Radius Of Gyration Research Articles

The effect of temperature on asphaltene transformation and agglomeration in oil pressure tank systems under injection of carbon dioxide in a porous structure: A molecular dynamics study

Asphaltene is a complex blend of high-molecular-weight hydrocarbons present in crude oil. It is a solid, insoluble component that precipitates from oil under certain circumstances, such as temperature (Temp), pressure, or composition changes. Despite its problems, asphaltene has potential uses in a variety of sectors, including the manufacture of carbon materials, asphalt, and pharmaceuticals. Specifically, this study investigated the changes in the asphaltene compaction process under carbon dioxide (CO2) injection by examining changes in initial temperature and analyzing influencing parameters such as radial distribution function, radius of gyration, and density changes. In this study, thermodynamic equilibrium in simulated asphaltene samples was achieved within 10 ns, with temperature and kinetic energy stabilizing at 310 K and 0.86 kcal/mol, respectively. The subsequent analysis focused on the agglomeration of asphaltene molecules under varying temperatures. The agglomeration process was completed within 10 ns, with the gyration radius stabilizing at 30.5 Å, providing insights into asphaltene behavior and its impact on petroleum fluid properties. At 300 K, asphaltene agglomeration increased viscosity to 23.3 Pa s by reducing molecular movement, illustrating the complex relationship between aggregation and fluid viscosity. The study also observed that asphaltene agglomeration increased viscosity to approximately 23.3 Pa s at 300 K due to reduced molecular movement. As the temperature was raised from 300 to 400 K, the maximum density profile decreased from 0.0225 to 0.0207 atom/Å3, while the gyration radius of asphaltene molecules decreased from 30.54 to 28.51 Å and viscosity increased from 23.3 to 23.92 Pa s. These results highlight the intricate effects of temperature on asphaltene dynamics and petroleum fluid properties.

Chromatographic analysis of branched and debranched starch structure: Variability of their results

Starch structure determination is crucial for understanding its properties and applications. However, method-dependent variations in size determination can lead to ambiguous interpretations. This study investigates the ambiguities in starch structure determination by evaluating the variation in size of four commercial branched starches as determined by average molar mass, gyration radius, hydrodynamic radius, and chain-length distribution. The starches were analyzed using high-performance size-exclusion chromatography (HPSEC) coupled with multi-angle laser light scattering (MALLS) and refractive index detector (RI), and after debranching by HPSEC-RI and high-performance anion-exchange chromatography (HPAEC) with pulsed amperometric detector (PAD). MALLS-derived MW values for amylose and amylopectin were higher than those obtained using the hydrodynamic volume method. The molecular weight of amylopectin chains, determined by the degree of polymerization (DP), ranged between 2.1 and 2.9 × 103 g/mol for short chains, and between 4.1 × 103 and 1.1 × 104 g/mol for long chains. Differences in amylopectin chain content were observed between HPSEC-RI and HPAEC-PAD, highlighting the complementary nature of these techniques. The study underscores the need for standardizing chromatography-based methodologies in starch research, particularly with the advent of new technologies.

Asymmetric fluctuation of overlapping dinucleosome studied by cryo-electron microscopy and small-angle X-ray scattering

Abstract Nucleosome remodelers modify the local structure of chromatin to release the region from nucleosome-mediated transcriptional suppression. Overlapping dinucleosomes (OLDNs) are nucleoprotein complexes formed around transcription start sites as a result of remodeling, and they consist of two nucleosome moieties: a histone octamer wrapped by DNA (octasome) and a histone hexamer wrapped by DNA (hexasome). While OLDN formation alters chromatin accessibility to proteins, the structural mechanism behind this process is poorly understood. Thus, this study investigated the characteristics of structural fluctuations in OLDNs. First, multiple structures of the OLDN were visualized through cryo-electron microscopy (cryo-EM), providing an overview of the tilting motion of the hexasome relative to the octasome at the near-atomistic resolution. Second, small-angle X-ray scattering (SAXS) revealed the presence of OLDN conformations with a larger radius of gyration than cryo-EM structures. A more complete description of OLDN fluctuation was proposed by SAXS-based ensemble modeling, which included possible transient structures. The ensemble model supported the tilting motion of the OLDN outlined by the cryo-EM models, further suggesting the presence of more diverse conformations. The amplitude of the relative tilting motion of the hexasome was larger, and the nanoscale fluctuation in distance between the octasome and hexasome was also proposed. The cryo-EM models were found to be mapped in the energetically stable region of the conformational distribution of the ensemble. Exhaustive complex modeling using all conformations that appeared in the structural ensemble suggested that conformational and motional asymmetries of the OLDN result in asymmetries in the accessibility of OLDN-binding proteins.

