Scalable Analysis of Dipole Moment Fluctuations for Characterizing Intermolecular Interactions and Structural Stability.

Accurately predicting protein-ligand interactions is essential in computational molecular biochemistry and in silico drug development. Monitoring changes in molecular dipole moments through molecular dynamics simulations provides valuable insights into dipole-dipole interactions, which are critical for understanding protein structure stability and predicting protein-ligand binding affinity. In this study, we propose a novel method to monitor changes in the interangle between dipole vectors of residue molecules within proteins and ligand molecules, aiming to evaluate the strength and consistency of interactions within the complex. Additionally, we extend the concept of positional root-mean-square fluctuation (RMSF), commonly used for protein structure stability analysis, to dipole moments, thus defining dipole moment RMSF. This enables us to analyze the stability of dipole moments for each residue within the protein and compare them across residues and between binding and non-binding complexes. Using the CRBP1-retinoic acid complex as our model system, we observed a significant difference in the interangle change of dipole moments for the key residue at the residue-level between the non-binding and binding complexes. Furthermore, we found that the dipole moment RMSF value of the non-binding complex was substantially larger than that of the binding complex, indicating greater dipole moment instability in the non-binding complex. Leveraging the concept of scalability inherent in the calculation of dipole moment vectors, we systematically expanded the residues within the protein's primary secondary structure. Our dipole moment analysis approach can provide valuable predictive insights into complex candidates, especially in situations where experimental comparisons are challenging.

Detection of sulfur mustard simulant by trisaryl phosphoric triamide-based resin using a quartz crystal microbalance sensor.

Chemical warfare agents (CWAs) pose a persistent threat to human safety, and bis(2-chloroethyl) sulfide, or sulfur mustard (SM) is one of the most dangerous substances and is able to cause serious harm. Detecting SM gas is vital, but current methods have high-temperature requirements and limited selectivity, mainly because of the lack of CWA receptor development, and this makes them challenging to use. To address this issue, we present a trisaryl phosphoric triamide-based resin receptor that preferentially interacts with a SM simulant 2-chloroethyl ethyl sulfide (2-CEES) through dipole interactions. The receptor was synthesized through a facile process using an amine and a triethyl phosphate and the properties of its coating were enhanced using epoxy chemistry. The receptor's superior triamide structure was evaluated using a quartz crystal microbalance and reactivity was confirmed by observing the variations in reactivity according to the number of phosphoramides. The receptor showed better reactivity to 2-CEES vapor than to the known poly(epichlorohydrin) and showed selectivity to other volatile organic compounds. Moreover, its durability was evident even 30 days post-coating. The applicability of this receptor extends to array sensors, sound acoustic wave sensors, and chemo-resistive and chemo-capacitive sensors, and it promises advances in chemical warfare agent detection.

A general one-pot, solvent-free solid-state synthesis of biocompatible metal nanoparticles using dextran as a tool: Evaluation of their catalytic and anti-cancer activities.

We propose a general green method coupled with a solid-state vibration ball milling strategy for the synthesis of various metal nanoparticles (MNPs), employing a polymeric carbohydrate dextran (Dx) as a reducing and stabilizing molecule. The synthesis of size-controlled Dx-based MNPs (Dx@MNPs), featuring comparatively narrow size distributions, was achieved by controlling the mass ratio of the reactants, reaction time, frequency of the vibration ball mill, and molecular weight of Dx. Notably, this process was conducted at ambient temperatures, without the aid of solvents and accelerating agents, such as NaOH, and conventional reductants as well as stabilizers. Thermal properties of the resulting Dx@MNPs nanocomposites were extensively investigated, highlighting the influence of metal precursors and reaction conditions. Furthermore, the catalytic activity of synthesized nanocomposites was evaluated through the reduction reaction of 4-nitrophenol, exhibiting great catalytic performance. In addition, we demonstrated the excellent biocompatibility of the as-prepared Dx@MNPs toward human embryonic kidney (HEK-293) cells, revealing their potential for anticancer activities. This novel green method for synthesizing biocompatible MNPs with Dx expands the horizons of carbohydrate-based materials as well as MNP nanocomposites for large-scale synthesis and controlled size distribution for various industrial and biomedical applications.

