomistic molecular dynamics simulations to reveal differences in stability as well as differences in how and where unfolding takes place upon activation.

Configuration Design and Dynamics Simulation Analysis of Deployable Exposure Experiment Platform

Aiming at the problem that the traditional rigid exposure experiment platform takes up too much launch space and consumes high launch cost, a thick panel kirigami method is used to propose a deployable thick panel model for the exposure experiment platform, which realizes the plane of the thick panel. In the unfolding design, the unfolding process simulation of the structure was carried out, the influence of different hinge position drives on the dynamic behavior of the structure unfolding was studied, and the kinematics laws of the structure unfolding process under different driving modes were summarized. The new deployable exposure experiment platform provides new ideas for the development and application of practical engineering in the future, and the dynamic simulation also provides a driving strategy for it.

Exploiting loop-grafting strategy resorting on computer-aided design to improve the thermostability of alpha-amylase from Geobacillus stearothermophilus

Starch-based industries require a robust alpha-amylase capable of withstanding elevated temperatures and long incubation periods. In this study, a loop-grafting strategy based on a computer-aided design was proposed to engineer a thermostable alpha-amylase from Geobacillus stearothermophilus. Molecular dynamics (MD) simulations and trajectory analyses were employed to target the weak spots responsible for thermal inactivation, and three loop regions were identified as weak spots requiring improvement. Subsequently, substitute candidates from the thermophilic orthologous library were selected to refine these weak spots and the most promising mutant was screened using thermal unfolding and MD simulations. Expectedly, an alpha-amylase variant was constructed efficiently and specifically, which can withstand high-temperatures up to 100 °C without any stability-activity trade-off, giving an 8.0-fold longer half-life at 100 °C. Notably, the variant exhibited excellent thermotolerance during corn starch liquefaction at 100 °C, giving a 3.3-fold increased product concentration. Furthermore, the origin of the enhanced thermostability based on the dynamic trajectory of the variant was revealed. Successful attempts to tailor the thermal resistance and catalytic activity of alpha-amylase can further fuel the food industry, particularly high-temperature starch-based industries.

Conformational Flexibility Is a Key Determinant for the Lytic Activity of the Pore-Forming Protein, Cytolysin A.

Several bacterial infections are mediated by pore-forming toxins (PFTs), a subclass of proteins that oligomerize on mammalian cell membranes forming lytic nanopores. Cytolysin A (ClyA), an α-PFT, undergoes a dramatic conformational change restructuring its two membrane-binding motifs (the β-tongue and the N-terminus helix), during pore formation. A complete molecular picture for this key transition and the driving force behind the secondary structure change upon membrane binding remain elusive. Using all-atom molecular dynamics (MD) simulations of the ClyA monomer and string method based free energy computations with path collective variables, we illustrate that an unfolded β-tongue motif is an on-pathway intermediate during the transition to the helix-turn-helix motif of the protomer. An aggregate of 28 μs of all-atom thermal unfolding MD simulations of wild-type ClyA and its single point mutants reveal that the membrane-binding motifs of the ClyA protein display high structural flexibility in water. However, point mutations in these motifs lead to a distinct reduction in the flexibility, especially in the β-tongue, thereby stabilizing the pretransition secondary structure. Resistance to unfolding was further corroborated by MD simulations of the β-tongue mutant motif in the membrane. Combined with the thermal unfolding simulations, we posit that the β-tongue as well as N-terminal mutants that lower the tendency to unfold and disorder the β-tongue are detrimental to pore formation by ClyA and its lytic activity. Erythrocyte turbidity and vesicle leakage assays indeed reveal a loss of activity for the β-tongue mutant, and delayed kinetics for the N-terminus mutants. On the other hand, a point mutation in the extracellular domain that did not abrogate lytic activity displayed similar unfolding characteristics as the wild type. Thus, attenuation of conformational flexibility in membrane-binding motifs correlates with reduced lytic and leakage activity. Combined with secondary structure changes observed in the membrane bound states, our study shows that the tendency to unfold in the β-tongue region is a critical step in the conformational transition and bistability of the ClyA protein and mutants that disrupt this tendency reduced pore formation. Overall, our finding suggests that inherent flexibility in the protein could play a wider and hitherto unrecognized role in membrane-mediated conformational transitions of PFTs and other membrane protein transformations.

Alternative Clinical Learning Experiences for Nursing Education Using Virtual Individual Patients.

