Assigning bond orders is a necessary and essential step for characterizing a chemical structure correctly in force field based simulations. Several methods have been developed to do this. They all ...have advantages but with limitations too. Here, an automatic algorithm for assigning chemical connectivity and bond order regardless of hydrogen for organic molecules is provided, and only three dimensional coordinates and element identities are needed for our algorithm. The algorithm uses hard rules, length rules and conjugation rules to fix the structures. The hard rules determine bond orders based on the basic chemical rules; the length rules determine bond order by the length between two atoms based on a set of predefined values for different bond types; the conjugation rules determine bond orders by using the length information derived from the previous rule, the bond angles and some small structural patterns. The algorithm is extensively evaluated in three datasets, and achieves good accuracy of predictions for all the datasets. Finally, the limitation and future improvement of the algorithm are discussed.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
In order to explore a scientific and effective fault complexity evaluation method, through analyzing the basic characteristic indicators of the fault, based on the fractal theory, selecting the ...fractal dimension value of the fault, the fault density value, the number of fault interchange points and the fault intensity index as the evaluation indicators, we use the idea of game theory to construct a combined weighting method of order relation analysis method and entropy weight method, and evaluate the complexity of faults in the north No.10 mining area of Jiangzhuang Coal Mine. The results are as follows: the simple and medium tectonic areas of the fault are mainly located in the west, south and north of the study area, and are distributed in a ring shape; the lower complex structural areas are mainly located in the south and north of the study area, distributed in strips and blocks; the complex structural areas are mainly located in the middle of the study area, and some are scattered in the south and north;
Tellurium nanostructures were synthesized by galvanic displacement reaction (GDR) of aluminum in an alkaline solution containing TeO32− ions. Due to negative redox potential of Al/AlO2− (i.e., −2.50V ...vs. sat. Ag/AgCl), TeO32− (+IV) can be reduced to Te22− (-I) and Te2− (-II), which resulted in the deposition of Te (0) nanostructures in the solution via chemical reaction between Te22− or Te2− and TeO32−. The deposition mechanism led to the formation of unique “rice-like” nanostructures in the solution instead of branched structures on the substrate. The sharp tips of the “rice-like” nanostructures may be attributed to the high density of surface charges at the tips. The morphology, diameter and aspect ratio of Te “rice-like” nanostructures were altered by the TeO32− concentration, solution pH, reaction time and the reaction temperature. Electrochemical analytical methods, including open circuit potential (OCP) and linear polarizations (LPs), were used to investigate the reaction mechanisms. The enhancement of piezoelectric constant (d11) of nanorices at small diameter was probably due to a flexoelectric effect.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Hypertension is the main risk factor for hemorrhagic stroke. Aldehyde dehydrogenase 2 (ALDH2) may inhibit the occurrence of hypertension by anti-oxidative stress and vascular dilation. The purpose ...was to investigate the relationship of
polymorphisms with hemorrhagic stroke in Hakka Chinese.
A total of 329 patients with hemorrhagic stroke and 515 controls were enrolled, and medical records (smoking and drinking history, hypertension, and diabetes) were collected. The genotypes of
rs671 of the two groups were detected and analyzed.
The proportion of the
rs671 G/G, G/A, and A/A genotype in patients with hemorrhagic stroke was 55.9%, 37.4%, and 6.7%, respectively, while those were 65.0%, 30.7%, and 4.3% in controls, respectively. There was statistically significant difference in
rs671 genotypes distribution (
=0.021) and alleles distribution (
=0.005) between patients and controls. Among hemorrhagic stroke patients, no statistically significant differences were observed between patients with
different genotypes. Logistic regression analysis showed that there was significantly high risk of hemorrhagic stroke in men (male vs female: adjusted OR 1.711, 95% CI 1.154-2.538,
=0.008), the presence of hypertension (with vs without hypertension: adjusted OR 16.095, 95% CI 10.958-23.641,
<0.001), and the presence of
rs671 G/A genotype (G/A vs G/G: adjusted OR 1.679, 95% CI 1.151-2.450,
=0.007) or A/A genotype (A/A vs G/G: adjusted OR 2.516, 95% CI 1.132-5.591,
=0.024).
rs671 polymorphism likely a risk factor for hemorrhagic stroke.