Efficient Super-Resolution Method for Targets Observed by Satellite SAR.

This study presents an efficient super-resolution (SR) method for targets observed by satellite synthetic aperture radar (SAR). First, a small target image is extracted from a large-scale SAR image and undergoes proper preprocessing. The preprocessing step is adaptively designed depending on the types of movements of targets. Next, the principal scattering centers of targets are extracted using the compressive sensing technique. Subsequently, an impulse response function (IRF) of the satellite SAR system (IRF-S) is generated using a SAR image of a corner reflector located at the calibration site. Then, the spatial resolution of the IRF-S is improved by the spectral estimation technique. Finally, according to the SAR signal model, the super-resolved IRF-S is combined with the extracted scattering centers to generate a super-resolved target image. In our experiments, the SR capabilities for various targets were investigated using quantitative and qualitative analysis. Compared with conventional SAR SR methods, the proposed scheme exhibits greater robustness towards improvement of the spatial resolution of the target image when the degrees of SR are high. Additionally, the proposed scheme has faster computation time (CT) than other SR algorithms, irrespective of the degree of SR. The novelties of this study can be summarized as follows: (1) the practical design of an efficient SAR SR scheme that has robustness at a high SR degree; (2) the application of proper preprocessing considering the types of movements of targets (i.e., stationary, moderate motion, and complex motion) in SAR SR processing; (3) the effective evaluation of SAR SR capability using various metrics such as peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), focus quality parameters, and CT, as well as qualitative analysis.

Comparative molecular dynamics study on the features of binding and non-binding modes of retinoic acid in cellular retinol-binding protein (I).

Retinoids play crucial roles in various biological processes by interacting with their carrier proteins such as cellular retinol-binding protein (CRBP). Understanding the molecular interactions between retinoids and CRBP enables their pharmacological and biomedical applications. Experimentally, CRBP(I) does not bind to retinoic acid, but when arginine is introduced into 108th residue instead of glutamine (Q108R), it binds to retinoic acid. Here, molecular dynamics simulations were performed to understand the differences in the microscopic and dynamic behaviors of the non-binding wild-type CRBP(I)-retinoic acid and binding Q108R variant-retinoic acid complexes. The ligand RMSD and RMSF, the binding poses of binding motif amino acids, and the number of hydrogen bonds and salt-bridges revealed the relative instability of the non-binding complex. In particular, the ligand's terminal group showed very different dynamics and interactions. So far, most studies have focused on the binding characteristics of retinoids, but the features of their non-binding modes have not been studied well. This study provides some structural insights into the non-binding modes of a retinoid in CRBP, which may be applicable in retinoid-based drug discovery and protein engineering through computational modeling.

Analysis of protein-protein interface with incorporating low-frequency molecular interactions in molecular dynamics simulation.

Protein-protein interactions are vital for various biological processes such as immune reaction, signal transduction, and viral infection. Molecular Dynamics (MD) simulation is a powerful tool for analyzing non-covalent interactions between two protein molecules. In general, MD simulation studies on the protein-protein interface have focused on the analysis of major and frequent molecular interactions. In this study, we demonstrate that minor interactions with low-frequency need to be incorporated to analyze the molecular interactions in the protein-protein interface more efficiently using the complex of SARS-CoV2-RBD and ACE2 receptor as a model system. It was observed that the dominance of interactions in the MD-simulated structures didn't directly correlate with the interactions in the experimentally determined structure. The interactions from the experimentally determined structure could be reproduced better in the ensemble of MD simulated structures by including the less frequent interactions compared to the norm of choosing only highly frequent interactions. Residue Interaction Networks (RINs) analysis also showed that the critical residues in the protein-protein interface could be more efficiently identified by incorporating low-frequency interactions in MD simulation. It is expected that the approach proposed in this study can be a new way of studying protein-protein interaction through MD simulation.