Acute care pediatric clinical experiences for undergraduate nursing students can present a challenge given the limited availability of clinical sites, increased restrictions, and variations in direct patient care experiences. Unfolding virtual individual patient pediatric simulations were developed using complex pediatric disorders with multiple physiological, psychosocial, and developmental components. Ten unfolding simulations were implemented to standardize clinical experiences and replace clinical hours. Students were evaluated using the Quint Leveled Clinical Competency Tool, demonstrating overall progressing ability to use clinical reasoning skills. Unfolding virtual individual patients allow for deliberate, coordinated, and consistent exposure to clinical experiences and are a valuable substitution for traditional clinicals.

Benchmarking Adaptive Steered Molecular Dynamics (ASMD) on CHARMM Force Fields.

The potentials of mean force (PMFs) along the end‐to‐end distance of two different helical peptides have been obtained and benchmarked using the adaptive steered molecular dynamics (ASMD) method. The results depend strongly on the choice of force field driving the underlying all‐atom molecular dynamics, and are reported with respect to the three most popular CHARMM force field versions: c22, c27 and c36. Two small peptides, ALA10 and 1PEF, serve as the particular case studies. The comparisons between the versions of the CHARMM force fields provides both a qualitative and quantitative look at their performance in forced unfolding simulations in which peptides undergo large changes in structural conformations. We find that ASMD with the underlying c36 force field provides the most robust results for the selected benchmark peptides.

An Unfolding Tabletop Simulation Training Exercise on Disaster Planning for Nursing Students.

Disaster planning is an essential component for nursing students to learn. Clinical experiences of disasters are typically unavailable for nursing students. Increasing frequency of disaster events around the globe has made disaster planning knowledge and skills a critical component in nursing education and professional practice. An unfolding tabletop disaster planning exercise was created as a simulation training strategy meant to strengthen essential disaster response skills. The exercise involves 5 realistic scenarios related to a mass casualty event, taking students from the disaster site to the hospital-based disaster response. Implementation of a tabletop disaster planning simulation in one nursing program replaced the traditional lecture-based disaster content. An unfolding tabletop disaster planning simulation is a comprehensive, interactive, sustainable, and low-cost teaching strategy that draws on nursing students' fundamental knowledge. Students had the opportunity to practice clinical skills required during a disaster, such as communication, prioritization, teamwork, and delegation.

Family and community nursing: The use of an unfolding simulation via zoom

BackgroundIt is often difficult for undergraduate nursing students to have sufficient opportunity to understand the role of the nurse in providing care for clients in the community . This article describes an innovative approach to teaching family and community nursing concepts via simulation. MethodsA unfolding simulation was developed which allowed nursing students to make four virtual visits with a family via Zoom. ResultsStudents developed skills in interviewing, an improved understanding of the use of technology in health care, increased awareness of the impact of values and beliefs on health and illness, and a greater awareness of the role of the nurse in the community. ConclusionsThe use of simulation provided an innovative, safe, and consistent learning experience for students, allowing them to gain a deeper understanding of family and community nursing.

Addressing 4Ms of Age-Friendly Health Systems for Older Adults in Family Nurse Practitioner Education through Simulation-Based Learning

The population in the United States is aging, and care of older adults is frequently more complex. Addressing older adult competencies in educational programs provides a foundation in which to assess this population, guide the plan of care and aid in decision making. Using the Institute of Healthcare Improvement (IHI) ‘4Ms’ framework, a family nurse practitioner (FNP) program designed a novel approach using an unfolding simulation to integrate the four elements: (a) What Matters Most, (b) Mentation, (c) Medication, and (d) Mobility. The pilot simulation focused on Mentation and What Matters Most in an Advanced Health Assessment course. Students conducted a comprehensive cognitive assessment for an older patient with memory concerns, providing education and resource referrals. Progressive simulations are planned as the patient's cognition declines, building in complexity to include Medications and Mobility while attending to What Matters Most for the patient and their family in each phase. In designing simulations using the 4Ms framework, the pilot simulation provided a teaching strategy and measurement of performance in caring for older adults, and students reported an increase in confidence in communicating and advocating for this population.

Parkinson's Disease Medication Administration During a Care Transition: The Impact of Interprofessional Team Simulation on Student Competency, Comfort, and Knowledge.

This study investigated the impact of an interprofessional mock code on students' comfort and competency related to Parkinson's disease (PD) medication administration during care transitions. Patients with PD are at increased risk for medication errors during hospitalization. Individualization of PD medication creates vulnerability during care transitions. Four interprofessional groups took part in this study: baccalaureate degree senior nursing students (n = 113), master's level nurse anesthesia students (n = 35), doctor of osteopathic medicine fourth-year students (n = 32), and doctor of clinical psychology fourth-year students (n = 22). Groups participated in an unfolding case study simulation involving a mock code with a focus on the omission of time-sensitive PD medication. Pre- and postsimulation test results were compared. Findings indicated an increased understanding among three of the four groups relating to medication timing during care transitions. All groups improved with respect to perceived comfort and competency.