The study was carried out to investigate protective effect of
Potentilla anserine polysaccharide on the process of apoptosis induced by hydrogen peroxide (H
2O
2) in murine splenic lymphocytes
in ...vitro. The results showed that apoptosis occured in murine splenic lymphocytes treated with H
2O
2
in vitro at a concentration of 200
μmol/L. Treatments with
Potentilla anserine polysaccharide at concentrations of 50, 100, 200 or 400
μg/mL decreased the amount of apoptosis cells and the anti-apoptosis effect showed a dose dependent manner increase. The results showed that PAP reduced intracellular oxidative damages and dose-dependently inhibited apoptosis. This suggests that PAP is a potential anti-apoptotic agent.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Entropy effects play an important role in drug-target interactions, but the entropic contribution to ligand-binding affinity is often neglected by end-point binding free energy calculation methods, ...such as MM/GBSA and MM/PBSA, due to the expensive computational cost of normal mode analysis (NMA). Here, we systematically investigated entropy effects on the prediction power of MM/GBSA and MM/PBSA using >1500 protein-ligand systems and six representative AMBER force fields. Two computationally efficient methods, including NMA based on truncated structures and the interaction entropy approach, were used to estimate the entropic contributions to ligand-target binding free energies. In terms of the overall accuracy, we found that, for the minimized structures, in most cases the inclusion of the conformational entropies predicted by truncated NMA (enthalpy
nmode_min_9Å
) compromises the overall accuracy of MM/GBSA and MM/PBSA compared with the enthalpies calculated based on the minimized structures (enthalpy
min
). However, for the MD trajectories, the binding free energies can be improved by the inclusion of the conformation entropies predicted by either truncated-NMA for a relatively high dielectric constant (
in
= 4) or the interaction entropy method for
in
= 1-4. In terms of reproducing the absolute binding free energies, the binding free energies estimated by including the truncated-NMA entropies based on the MD trajectories (Δ
G
nmode_md_9Å
) give the lowest average absolute deviations against the experimental data among all the tested strategies for both MM/GBSA and MM/PBSA. Although the inclusion of the truncated NMA based on the MD trajectories (Δ
G
nmode_md_9Å
) for a relatively high dielectric constant gave the overall best result and the lowest average absolute deviations against the experimental data (for the ff03 force field), it needs too much computational time. Alternatively, considering that the interaction entropy method does not incur any additional computational cost and can give comparable (at high dielectric constant,
in
= 4) or even better (at low dielectric constant,
in
= 1-2) results than the truncated-NMA entropy (Δ
G
nmode_md_9Å
), the interaction entropy approach is recommended to estimate the entropic component for MM/GBSA and MM/PBSA based on MD trajectories, especially for a diverse dataset. Furthermore, we compared the predictions of MM/GBSA with six different AMBER force fields. The results show that the ff03 force field (ff03 for proteins and
gaff
with AM1-BCC charges for ligands) performs the best, but the predictions given by the tested force fields are comparable, implying that the MM/GBSA predictions are not very sensitive to force fields.
Nmode entropy and interaction entropy were assessed for MM/PB(GB)SA based on >1500 systems and 6 force fields.
(1) Background: Enterobius vermicularis infection causes a significant health burden in children. The infection occurs throughout the country and remains a serious public concern in China. Therefore, ...it is necessary to know the situation of E. vermicularis infection, to provide a scientific basis for the disease control and the optimum conditions for children's growth. (2) Methods: Descriptive epidemiological analysis was implemented to demonstrate the status and changing trend of E. vermicularis infection from 2016 to 2020, while the spatial distribution characteristics and spatial-temporal clustering were illuminated by spatial autocorrelation analysis and spatio-temporal scanning analysis. (3) Results: The infection of E. vermicularis showed a fluctuating downward trend with a decline of 32.00% in 2020 compared to that in 2016 and was concentrated in central and southern China. There was no significant difference in infection rate between boys and girls, while the high infection rate was presented in 4-, 5- and 6- year-old children. The hotspots and spatial clustering areas were mainly concentrated in southern China. (4) Conclusions: From 2016 to 2020, the infection rate of E. vermicularis in children aged 3 to 9 years in China demonstrated a declining trend, and its distribution showed spatial clustering, mainly in southern China. Therefore, it is necessary to strengthen surveillance and implement control measures in combination with health education and environmental improvement.
Extensive efforts have been devoted to determining the binding specificity of Src homology 3 (SH3) domains usually in a case-by-case manner. A generic structure-based model is necessary to decipher ...the protein recognition code of the entire domain family. In this study, we have developed a general framework that combines molecular modeling and a machine learning algorithm to capture the energetic characteristics of the domain-peptide interactions and predict the binding specificity of the SH3 domain family. Our model is not trained for individual SH3 domains; rather it is a generic model for the entire domain family. Our model not only achieved satisfactory prediction accuracy but also provided structural insights into which residues are important for the binding specificity. The success of our framework on SH3 domains suggests that it is possible to establish a theoretical model to decipher the protein recognition code of any modular domain.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Human clearance is often predicted prior to clinical study from in vivo preclinical data by virtue of interspecies allometric scaling methods. The aims of this study were to determine the important ...molecular descriptors for the extrapolation of animal data to human clearance and further to build a model to predict human clearance by combination of animal data and the selected molecular descriptors. These important molecular descriptors selected by genetic algorithm (GA) were from five classes: quantum mechanical, shadow indices, E‐state keys, molecular properties, and molecular property counts. Although the data set contained many outliers determined by the conventional Mahmood method, the variation of most outliers was reduced significantly by our final support vector machine (SVM) model. The values of cross‐validated correlation coefficient and root‐mean‐squared error (RMSE) for leave‐one‐out cross‐validation (LOOCV) of the final SVM model were 0.783 and 0.305, respectively. Meanwhile, the reliability and consistency of the final model were also validated by an external test set. In conclusion, the SVM model based on the molecular descriptors selected by GA and animal data achieved better prediction performance than the Mahmood method. This approach can be applied as an improved interspecies allometric scaling method in drug research and development.
A SVM model based on molecular descriptors and animal data was built to predict human clearance. Compared with the conventional Mahmood method, the SVM model, constructed on the 122 commercially available drugs, can markedly enhance the prediction performance of CLhuman. This approach should be considered as an improved allometric scaling method in further drug research and development.
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BFBNIB, DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, SIK, UILJ, UKNU, UL, UM, UPUK
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