PPP1R81 correlates with the survival and cell proliferation in lower-grade glioma.

BACKGROUND: The specific functions of PPP1R81 has been elucidated in multiple cancers; however, its role in lower-grade glioma (LGG) remains unknown. In this research, we inspected the specific role of PPP1R81 in LGG. METHODS: We totally evaluated the expression pattern and prognostic role of PPP1R81 in multitudinous tumors. Subsequently, we systematically examined the connection between PPP1R81 expression and prognosis, clinical characteristics, biological functions, genetic variations, and immunological characteristics in LGG according to the Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Altas (CGGA) databases. In vitro experiments were executed to inspect the expression level and specific roles of PPP1R81 in LGG. RESULTS: PPP1R81 was elevated in multiple tumors and was tightly linked to a poor prognosis. LGG with higher expression of PPP1R81 showed poorer prognosis compared with lower expression of PPP1R81. The results of univariate and multivariate Cox regression analyses confirmed that the expression of PPP1R81 was an independent prognostic biomarker of LGG. Immune cell infiltration, immune checkpoint genes (ICPGs), copy number alterations (CNA), and tumor mutation burden (TMB) were also closely associated with PPP1R81 expression in LGG. In vitro experiments demonstrated that PPP1R81 was up-regulated and closely interrelated with cell proliferation and cell cycle in LGG. CONCLUSION: PPP1R81 was an independent prognostic signature and underlying therapeutic target for patients with LGG.

N6-methyladenosine (m6A)-connected lncRNAs are linked to survival and immune infiltration in glioma patients.

BACKGROUND: The connection between m6A-assiociateed lncRNAs and prognosis has been demonstrated in multiple types of tumors. However, potential roles of m6A-assiociateed lncRNAs in glioma is still rare. METHODS: We implemented consensus cluster analysis to group the downloaded samples into two subtypes. The least absolute shrinkage and selection operator (LASSO) analysis was used to create a risk model. Additionally, the conjunction between m6A-related lncRNAs and immune cells infiltration was explored by conducting the R package. Ultimately, we inspected the underlying downstream pathways of the two subtypes by performing Gene Set Enrichment Analysis (GSEA). The expression level of m6A-connected lncRNAs in glioma were examined by conducting in vitro experiments. RESULTS: We ascertained two subtypes of glioma in line with the consensus clustering of m6A-associated lncRNAs. We confirmed that age, grade, and IDH are related to the two subtypes. Additionally, the immune cells infiltration and immune checkpoint molecules of the two clusters were discussed. A risk signature including AL359643.3, AL445524.1, AL162231.2, AL117332.1, AP001486.2, POLR2J4, AC120036.4, LINC00641, LINC00900, CRNDE, and AL158212.3, was identified using the Cox regression and LASSO analyses. We also verified the prognostic value and discussed the immune cells infiltration and immune checkpoint molecules of the risk signature. In vitro experiments verified that the m6A-associated lncRNAs was abnormally expressed in glioma. CONCLUSION: We elaborated the significant role of m6A-connected lncRNAs in glioma prognosis and immune infiltration and suggest that these key regulators may serve as underlying therapeutic targets to build up the efficacy of glioma immunotherapy.

Recovery time from VR sickness due to susceptibility: Objective and quantitative evaluation using electroencephalography.