ScatterX： A software for fast processing of high-throughput small-angle scattering data

Abstract Scattering experiments become increasingly popular in modern scientific research, including the areas of materials, biology, chemistry, physics, etc. Besides, various types of scattering facilities have been developed recently, such as lab-based X-ray scattering equipment, national synchrotron facilities and large neutron facilities. These above-mentioned trends bring up fast-increasing data amounts of scattering data, as well as different scattering types (X-ray, neutron, laser and even microwaves). This struggles with data analysis software of the last generation, where data are usually analyzed assuming certain first-principle models and given data formats. To help researchers process and analyze scattering data more efficiently, we developed a general and model-free scattering data analysis software based on matrix operation, which has the unique advantage of high throughput scattering data processing, analysis and visualization. To maximize generality and efficiency, data processing is performed based on a three-dimensional matrix, where scattering curves are saved as matrices or vectors, rather than the traditional definition of paired values. It can not only realize image batch processing, background subtraction and correction, but also analyze data according to scattering theory and model, such as radius of gyration, fractal dimension and other physical quantities. In the aspect of visualization, the software allows the modify the color maps of two-dimensional scattering images and the gradual color variation of one-dimensional curves to suit efficient data communications. In all, this new software can work as a standalone platform for researchers to process, analyze and visualize scattering data from different research facilities without considering different file types or formats. All codes in this manuscript are open-sourced and can be easily implemented in matrix-based software, such as MATLAB, Python and Igor.

Folding behaviors of two-dimensional flexible polymers.

Unlike one-dimensional polymers, the theoretical framework on the behaviors of two-dimensional (2D) polymers is far from completeness. In this study, we model single-layer flexible 2D polymers of different sizes and examine their scaling behaviors in solution, represented by Rg ∼ Lν, where Rg is the radius of gyration and L is the side length of a 2D polymer. We find that the scaling exponent ν is 0.96 for a good solvent and 0.64 for under poor solvent condition. Interestingly, we observe a previously unnoticed phenomenon: under intermediate solvent conditions, the 2D polymer folds to maintain a flat structure, and as L becomes larger, multiple folded structures emerge. We introduce a shape parameter Q to diagram the relationship of folded structures with the polymer size and solvent condition. Theoretically, we explain the folding transitions by the competition between bending and solvophobic free energies.

Molecular Dynamics Simulation Study on the Structural and Thermodynamic Analysis of Oxidized and Unoxidized Forms of Polyaniline.

The conducting polymer polyaniline (PANI) has shown significant interest for the development of electrified membranes (EMs) with superior antifouling characteristics. However, the blending and doping of PANI with other polymers and nanomaterials highly influence the properties of the membrane surface. PANI exists in two forms: oxidized, known as emeraldine salt (ES), and unoxidized, referred to as emeraldine base (EB). Therefore, understanding the different forms of PANI and the variations between the oxidized and unoxidized forms along the length of the polymer chain is intriguing. In this paper, we present the design of a novel copolymer consisting of EB and ES monomers with varying charge densities and different segmental arrangements. We present various intra- and intermolecular structural properties of the PANI chains using all-atom molecular dynamics (MD) simulations. Herein, we present a detailed conformational free energy analysis to understand the conformational transitions of the PANI chains. Our results show increased radius of gyration (Rg) values with increased charge density. Furthermore, we also present the H-bonding, free energy analysis, reduced density gradient (RDG), and solvent-accessible surface area (SASA) values for the observed conformational transitions of PANI. Therefore, these observations are crucial in understanding the complex behavior of chains for designing target-specific polymeric materials.

