Free Energy Profile and Mechanism of Self-Assembly of Peptide Amphiphiles Based on a Collective Assembly Coordinate

By combining targeted molecular dynamics (TMD) simulations, umbrella sampling, and the weighted histogram analysis method (WHAM), we have calculated the potential of mean force (PMF) for the transition between the bound and free states of 90 peptide amphiphiles (PAs) in aqueous solution, with the bound state corresponding to a cylindrical micelle fiber. We specifically consider a collective reaction coordinate, the radius of gyration of the PAs, to describe assembly in this work. It is found that the free energy, enthalpy, and entropy differences between the free and bound states are −126 kcal/mol, −185 kcal/mol, and −190 cal/(mol K), respectively, for the self-assembly process. This indicates that the driving force to form the micelle structure is enthalpic. The enthalpic driving forces originate from several factors, including the conformational energy of PAs and the electrostatic and van der Waals interaction energy between solvent molecules and between solvent and PAs. Among these interactions, the solvent electrostatic interaction is the dominating one, contributing 54% of the total driving force. The PMF profile can be recognized as involving two stages of assembly: (1) PAs initially approach each other in mostly random configurations and loosely aggregate, resulting in significant desolvation and initiation of head–tail conformational reorganization; (2) PAs undergo a conformational disorder-to-order transition, including forming secondary structures that include more β-sheets and fewer random coils, along with tail–head core–shell alignment and condensation that leads to total exclusion of water from the core. The PMF decreases slowly in the first stage, but rapidly in the second. This study demonstrates a hierarchy of assembly steps in which PA structural changes, solvation, and redistribution of solvent molecules play significant roles in the PA self-assembly process

Free-Energy Landscape for Peptide Amphiphile Self-Assembly: Stepwise versus Continuous Assembly Mechanisms

The mechanism of self-assembly of 140 peptide amphiphiles (PAs) to give nanofiber structures was investigated using a coarse-grained method to quantitatively determine whether the assembly process involves discrete intermediates or is a continuous process. Two novel concepts are introduced for this analysis, a cluster analysis of the time dependence of PA assembly and use of the fraction of native contacts as reaction coordinates for characterizing thermodynamic functions during assembly. The cluster analysis of the assembly kinetics demonstrates that a pillar-like intermediate state is formed before the final cylindrical semifiber structure. We also find that head group assembly occurs on a much shorter time scale than tail group assembly. A 2D free-energy landscape with respect to the fraction of native contacts was calculated, and the pillar-like intermediate structure was also found, with free energies about 1.2 kcal/mol higher than the final state. Although this intermediate state exists for only hundreds of nanoseconds, the PA self-assembly process can be recognized as involving two steps, (a) transition from the disordered state to the noncylindrical pillar-like intermediate and (b) pillar-like to final semifiber transition. These results are important to the further design of PAs as functional nanostructures

The effect of perceived global stress and altruism on prosocial driving behavior, yielding behavior, and yielding attitude

Traffic accidents are mainly caused by driver-to-pedestrian collisions or driver-to-driver collisions. Prosocial driving behavior indicates that drivers exhibit altruistic behavior toward other drivers on roads. Yielding behavior demonstrates that drivers grant the right of passage to pedestrians at unsignalized crossings, while yielding attitude presents the subjective emotional and cognitive inclination to yield to pedestrians at unsignalized crossings. This study aims to explore the effect of altruism and drivers’ perceived stress on prosocial driving behavior, yielding behavior, and yielding attitude. In addition, we endeavor to explore the effect of stress on prosocial driving behavior exhibiting an inverted “U-type” curve as Yerkes-Dodson’s law suggests and test the moderating role of perceived stress on altruism and prosocial driving behavior/yielding behavior/yielding attitude. Using a survey method, we asked 454 participants to complete an altruism scale from the IPIT measuring altruism, a Perceived Stress Scale-10 measuring drivers’ perceived stress, a prosocial driving scale from the PADI measuring prosocial driving behavior, and items on yielding behavior and yielding attitude. Then, a correlational matrix, a hierarchical multiple nonparametric regression analysis, and a moderating analysis of perceived stress were employed in sequence to reach our objective. The hierarchical multiple nonparametric regression analysis showed that altruism positively predicts yielding attitude (F = 41.56, p z = 8.46, p F = 110.66, p F = 7.63, p F = 0.51, p > 0.05) or yielding behavior (z = 0.12, p > 0.05), which exhibits an inverted “U-type” curve. Moderating analyses showed that stress only moderates the relationship between altruism and yielding attitude (B = −0.24, t = −2.62, p  Altruism is positively related to prosocial driving behavior, yielding behavior, and yielding attitude. Stress influences prosocial driving behavior only and exhibits an inverted “U-type” curve. Stress does not directly influence the yielding behavior. Instead, stress moderates the relationship between altruism and yielding attitude only and may further increase the possibility of yielding behavior.</p

Kinetic Study of Ozone Photocatalytic Decomposition Using a Thin Film of TiO₂ Coated on a Glass Plate and the CFD Modeling Approach