Interprofessional mock code simulation promotes collaboration and competency in Parkinson's medication safety during transition in care

An interprofessional mock code simulation was designed to educate students from four healthcare disciplines on the care of a patient with Parkinson's disease (PD) during a care transition. This interprofessional education initiative facilitated students learning about, from, and with each other. The simulation consisted of an unfolding patient with Parkinson's disease (PD) that involved an incomplete medication reconciliation and an omission of time-sensitive PD medication, resulting in a full code. The simulation explored quality improvement strategies for safe and timely medication administration and reconciliation during a care transition for a patient with PD. The simulation was conducted in the Learning Resource Simulation Center with small groups of students from two separate institutions and four separate schools or college programs rotating throughout the semester. The student participants consisted of the following: Baccalaureate Degree Senior Nursing Students; Master's level Senior Nurse Anesthesia Students; Fourth-Year Doctor of Osteopathic Medicine Students; and Fourth-Year Doctor of Psychology Students. The objectives of the interprofessional mock code simulation were as follows: 1) learners shall understand the roles and responsibilities of members of a healthcare team by participating in an interprofessional simulation of a patient with Parkinson's disease during a mock code scenario; 2) learners shall recognize the harm that occurs from incomplete medication reconciliation specific to Parkinson's disease during care transitions such as disorientation, garbled speech, severely limited breathing capacity and even death; and 3) learners from four different healthcare disciplines will evaluate their comfort and competence specific to working as part of an interprofessional healthcare team during a mock code simulation. The simulation demonstrated an increase in knowledge among all the interprofessional healthcare team members regarding PD medication safety. This PD unfolding case study simulation training also helped students and future professionals feel comfortable and competent while working together during a patient code situation in the acute care setting. This simulation holds great potential for dissemination among all faculty disciplines to improve the quality and safety of the PD population during care transitions. A complete copy of the IPE simulation is available upon request from the primary author.

The Clinical Pause: An Augmented Approach to Simulation Debriefing in Nursing Education.

Debriefing after simulation, a form of reflection-on-action, is widely practiced in nursing education. A lesser used alternative is a faculty-facilitated clinical pause. During natural breaks within an unfolding simulation scenario, faculty incorporated Caputi's thinking skills to facilitate clinical reasoning, reflection-in-action, and timely feedback. The clinical pause enabled well-timed validation of correct thinking, resolution of erroneous thinking, and deliberate practice opportunities to construct contextual meaning. Written student comments, obtained after the simulation, suggest the clinical pause teaching innovation enhanced learning and clinical reasoning. Combining the clinical pause with end-of-simulation debriefing can provide a powerful one-two punch that maximizes clinical judgment.

A Simulated Perioperative Clinical Day for Prelicensure Nursing Students.

The inclusion of perioperative clinical learning experiences in prelicensure nursing education reinforces foundational nursing skills. However, perioperative experiences in clinical settings are not consistently available for student learning. An unfolding perioperative simulation day was created as an alternate to traditional clinical learning. Three simulation-based experiences were designed to include nursing care of the patient during the preoperative, intraoperative, and postoperative phases of the perioperative experience. Implementation of a perioperative simulation as an alternative to traditional clinical learning in one prelicensure program had positive effects on students' ability to achieve learning outcomes, to collaborate, and to improve self-confidence. A simulated perioperative clinical day provides an engaging learning experience, reinforcing foundational clinical skills such as patient safety, infection control, patient mobility, teamwork, and communication. [J Nurs Educ. 2021;60(7):386-390.].

Enhancing the thermostability of a mono- and diacylglycerol lipase from Malassizia globose by stabilizing a flexible loop in the catalytic pocket

A lipase from Malassizia globose, named SMG1, is highly desirable for industrial application due to its substrate specificity towards mono- and diacylglycerol. To improve its thermostability, we constructed a mutant library using an error-prone polymerase chain reaction, which was screened for both initial and residual enzymatic activity. Selected mutants were further studied using purified proteins for their kinetic thermostability at 45 ℃, T50 (the temperature at which the enzyme loses half of its activity), and the optimal reaction temperature. Results showed that the majority of mutations with improved thermostability were on the protein surface. D245N and L270P showed the most significant thermostability enhancement with an approximately 3 ℃ increase in T50 compared to wild-type (WT). In addition, combining these two mutations resulted in an increase of T50 by 5 °C. Also, the optimal reaction temperatures of L270P and this double mutant are 10 ℃ higher than WT. The double mutant showed an approximately 100-fold increase in half-life at 45 ℃ and higher enzymatic activities at 30 ℃ and above compared to WT. High-temperature unfolding molecular dynamics simulation suggested that the double mutant stabilized a flexible loop in the catalytic pocket.