Elucidating Protein Structures in the Gas Phase: Traversing Configuration Space with Biasing Methods.

Achieving accurate characterization of protein structures in the gas phase continues to be a formidable challenge. To tackle this issue, the present study employs Molecular Dynamics (MD) simulations in tandem with enhanced sampling techniques (methods designed to efficiently explore protein conformations). The objective is to identify suitable structures of proteins by contrasting their calculated Collision Cross-Section (CCS) with those observed experimentally. Significant discrepancies were observed between the initial MD-simulated and experimentally measured CCS values through Ion Mobility-Mass Spectrometry (IMS-MS). To bridge this gap, we employed two distinct enhanced sampling methods, Harmonic Biasing Potential and Adaptive Biasing Force, which help the proteins overcome energy barriers to adopt more compact configurations. These techniques leverage the radius of gyration as a reaction coordinate (guiding parameter), guiding the system toward compressed states that potentially match experimental configurations more closely. The guiding forces are only employed to overcome existing barriers and are removed to allow the protein to naturally arrive at a potential gas phase configuration. The results demonstrated close alignment (within ∼4%) between simulated and experimental CCS values despite using different strengths and/or methods, validating their efficacy. This work lays the groundwork for future studies aimed at optimizing biasing methods and expanding the collective variables used for more accurate gas-phase structural predictions.

Nanoscale Structures of Tough Microparticle-Based Films Investigated by Synchrotron X-Ray Scattering and All-Atom Molecular-Dynamics Simulation.

In this study, the nanoscale structures of microparticle-based films are revealed by synchrotron small-angle X-ray scattering (SAXS) and all-atom molecular-dynamics (AA-MD) simulations. The microparticle-based films consisting of the simplest acrylate polymer microparticles are applied as a model because the films are formed without additives and organic solvents and exhibit high toughness properties. The characteristic interfacial thickness (tinter) obtained from the SAXS analysis reflects the mixing degree of polymer chains on the microparticle surface in the film. The cross-linking density of inner microparticles is found to be strongly correlated to not only several properties of individual microparticles, such as swelling ratio and radius of gyration, but also the tinter and toughness of the corresponding films. Therefore, the tinter and toughness values follow a linear relationship because the cross-linking restricts the mixing of polymer chains between their surfaces in the film, which is a unique feature of microparticle-based films. This characteristic also affects their deformation behavior observed by in situ SAXS during tensile testing and their density profiles calculated by AA-MD simulations. This work provides a general strategy for material design to control the physical properties and structures of their films for advanced applications, including volatile organic compound-free sustainable coatings and adhesives.

Nanoscopically Confined 1,4-Polybutadiene Melts: Exploring Confinement by Alumina Nanorod and Nanopore Systems.

We present molecular dynamics simulations of a chemically realistic model of 1,4-polybutadiene (PBD) in contact with curved alumina surfaces. We contrast the behavior of PBD infiltrated into alumina pores with a curvature radius of about three times the radius of gyration of the chains to its behavior next to a melt dispersed alumina rod of equal absolute curvature. These confinement types represent situations occurring in polymer melts loaded with nanoparticles due to nanoparticle aggregation. While there are observable differences in structure and dynamics due to the different types of geometric confinement, the main effects stem from the strong attraction of PBD to the alumina surfaces. This strong attraction leads to a deformation of the chains in contact to the surfaces. We focus on temperatures well above the bulk glass transition temperature, but even at these high temperatures, the layers next to the alumina surfaces show glass-like relaxation behavior. We analyze the signature of this glassy behavior for neutron scattering or nuclear magnetic resonances experiments.