With the increasing use of virtual reality (VR) devices, interest in reducing their negative effects, such as VR sickness, is also increasing. This study used electroencephalography (EEG) to investigate participants' VR sickness recovery time after watching a VR video. We tested 40 participants in advance using a motion sickness susceptibility questionnaire (MSSQ). We classified the participants into two groups (sensitive group/non-sensitive group) depending on their MSSQ scores. We used a simulator sickness questionnaire (SSQ) and EEG to evaluate VR sickness. The SSQ score increased significantly after watching the VR sickness-inducing video (VR video) in both groups (p < 0.001). The recovery time based on the SSQ was 11.3 ± 6.6 min for the sensitive group and 9.1 ± 5.2 min for the non-sensitive group. The difference in recovery time between the two groups was not significant (p > 0.05). EEG results showed that recovery time took an average of 11.5 ± 7.1 min in both groups. The EEG data showed that the delta wave increased significantly across all brain areas (p < 0.01). There was no statistical difference between groups in recovering VR sickness depending on individual characteristics. However, we confirmed that subjective and objective VR recovery required at least 11.5 min. This finding can inform recommendations regarding the VR sickness recovery times.

Effects of Vitamin D Supplementation on Testosterone, Prostate, and Lower Urinary Tract Symptoms: A Prospective, Comparative Study.

PURPOSE: Several studies have associated the serum vitamin D level with total testosterone levels and the prostate volume. Herein, we investigated the effect of vitamin D supplementation on testosterone, prostate, and lower urinary tract symptoms (LUTS) in men. MATERIALS AND METHODS: Men over 40 years of age diagnosed with a vitamin D deficiency (25[OH]D <20 ng/mL) who received vitamin D supplementation for one year were included in the study and administered 25,000 IU of cholecalciferol every 2 weeks. Prostate ultrasound, uroflowmetry, postvoid residual urine volume measurement, and serological tests (serum testosterone levels, etc.) were performed upon diagnosis and one year later. Participants also answered the International Prostate Symptom Score (IPSS) and Aging Males' Symptoms Scale (AMS) questionnaires. RESULTS: A significant increase was observed in the vitamin D level following one year of vitamin D supplementation, with a significant decrease in the postvoid residual urine volume, total IPSS score and without a significant change in the prostate volume. Improved psychological subscale score of AMS questionnaire was observed with a statistical significance. CONCLUSIONS: Vitamin D supplementation suppressed the increase in the prostate volume and improved the LUTS. Although there is no direct effect on serum testosterone levels, vitamin D supplementation helped improve hypogonadal symptoms.

Residue interaction network and molecular dynamics simulation study on the binding of S239D/I332E Fc variant with enhanced affinity to FcγRIIIa receptor.

Engineering of Fc has been adapted as an efficient method for enhanced or reduced affinity towards Fc receptors in the development of therapeutic antibodies. S239D/I332E mutation of Fc induces approximately two logs greater affinity to the FcγRIIIa receptor and has been extensively employed in various Fc engineering studies. It is known that the mutation gives rise to the formation of salt bridges between the mutated residues of Fc and FcγRIIIa, but the overall effect of the mutation in the binding interface of the Fc-FcγRIIIa complex is still unclear. In this study, the molecular interactions in the binding interface of mutant Fc and FcγRIIIa were analyzed and compared with those of wild-type Fc binding through residue interaction network (RIN) analysis and molecular dynamics (MD) simulation. RIN analysis identified specific molecular interactions and Hub residues in the interfaces, and their numbers were increased by introducing the mutation, with maintaining most of the molecular interactions in the wild-type complex. MD simulation study revealed that the numbers of stable electrostatic interactions and stable Hub residues in the mutant complex were higher than those in the wild-type complex. The introduced mutations were shown to form further charge-charge attractive interactions in addition to the identified salt bridges without generating any repulsive interactions. These results are expected to provide further structural insight into Fc variants' design based on the S239D/I332E mutation.

Super-Resolution Procedure for Target Responses in KOMPSAT-5 Images.