In Silico Therapeutic Peptide Design Against Pathogenic Domain Swapped Human Cystatin C Dimer

In humans, cystatin C mediated amyloid aggregation is quite detrimental. It is deemed to actuate intra-cerebral haemorrhaging, stroke, paralysis and further, turns out to be fatal under exigent circumstances. Especially, the domain swapped dimerization of cystatin C is the pathogenic trigger that propels its amyloidosis. Targeting the protein at this initial pathogenic stage could be effective in arresting cystatin C amyloid formation and its eventual aggregation. In our current analysis, using a logically assertive coherent computational pipeline, we have proffered an efficacious peptide based therapeutic (due to its benefits over small molecules) against the domain swapped cystatin C amyloid like dimer (CCAD) pre-fibril. Wherein, the tripeptide, ‘LVN’ has effectually decreased the average beta sheet content (a distinct pathogenic aspect of amyloids) of CCAD from 49 to 43%. Findings from discrete molecular dynamics simulation through intramolecular hydrogen bond analysis, covariance matrix, free energy landscape and solvent accessible surface area have further substantiated that, upon interaction, LVN has steered CCAD from its distinct pathogenic behaviour. Besides, the thermal unfolding simulation indicated that due to LVN’s confluence with CCAD, the phase transition of the complex to a flexible state from a rigid phase, occurs with a relatively lower temperature and energy, compared to peptide unbound pathogenic CCAD. Hence, the consistent findings from various computational tools anticipate that LVN tripeptide could be a potent promising candidate in mitigating cystatin C amyloid aggregation in humans.

Coarse-Grained Unfolding Simulations of FtsZ and Docking of Therapeutic Compounds

FtsZ is the crucial protein driving bacterial cell division. The protein monomers form filaments that wrap around the cell to form the Z-ring and then constrict. This key role in cell division makes FtsZ an attractive antibiotic target. in particular, new antibiotics are needed to combat MRSA and VRSA infections, two of the most common antibiotic resistant strains. These long FtsZ filaments have not been studied computationally yet, due to the amount of processing power required. We used coarse-grained simulations run on graphics cards to overcome this barrier, and performed unfolding simulations of FtsZ monomers, as well as stretching simulations of a short S. aureus FtsZ filament. Early results show that the species of FtsZ determines the strength of the filament interface, but that monomers unfold very similarly regardless of species. Additionally, we used the SwissDock program to investigate the binding of two identified drug compounds to the several FtsZ proteins from different bacterial species. The results show multiple binding sites, including along the filament and at filament interfaces, which corroborate proposed therapeutic uses.

Molecular Dynamics Study of Insulin Mutants

Human insulin, a small protein hormone consisting of A-chain (21 residues) and B-chain (30 residues) linked by three disulfide bonds, is crucial for controlling the hyperglycemia in type I diabetes. In the present work molecular dynamics simulation (MD) with human insulin and its mutants was used to assess the influence of 10 point mutations (HisA8, ValA10, AspB10, GlnB17, AlaB17, GlnB18, AspB25, ThrB26, GluB27, AspB28), 6 double mutations (GluA13+GluB10, SerA13+GluB27, GluB1+GluB27, SerB2+AspB10, AspB9+GluB27, GluB16+GluB27) and one triple mutation (GluA15+AspA18+AspB3) in the protein sequence on the structure and dynamics of human insulin. A series of thermal unfolding MD simulations with wild type (WT) human insulin and its mutants was performed at 400 K with GROMACS software (version 5.1) using the CHARMM36m force field. The MD results have been analyzed in terms of the parameters characterizing both the global and local protein structure, such as the backbone root mean-square deviation, gyration radius, solvent accessible surface area, the root mean-square fluctuations and the secondary structure content. The MD simulation data showed that depending on time evolution of integral characteristics, the examined mutants can be tentatively divided into three groups: 1) the mutants HisA8, ValA10, AlaB17, AspB25, ThrB26, GluB27, GluA13+GluB10, GluB1+GluB27 and GluB16+GluB27, which exert stabilizing effect on the protein structure in comparison with wild type insulin; 2) the mutants GlnB17, AspB10, SerB2+AspB10 and GluA15+AspA18+AspB3 that did not significantly affect the dynamical properties of human insulin with a minimal stabilizing impact; 3) the mutants AspB28, AspB9+GluB27 and SerA13+GluB27, GlnB18, destabilizing the protein structure. Analysis of the secondary structure content provided evidence for the influence of AspB28, AspB9+GluB27 and SerA13+GluB27, GlnB18 on the insulin unfolding. Our MD results indicate that the replacement of superficial nonpolar residues in the insulin structure by hydrophilic ones gives rise to the increase in protein stability in comparison with the wild type protein.