Compressive behaviors and deformation mechanism of carbon fiber reinforced epoxy composites: A microscopic and molecular dynamics perspective

AbstractInvestigating the macro‐mechanical properties of polymer composites at the nanoscale is a challenging topic. Here we report the compressive performances of carbon fiber‐reinforced epoxy composites using molecular dynamics (MD) simulations. The evolution of microstructure and microscopic energy, including free volume, radius of gyration, dihedral angle, potential energy, and interaction energy, has been investigated to characterize compressive behaviors at the nanoscale. Molecular chains gradually bend, and the movement space of the molecular chains decreases during compression loading. The radius of gyration and dihedral angle are deformed into a state of irreversible plasticity to accommodate the microstructural transformation. The interaction energy increases and subsequently declines as the carbon fiber/epoxy interface gets closer, reflecting the transition of the internal structure. The inhomogeneity and interfacial concentration distribution of stress, and local molecular stiffness under various strains have been obtained to reveal the nanoscopic mechanism of epoxy failure and interface delamination during compression. This study reveals the compression behaviors and deformation mechanism of carbon fiber‐reinforced epoxy composites at the molecular level, providing directions and possibilities for molecular design and structural optimization of composites.Highlights The nanoscopic compression deformation of CFRP composites is studied. Microstructural evolution and conformation transformation are revealed. The evolution and transition of microscopic energy are analyzed. Micro‐mechanism of epoxy deformation and interface delamination is elucidated.

Computational exploration of novel ketoprofen derivatives: Molecular dynamics simulations and MM-PBSA calculations for COX-2 inhibition as promising anti-inflammatory drugs

Computer-aided drug design is widely employed to identify novel compounds for therapeutic applications. Ketoprofen (KTP), a commonly used and marketed nonsteroidal anti-inflammatory drug (NSAID), is effective in treating pain, fever, inflammation, and some cancers. In this research, we explored the behavior of six analogues designed by structurally modifying the KTP molecule. Specifically, KTP-A and KTP-B contain a –CN group at the ortho position, KTP-C and KTP-D have a –CN group at the meta position, and KTP-E and KTP-F feature a –CF3 group at the meta position. To assess these analogues, we conducted molecular dynamics simulations (MD) to study their inhibitory effects on human cyclooxygenase 2 (COX-2), providing detailed insights into the structure and dynamics of the protein both with and without ligands. MD simulation, enhanced by technological advances, has proven to be a powerful tool for new drug discovery. We further quantified the binding affinity of these drug molecules toward COX-2 using molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) binding free energy calculations. The dynamic properties were evaluated through analyses of root mean square deviations (RMSD), root mean square fluctuations (RMSF), radius of gyration (Rg), solvent-accessible surface area (SASA), covariance matrix, principal component analysis (PCA), and Gibbs free energy landscapes (FEL). Ultimately, this study confirms that the six KTP derivatives are promising candidates for the treatment of inflammation, with KTP-B standing out as particularly effective.

Unwinding DNA strands by single-walled carbon nanotubes: Molecular docking and MD simulation approach

Despite the growing research into the use of carbon nano-tubes (CNTs) in science and medicine, concerns about their potential toxicity remain insufficiently studied. This study utilizes molecular docking calculations combined by molecular dynamics simulations to investigate the dynamic intricacies of the interaction between single-walled carbon nanotubes (swCNTs) and double-stranded DNA (dsDNA). By examining the influence of swCNT characteristics such as length, radius, and chirality, our findings shed light on the complex interplay that shapes the binding affinity and stability of the dsDNA-swCNT complex. Molecular docking results identify a zigzag swCNT, with a radius of 0.16 Å and a length of 38 Å, as exhibiting the highest binding affinity with dsDNA (−23.9 kcal/mol). Comprehensive analyses, spanning docking results, binding energies, RMSD, radius of gyration, and potential of mean force (PMF) profiles, provide a detailed understanding of the denaturation dynamics. The PMF profiles reveal the thermodynamic feasibility of the DNA-CNT interaction, outlining distinct energy landscapes and barriers: when the selected swCNT binds within the dsDNA groove, the system becomes trapped at the first and second local energy minima, occurring at 1.48 nm and 1.00 nm, respectively. Intramolecular hydrogen bond calculations show a significant reduction, affirming the denaturing effect of swCNTs on DNA. Furthermore, the study reveals a significant reduction in the binding affinity of Ethidium Bromide (EB) to dsDNA following its interaction with swCNT, with a decrease in EB binding to dsDNA of approximately 13.2 %. This research offers valuable insights into the toxic effects of swCNTs on dsDNA, contributing to a rationalization of the cancerous potential of swCNTs.