Recently, target analysis using satellite SAR images has received much attention in the area of satellite SAR remote sensing. Because the spatial resolution of the target response in the satellite SAR image is a main factor that has a large effect on target analysis performances, the improvement of the spatial resolution of target response is required to enhance the target analysis capability. However, the spatial resolution is already determined in the satellite SAR system design process. To solve the above problem, the super-resolution techniques that have been applied to radar images can be utilized. However, the application of the super-resolution techniques to the target response in the satellite SAR image is not simple due to the following reasons. First, the target's motion induces severe blurring of the target response, which impedes the successful improvement of spatial resolution. Next, the zero-region in the frequency spectrum of the target image containing the target response also hinders the generation of the super-resolved image. To successfully improve spatial resolution of the satellite SAR image, the super-resolution techniques should be combined with proper preprocessing steps that can cope with the above two issues. In this paper, the whole super-resolution procedure for target responses in KOMPSAT-5 images is described. To the best of the authors' knowledge, the description of the whole super-resolution procedure for target responses is the first ever attempt in the area of satellite SAR. First, a target image containing the target response is extracted from a large-scale KOMPSAT-5 image. Subsequently, the target image is transformed to be appropriate for the utilization of super-resolution techniques by proper preprocessing steps, considering the direction of super resolution and the motion of the target. Then, some super-resolution techniques are utilized to improve the spatial resolutions and qualities of the target images. The super-resolution performances of the proposed scheme are validated using various target images for point static, extended static, and extended moving targets. The novelties of this paper can be summarized as follows: (1) the practical design of whole super-resolution processing for real satellite SAR images; (2) the performance evaluation of super-resolution techniques on real satellite SAR images. The results show that the proposed scheme can led to noticeable improvements of spatial resolution of the target images for various types of targets with reliable computation times. In addition, the proposed scheme also enhanced PSLR, ISLR, and IC, leading to clearer scattering information of the principal scatterers. Consequently, the proposed method can assist in extracting more precise and meaningful information for targets represented in KOMPSAT-5 images, which means great potential for target recognition.

Cell disruption and lipid extraction from Chlorella species for biorefinery applications: Recent advances.

Chlorella is a promising microalga for CO2-neutral biorefinery that co-produces drop-in biofuels and multiple biochemicals. Cell disruption and selective lipid extraction steps are major technical bottlenecks in biorefinement because of the inherent robustness and complexity of algal cell walls. This review focuses on the state-of-the-art achievements in cell disruption and lipid extraction methods for Chlorella species within the last five years. Various chemical, physical, and biological approaches have been detailed theoretically, compared, and discussed in terms of the degree of cell wall disruption, lipid extractability, chemical toxicity, cost-effectiveness, energy use, scalability, customer preferences, environment friendliness, and synergistic combinations of different methods. Future challenges and prospects of environmental-friendly and efficient extraction technologies are also outlined for practical applications in sustainable Chlorella biorefineries. Given the diverse industrial applications of Chlorella, this review may provide useful information for downstream processing of the advanced biorefineries of other algae genera.

Protein Repair and Analysis Server: A Web Server to Repair PDB Structures, Add Missing Heavy Atoms and Hydrogen Atoms, and Assign Secondary Structures by Amide Interactions.

The Protein Data Bank (PDB) file format developed at Brookhaven National Laboratory is the most popular file format to store biological data and is widely supported by many software programs for the editing and visualization of macromolecular structures. Unfortunately, many of these structures have variety of issues ranging from missing side chains and/or atoms to alternate locations (rotamers). To fix these flaws, one has to learn a new program, compile modules, and install libraries. To overcome these challenges, we present Protein Repair and Analysis Server (PRAS), an easy-to-use web server to repair protein structures and add missing atoms. The PRAS program flow has two main sections. In the first section, several subroutines are called to deal with sequence microheterogeneity, rotamers, missing side chains, heavy atoms, or hydrogen atoms. A log file is generated detailing irregularities and their fixes as carried out by the program. In the later section, the program uses the error-corrected protein structure to assign secondary structure elements based on amide-amide interactions of the backbone. Plots of four Ramachandran types (general, glycine, proline, and pre-proline) and percentage of secondary structure elements; a log file and the error-corrected PDB file can be downloaded by clicking on the download link generated by the server. The server is freely available and is accessed through its web address at www.protein-science.com. Alternatively, users can download the source code from the server or install the program on their local machines following the instructions at https://pypi.org/project/Pras-Server/ or https://github.com/osita-sunday-nnyigide/Pras_Server. While the present work focuses on the repair of structural data in the PDB format, the server is capable of fixing similar errors in the extensible and newly adopted mmCIF format.