Structure network-based landscape of rhodopsin misfolding by mutations and algorithmic prediction of small chaperone action

Failure of a protein to achieve its functional structural state and normal cellular location contributes to the etiology and pathology of heritable human conformational diseases. The autosomal dominant form of retinitis pigmentosa (adRP) is an incurable blindness largely linked to mutations of the membrane protein rod opsin. While the mechanisms underlying the noxious effects of the mutated protein are not completely understood, a common feature is the functional protein conformational loss. Here, the wild type and 39 adRP rod opsin mutants were subjected to mechanical unfolding simulations coupled to the graph theory-based protein structure network analysis.A robust computational model was inferred and in vitro validated in its ability to predict endoplasmic reticulum retention of adRP mutants, a feature linked to the mutation-caused misfolding. The structure-based approach could also infer the structural determinants of small chaperone action on misfolded protein mutants with therapeutic implications.The approach is exportable to conformational diseases linked to missense mutations in any membrane protein.

Conserved patterns and interactions in the unfolding transition state across SH3 domain structural homologues.

Proteins with similar structures are generally assumed to arise from similar sequences. However, there are more cases than not where this is not true. The dogma is that sequence determines structure; how, then, can very different sequences fold to the same structure? Here, we employ high temperature unfolding simulations to probe the pathways and specific interactions that direct the folding and unfolding of the SH3 domain. The SH3 metafold in the Dynameomics Database consists of 753 proteins with the same structure, but varied sequences and functions. To investigate the relationship between sequence and structure, we selected 17 targets from the SH3 metafold with high sequence variability. Six unfolding simulations were performed for each target, transition states were identified, revealing two general folding/unfolding pathways at the transition state. Transition states were also expressed as mathematical graphs of connected chemical nodes, and it was found that three positions within the structure, independent of sequence, were consistently more connected within the graph than any other nearby positions in the sequence. These positions represent a hub connecting different portions of the structure. Multiple sequence alignment and covariation analyses also revealed certain positions that were more conserved due to packing constraints and stabilizing long-range contacts. This study demonstrates that members of the SH3 domain with different sequences can unfold through two main pathways, but certain characteristics are conserved regardless of the sequence or unfolding pathway. While sequence determines structure, we show that disparate sequences can provide similar interactions that influence folding and lead to similar structures.

Validation of DBFOLD: An efficient algorithm for computing folding pathways of complex proteins.

Atomistic simulations can provide valuable, experimentally-verifiable insights into protein folding mechanisms, but existing ab initio simulation methods are restricted to only the smallest proteins due to severe computational speed limits. The folding of larger proteins has been studied using native-centric potential functions, but such models omit the potentially crucial role of non-native interactions. Here, we present an algorithm, entitled DBFOLD, which can predict folding pathways for a wide range of proteins while accounting for the effects of non-native contacts. In addition, DBFOLD can predict the relative rates of different transitions within a protein's folding pathway. To accomplish this, rather than directly simulating folding, our method combines equilibrium Monte-Carlo simulations, which deploy enhanced sampling, with unfolding simulations at high temperatures. We show that under certain conditions, trajectories from these two types of simulations can be jointly analyzed to compute unknown folding rates from detailed balance. This requires inferring free energies from the equilibrium simulations, and extrapolating transition rates from the unfolding simulations to lower, physiologically-reasonable temperatures at which the native state is marginally stable. As a proof of principle, we show that our method can accurately predict folding pathways and Monte-Carlo rates for the well-characterized Streptococcal protein G. We then show that our method significantly reduces the amount of computation time required to compute the folding pathways of large, misfolding-prone proteins that lie beyond the reach of existing direct simulation. Our algorithm, which is available online, can generate detailed atomistic models of protein folding mechanisms while shedding light on the role of non-native intermediates which may crucially affect organismal fitness and are frequently implicated in disease.