Comprehensive in silico characterization of Arabidopsis thaliana RecQl helicases through structure prediction and molecular dynamics simulations

Helicases are ubiquitous enzymes with specific functions that contribute to almost all nucleic acid metabolic processes. The RecQ helicase family is essential for integrity in all organisms through DNA replication, repair, and recombination. This study investigated five RecQ-like helicases in Arabidopsis thaliana (AtRecQl) that exhibit diverse structural and physiochemical attributes and functions. Cis-regulatory element analysis identified stress, hormone, cell cycle, and development-responsive modules involved in various events in plant growth and development. Gene ontology analysis revealed that the five AtRecQl were associated with various cellular components, molecular functions, and biological processes. Protein-protein interaction analysis also implicated some in various abiotic stress processes. Structural analysis and molecular dynamics (MD) simulations were performed to examine conformational stability through root means square deviation and radius of gyration, showing stable AtRecQl protein structures. Free energy landscape analysis validated thermodynamically stable structures throughout the MD simulation. Principle component analysis and probability density functions from MD simulations provided satisfactory structural variational data for the complexes and limited coordinate movements. These insights might greatly benefit future studies.

Networks of ion-pairs are responsible for the large differences in the thermal stability of two structurally similar aminopeptidases.

Aminopeptidases are an important class of enzymes for protein metabolism. Leucyl aminopeptidase (PepL) preferably removes leucine from the N-terminus of small peptides. PepL of Lacticaseibacillus casei was observed to be thermally unstable, while a structurally similar aminopeptidase T (AmpT) of Thermus thermophilus is highly stable. To understand the molecular interaction responsible for the large difference in their stability, molecular dynamics simulations were carried out to study the thermal stability of PepL and AmpT at 300 K to 450 K temperature range over 100 ns. PepL sampled a larger conformational space with a rugged free-energy landscape, while AmpT navigated a smoother energy landscape to reach the global minimum. The RMSD, RMSF, radius of gyration and principal component analysis suggested large movements in PepL than in AmpT with an increase in temperature. Analysis of residue-interaction network revealed AmpT possessing a greater number of low, medium and high energy contacts in comparison to PepL. AmpT showed a higher abundance of ion-pair clusters and ionic residues per cluster compared to PepL. Moreover, AmpT retained a greater number of high-energy contacts at elevated temperatures. These findings showed that the inherently lower stability of PepL originates from a comparatively smaller number of contacts and can be pivotal in engineering PepL for higher stability.

Evaluation of tamoxifen analogues as potential estrogen receptor alpha inhibitors for breast cancer treatment: A computational approach

Estrogen receptors, particularly ERα, play a key role in breast cancer progression, making them prime targets for therapeutic intervention. Tamoxifen (TAM), a selective estrogen receptor modulator (SERM), has been widely used for the treatment of ER+ breast cancer; however, its clinical application is limited by side effects and the emergence of resistance. This study aims to identify and evaluate TAM analogues with improved efficacy and reduced side effects by employing molecular docking and molecular dynamics (MD) simulations. Droloxifene, endoxifen, and afimoxifene emerged as promising candidates, exhibiting strong binding affinities with ERα, as indicated by highly negative binding energy (BE) values in docking simulations. MD simulations further validated the stability of the complexes formed between these analogues and ERα, with low root mean square deviation (RMSD) values and stable radius of gyration (Rg) profiles. Root mean square fluctuation (RMSF) analysis revealed balanced flexibility, with droloxifene and afimoxifene showing optimized flexibility for stable binding. Hydrogen bond analysis indicated more stable interactions between these analogues and ERα compared to TAM, suggesting enhanced binding affinity. MM/GBSA binding free energy analysis confirmed the high affinity of these analogues, with droloxifene displaying the most effective binding free energy (ΔGtotal) value. ADMET profiling suggests that droloxifene and endoxifen have superior pharmacokinetic properties relative to TAM. Overall, droloxifene, endoxifen, and afimoxifene represent promising alternatives to TAM, with the potential for further clinical development in breast cancer treatment. Experimental validation in cell-based and in vivo models will be crucial in future studies to confirm their efficacy and safety profiles.