COVID-19 outbreak response at a nursing hospital in South Korea in the post-vaccination era, including an estimation of the effectiveness of the first shot of the Oxford-AstraZeneca COVID-19 vaccine (ChAdOx1-S).

OBJECTIVES: We descriptively reviewed a coronavirus disease 2019 (COVID-19) outbreak at a nursing hospital in Gyeonggi Province (South Korea) and assessed the effectiveness of the first dose of the Oxford-AstraZeneca vaccine in a real-world population. METHODS: The general process of the epidemiological investigation included a public health intervention. The relative risk (RR) of vaccinated and unvaccinated groups was calculated and compared to confirm the risk of severe acute respiratory syndrome coronavirus-2 (SARSCoV-2) infection, and vaccine effectiveness was evaluated based on the calculated RR. RESULTS: The population at risk was confined to ward E among 8 wards of Hospital X, where the outbreak occurred. This population comprised 55 people, including 39 patients, 12 nurses, and 4 caregivers, and 19 cases were identified. The RR between the vaccinated and unvaccinated groups was 0.04, resulting in a vaccine effectiveness of 95.3%. The vaccination rate of the nonpatients in ward E was the lowest in the entire hospital, whereas the overall vaccination rate of the combined patient and non-patient groups in ward E was the third lowest. CONCLUSION: The first dose of the Oxford-AstraZeneca vaccine (ChAdOx1-S) was effective in preventing SARS-CoV-2 infection. To prevent COVID-19 outbreaks in medical facilities, it is important to prioritize the vaccination of healthcare providers.

Estimating objective (EEG) and subjective (SSQ) cybersickness in people with susceptibility to motion sickness.

Cybersickness refers to the uncomfortable side effects, such as headaches, dizziness, and nausea, felt while experiencing virtual reality (VR). This study investigated cybersickness in people with sensitivity to motion sickness using electroencephalography (EEG), the Simulator Sickness Questionnaire (SSQ), and simple VR content. Based on the scores from the Motion Sickness Susceptibility Questionnaire (MSSQ), 40 males in their twenties were selected as the sensitive group (n = 20) and non-sensitive group (n = 20). The experiment contained two conditions: a baseline condition representing a resting state and a cybersickness condition in which watching VR content induced cybersickness. The SSQ score increased significantly after watching the VR content in both groups. The sensitive group showed significantly lower absolute power in the beta and gamma bands than the non-sensitive group. The cybersickness condition showed significantly increased delta and decreased alpha compared to the baseline condition. We evaluated EEG and SSQ to identify subjective symptoms and objective physiological changes associated with cybersickness.

N-Triflyl Phosphoric Triamide: A High-Performance Purely Organic Trifurcate Quartz Crystal Microbalance Sensor for Chemical Warfare Agent.

G-, V-, and A-series nerve agents are extremely toxic organophosphorus chemical warfare agents (CWAs) that incorporate P═O functional groups. Their colorless, tasteless, and odorless nature makes rapid and efficient detection challenging. Here, we report an unprecedented N-triflyl phosphoric triamide (N-TPT) receptor, which is a new class of triple hydrogen bonding donor molecular sensors for CWA recognition via noncovalent host-guest-type interactions. The highly robust trifurcate structures were designed based on density functional theory (DFT) computations and synthesized from N-triflyl phosphorimidoyl trichloride by simple stepwise processes. Quartz crystal microbalance (QCM) analysis allowed robust detection of typical CWA simulants, such as dimethyl methylphosphonate. The concentration-dependent QCM profiles were fitted with the Sips isotherm model, revealing that the thermodynamic parameters of the binding behaviors are roughly correlated with the calculated results. Developed N-TPT receptors show higher binding abilities than previously reported receptors and reasonable selectivity over other volatile compounds.