The kinetics of ozone photocatalytic decomposition in a flow-through reactor using a thin film of TiO₂ coated on a glass plate is investigated. The Langmuir–Hinshelwood kinetic model provides a good description of the ozone decomposition. The effect of light intensity on reaction rate is also studied, showing a transition in the kinetic order with respect to light intensity occurred from 0.75 to 1.0 mW·cm^–2 under the experimental conditions. Fluid dynamics and surface photocatalytic reaction modeling by the computational fluid dynamic (CFD) approach is then proposed. The parameters determined in the kinetic experiment are used to calculate the ozone concentration distribution in the flow-through reactor under a given radiation field. In terms of conversion yield, the model predictions agree closely with the experimental results within the range in which the results are examined. This study presents a simple example of the photocatalytic reaction process modeling. Knowledge of the intrinsic kinetics allows the universal application of this CFD approach to the optimization and design of photocatalytic reactors

Image4_SVhawkeye: an ultra-fast software for user-friendly visualization of targeted structural fragments from BAM files.JPEG

SVhawkeye is a novel visualization software created to rapidly extract essential structural information from third-generation sequencing data, such as data generated by PacBio or Oxford Nanopore Technologies. Its primary focus is on visualizing various structural variations commonly encountered in whole-genome sequencing (WGS) experiments, including deletions, insertions, duplications, inversions, and translocations. Additionally, SVhawkeye has the capability to display isoform structures obtained from iso-seq data and provides interval depth visualization for deducing local copy number variation (CNV). One noteworthy feature of SVhawkeye is its capacity to genotype structural variations, a critical function that enhances the accuracy of structural variant genotyping. SVhawkeye is an open-source software developed using Python and R languages, and it is freely accessible on GitHub (https://github.com/yywan0913/SVhawkeye).</p

Image2_SVhawkeye: an ultra-fast software for user-friendly visualization of targeted structural fragments from BAM files.JPEG

SVhawkeye is a novel visualization software created to rapidly extract essential structural information from third-generation sequencing data, such as data generated by PacBio or Oxford Nanopore Technologies. Its primary focus is on visualizing various structural variations commonly encountered in whole-genome sequencing (WGS) experiments, including deletions, insertions, duplications, inversions, and translocations. Additionally, SVhawkeye has the capability to display isoform structures obtained from iso-seq data and provides interval depth visualization for deducing local copy number variation (CNV). One noteworthy feature of SVhawkeye is its capacity to genotype structural variations, a critical function that enhances the accuracy of structural variant genotyping. SVhawkeye is an open-source software developed using Python and R languages, and it is freely accessible on GitHub (https://github.com/yywan0913/SVhawkeye).</p

Molecular Dynamics Simulations and Electronic Excited State Properties of a Self-Assembled Peptide Amphiphile Nanofiber with Metalloporphyrin Arrays

We have employed molecular dynamics simulations and quantum chemistry methods to study the structures and electronic absorption properties of a novel type of photonic nanowire gel constructed by the self-assembly of peptide amphiphiles (PAs) and the chromophore-(PPIX)Zn molecules. Using molecular dynamics simulations, structures of the self-assembled fiber were determined with atomistic detail, including the distribution of chromophores along the nanofiber and the relative distances and orientations of pairs of chromophores. In addition, quantum chemistry calculations were used to determine the electronic structure and absorption properties of the chromophores in the fiber, so as to assess the capabilities of the nanofiber for photonics applications. The calculations show that the PA nanofiber provides an effective scaffold for the chromophores in which the chromophores form several clusters in which nearest neighbor chromophores are separated by less than 20 Å. The calculations also indicate that the chromophores can be in both the hydrophilic shell and hydrophobic core portions of the fiber. There are only small spectral shifts to the B-band of the porphyrins arising from the inhomogeneous microelectronic environment provided by the fiber. However, there are much stronger electronic interactions between nearby pairs of chromophores, leading to a more significant red shift of the B-band that is similar to what is found in the experiments and to significant excitonic coupling that is seen in circular dichroism spectra. This electronic interaction between chromophores associated with the PA nanofiber structure is crucial to future applications of these fibers for light-harvesting applications

Image1_SVhawkeye: an ultra-fast software for user-friendly visualization of targeted structural fragments from BAM files.JPEG

SVhawkeye is a novel visualization software created to rapidly extract essential structural information from third-generation sequencing data, such as data generated by PacBio or Oxford Nanopore Technologies. Its primary focus is on visualizing various structural variations commonly encountered in whole-genome sequencing (WGS) experiments, including deletions, insertions, duplications, inversions, and translocations. Additionally, SVhawkeye has the capability to display isoform structures obtained from iso-seq data and provides interval depth visualization for deducing local copy number variation (CNV). One noteworthy feature of SVhawkeye is its capacity to genotype structural variations, a critical function that enhances the accuracy of structural variant genotyping. SVhawkeye is an open-source software developed using Python and R languages, and it is freely accessible on GitHub (https://github.com/yywan0913/SVhawkeye).</p

Image3_SVhawkeye: an ultra-fast software for user-friendly visualization of targeted structural fragments from BAM files.JPEG

SVhawkeye is a novel visualization software created to rapidly extract essential structural information from third-generation sequencing data, such as data generated by PacBio or Oxford Nanopore Technologies. Its primary focus is on visualizing various structural variations commonly encountered in whole-genome sequencing (WGS) experiments, including deletions, insertions, duplications, inversions, and translocations. Additionally, SVhawkeye has the capability to display isoform structures obtained from iso-seq data and provides interval depth visualization for deducing local copy number variation (CNV). One noteworthy feature of SVhawkeye is its capacity to genotype structural variations, a critical function that enhances the accuracy of structural variant genotyping. SVhawkeye is an open-source software developed using Python and R languages, and it is freely accessible on GitHub (https://github.com/yywan0913/SVhawkeye).</p