Destabilisation of Alzheimer's amyloid-β protofibrils by Baicalein: mechanistic insights from all-atom molecular dynamics simulations.

Alzheimer's disease (AD) is the most common form of dementia and the fifth leading cause of death globally. Aggregation and deposition of neurotoxic Aβ fibrils in the neural tissues of the brain is a key hallmark in AD pathogenesis. Destabilisation studies of the amyloid-peptide by various natural molecules are highly relevant due to their neuroprotective and therapeutic potential for AD. We performed molecular dynamics (MD) simulation to investigate the destabilisation mechanism of amyloidogenic protofilament intermediate by Baicalein (BCL), a naturally occurring flavonoid. We found that the BCL molecule formed strong hydrophobic contacts with non-polar residues, specifically F19, A21, V24, and I32 of Chain A and B of the pentameric protofibril. Upon binding, it competed with the native hydrophobic contacts of the Aβ protein. BCL loosened the tight packing of the hydrophobic core by disrupting the hydrogen bonds and the prominent D23-K28 inter-chain salt bridges of the protofibril. The decrease in the structural stability of Aβ protofibrils was confirmed by the increased RMSD, radius of gyration, solvent accessible surface area (SASA), and reduced β-sheet content. PCA indicated that the presence of the BCL molecule intensified protofibril motions, particularly affecting residues in Chain A and B regions. Our findings propose that BCL would be a potent destabiliser of Aβ protofilament, and may be considered as a therapeutic agent in treating AD.

From unbound to bound states: Ab initio molecular dynamics of ammonia clusters with an excess electron.

Ab initio molecular dynamics simulations of negatively charged clusters of 2-48 ammonia molecules were performed to elucidate the electronic stability of the excess electron as a function of cluster size. We show that while the electronic stability of finite temperature clusters increases with cluster size, as few as 5-7 ammonia molecules can bind an excess electron, reaching a vertical binding energy slightly less than half of the bulk value for the largest system studied. These results, which are in agreement with previous studies wherever available, allowed us to analyze the excess electron binding patterns in terms of its radius of gyration and shape anisotropy and provide a qualitative interpretation based on a particle-in-a-spherical-well model.

Simultaneous effects of temperature and backbone length on static and dynamic properties of high-density polyethylene-1-butene copolymer melt: Equilibrium molecular dynamics approach

Abstract Temperature and chain length play significant roles in determining the physical properties of polymer melts. In the current computational research, a molecular dynamics (MD) approach was implemented to describe the static and dynamic properties of (1) high-density polyethylene-1-butene with 120 beads in backbone (PE120) and (2) entangled high-density polyethylene-1-butene with 600 beads in the backbone (PE600). The transferable potentials for phase equilibria force fields were used for CH2 beads in a defined initial condition. First, the equilibrium phase of the designed systems was reported with total energy and density convergency at various initial temperatures (T 0 = 450, 470, and 490 K). Also, gyration radius (R g) and end-to-end distance (R) were calculated for the static behavior description of the two PEs. Zero-shear viscosity (η 0), mean square displacement, and diffusion coefficient (D) were estimated to define the dynamic behavior of PE120 and PE600 systems. MD outputs predicted that 10 ns is sufficient for equilibrium phase detection inside polymeric samples. After equilibrium phase detection, R g converged to 14.97 and 17.35 Å in PE120 and PE600, respectively (T 0 = 450 K). Furthermore, MD outputs show that temperature variation can considerably affect the time evolution of the system. Numerically, the η 0 of PE120 and PE600 converged to 49 and 168 cp at 450 K. These results of η 0 parameter as a function of temperature are an important output of MD simulations. The results predicted that η 0 decreases to 24 and 44 cp for PE120 and PE600 samples with an increase in temperature from 450 to 490 K. With the creation of the entanglements network, D reached the highest value of 2 × 10−9 m2·s−1 among the designed polymeric systems. The results are in good consistency with experimental reports. It is expected that the result of this study can be used in designing improved polymeric systems for real applications.