COVID-19 outbreak response at a nursing hospital in South Korea in the post-vaccination era, including an estimation of the effectiveness of the first shot of the Oxford-AstraZeneca COVID-19 vaccine (ChAdOx1-S)

Objectives@#We descriptively reviewed a coronavirus disease 2019 (COVID-19) outbreak at a nursing hospital in Gyeonggi Province (South Korea) and assessed the effectiveness of the first dose of the Oxford-AstraZeneca vaccine in a real-world population. @*Methods@#The general process of the epidemiological investigation included a public health intervention. The relative risk (RR) of vaccinated and unvaccinated groups was calculated and compared to confirm the risk of severe acute respiratory syndrome coronavirus-2 (SARSCoV-2) infection, and vaccine effectiveness was evaluated based on the calculated RR. @*Results@#The population at risk was confined to ward E among 8 wards of Hospital X, where the outbreak occurred. This population comprised 55 people, including 39 patients, 12 nurses, and 4 caregivers, and 19 cases were identified. The RR between the vaccinated and unvaccinated groups was 0.04, resulting in a vaccine effectiveness of 95.3%. The vaccination rate of the nonpatients in ward E was the lowest in the entire hospital, whereas the overall vaccination rate of the combined patient and non-patient groups in ward E was the third lowest. @*Conclusion@#The first dose of the Oxford-AstraZeneca vaccine (ChAdOx1-S) was effective in preventing SARS-CoV-2 infection. To prevent COVID-19 outbreaks in medical facilities, it is important to prioritize the vaccination of healthcare providers

Effect of molecular properties of the protein-ligand complex on the prediction accuracy of AutoDock.

Molecular docking approach has been extensively used to predict the ligand's binding conformation in the binding pocket of protein. However, its prediction accuracy is still limited and highly dependent on target protein-ligand complexes. In this study, we investigated the effects of ligand torsion number, ligand hydrophobicity, and binding-site hydrophobicity on the prediction accuracy of Autodock, a popular molecular docking tool, combinatorially as well as respectively. A clear understanding of how these properties affect the prediction accuracy was observed when these properties were studied combinatorially rather than individually. The combination of low ligand torsion number-hydrophilic ligand-hydrophobic binding site provided the best prediction accuracy while the high ligand torsion number-hydrophilic ligand-hydrophobic binding pocket combination showed the least prediction accuracy. This study allowed us to determine the molecular properties of complex, showing relatively higher or low prediction accuracy and can be employed as a reference in the molecular docking studies using Autodock.

Test-retest reliability of the virtual reality sickness evaluation using electroencephalography (EEG).

No reliable quantitative and objective measurement method for virtual reality (VR) sickness has been firmly established to date. Electroencephalography (EEG) may be a strong candidate to evaluate VR sickness objectively. However, no test-retest evaluation has been made for VR sickness using EEG. To recruit VR sickness-sensitive participants, we tested 858 participants (age = 20's-50's) using the Motion Sickness Susceptibility Questionnaire (MSSQ). Among them, we recruited 21 males (average age = 25.0) who obtained the 75th percentile of scores on the MSSQ (32.9 ± 5.7). VR sickness was evaluated twice (one week apart) using EEG with VR video content designed to cause VR sickness. A Simulation Sickness Questionnaire (SSQ) was also used to evaluate VR sickness. In terms of the reliability of EEG, ICC and Cronbach's alpha analyses showed that three waves (delta, theta, and alpha) were consistent in two areas (frontal and central). A significant difference in EEG was also found repeatedly between the baseline and VR sickness (delta, theta, and alpha) in two areas (frontal and central). We evaluated EEG for its reliability and found specific waves and areas that showed good consistency and significant changes associated with VR sickness. These findings may support further research of VR sickness evaluation.