Cheminformatics-driven prediction of BACE-1 inhibitors: Affinity and molecular mechanism exploration

The β-secretase, sometimes referred to as BACE1 or Asp2, is the enzyme responsible for initiating the production of Aβ by breaking down the amyloid precursor protein. Hence, BACE is a pivotal target for pharmacological intervention aimed at diminishing the production of Aβ in Alzheimer's disease (AD). We did a quantitative structure-activity relationship (QSAR) study on 1235 compounds that had been experimentally reported as BACE-1 inhibitors (Ki) to find the target molecule and structural patterns linked to blocking the BACE-1 receptor. The OECD-recommended genetic algorithm-multiple linear regression (GA-MLR) QSAR model strikes a good balance between being able to make accurate predictions and understanding how things work. It achieves high values for many evaluation metrics, including R2tr = 0.8047, Q2LMO = 0.802, R2ex = 0.805, CCCex = 0.891, Q2-F1=0.801, Q2-F2=0.799, and Q2-F3=0.815. The mechanistic interpretation of QSAR has identified some nitrogen atoms that are required to block beta-secretase and make it less effective at doing its job. A positively charged aromatic carbon atom has a more significant impact on beta-secretase-1 inhibition. The docking study showed that the catalytic dye residues Asp32 and Asp228 become protonated when compound 27 is present, but they stay unprotonated when compound 27 is not present. These rings of pyrazine and pyridine interact hydrophobically with Tyr71 and Ile118 residues, confirming the pharmacophoric features seen in the QSAR data. We examined the stability of both the protein-ligand complex and the apo-protein. The apoprotein had an average gyration radius of 22.13, whereas the protein-ligand complex had an average gyration radius of 22.91. No changes were made to the results from the molecular docking, molecular dynamics (MD) simulation, MMGBSA (Molecular Mechanics Generalized Born Surface Area), or DFT analyses. Therefore, the current work could effectively contribute to the future development of BACE inhibitors in medication design.

A novel data-driven approach for customizing destination choice set: A case study in the Netherlands

Modeling the destination choice has been of great interest for travel behavior community as well as policymakers in understanding the demand for land use and transportation infrastructures at aggregate and disaggregate levels and possibly devising policies to balance the demand and supplies. One of the challenges underlying predictions of location choice is the large choice set. While traditionally many methods had been devised to limit the choice set size either on a rather ad hoc basis or based on space–time prism by removing the locations out of reach of the subjects, the current study takes a substantially different approach and proposes a data-driven method to customize the generation of the choice set. The proposition is that observing the mobility patterns of citizens for multiple weeks would enable us to limit the choice set, depending on how far the subjects travel (beyond or within the distance they travel for their most frequent activities) to conduct their various activities. More precisely, using longitudinal trajectory data, we first classify people into two subgroups: returners and explorers, based on the size of the area (around their k most visited locations: k-radius of gyration) they move during the observation period. The destination choice set for four types of activities is then customized for returners (and explorers) and is used in a sequence of decisions represented by decision trees for the prediction of their destinations. The models for the whole sample and each subgroup separately are compared. The results suggest that the accuracy of destination prediction improves substantially for all four selected activity types, especially for the returners whose choice sets are formed based on their radius of gyration.