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Accurate prediction of ligand-receptor binding affinity is crucial in structure-based drug design, significantly impacting the development of effective drugs. Recent advances in machine learning (ML)–based scoring functions have improved these predictions, yet challenges remain in modeling complex molecular interactions. This study introduces the AGL-EAT-Score, a scoring function that integrates extended atom-type multiscale weighted colored subgraphs with algebraic graph theory. This approach leverages the eigenvalues and eigenvectors of graph Laplacian and adjacency matrices to capture high-level details of specific atom pairwise interactions. Evaluated against benchmark datasets such as CASF-2016, CASF-2013, and the Cathepsin S dataset, the AGL-EAT-Score demonstrates notable accuracy, outperforming existing traditional and ML-based methods. The model's strength lies in its comprehensive similarity analysis, examining protein sequence, ligand structure, and binding site similarities, thus ensuring minimal bias and over-representation in the training sets. The use of extended atom types in graph coloring enhances the model's capability to capture the intricacies of protein-ligand interactions. The AGL-EAT-Score marks a significant advancement in drug design, offering a tool that could potentially refine and accelerate the drug discovery process. Scientific Contribution The AGL-EAT-Score presents an algebraic graph-based framework that predicts ligand-receptor binding affinity by constructing multiscale weighted colored subgraphs from the 3D structure of protein-ligand complexes. It improves prediction accuracy by modeling interactions between extended atom types, addressing challenges like dataset bias and over-representation. Benchmark evaluations demonstrate that AGL-EAT-Score outperforms existing methods, offering a robust and systematic tool for structure-based drug design. [ABSTRACT FROM AUTHOR]

Tropomyosin kinase receptor B (TrkB) has been explored as a therapeutic target for neurological and psychiatric disorders. However, the development of TrkB agonists was hindered by our poor understanding of the TrkB agonist binding location and affinity (both affect the regulation of disorder types). This motivated us to develop a combined computational and experimental approach to study TrkB binders. First, we developed a docking method to simulate the binding affinity of TrkB and binders identified by our magnetic drug screening platform from Gotu kola extracts. The Fred Docking scores from the docking computation showed strong agreement with the experimental results. Subsequently, using this screening platform, we identified a list of compounds from the NIH clinical collection library and applied the same docking studies. From the Fred Docking scores, we selected two compounds for TrkB activation tests. Interestingly, the ability of the compounds to increase dendritic arborization in hippocampal neurons matched well with the computational results. Finally, we performed a detailed binding analysis of the top candidates and compared them with the best-characterized TrkB agonist, 7,8-dyhydroxyflavon. The screening platform directly identifies TrkB binders, and the computational approach allows for the quick selection of top candidates with potential biological activities based on the docking scores. [ABSTRACT FROM AUTHOR]

Processing is one of the important and crucial parts that has been applied in traditional oriental medicine for a long time. The traditional ingredients were processed on the basis of the Yin Yang theory, Five Elements theory, and folk experiences. Among many processing techniques, honey-frying is a process enhancing the effects of traditional herbs on the Spleen and Stomach organs. This report provides an overview of the differences between chemical constituents and pharmacological activities of some traditional ingredients before and after roasting with honey. [ABSTRACT FROM AUTHOR]

Based on the first-order shear deformation theory taking into account geometrical nonlinearity, initial geometrical imperfection, vibration and nonlinear dynamic analysis of the sandwich laminated composite panel characterized by a continuous thickness variation in thermal environment and resting on an elastic foundation are considered in this paper. Variable thickness could affect the design of composite panel since it allows to tailor the stiffness features in the most stressed areas within the domain, keeping the weight constant. As a consequence, an improved dynamic behavior of the structure may be exhibited. The motion equations of dynamic analysis are determined due to Galerkin method and the obtained equation is numerically solved by using Runge–Kutta method. In numerical results, the effects of initial geometrical imperfections and geometrical parameters, material properties, coefficients of foundation, mechanical loads, temperature and the variable thickness on the nonlinear dynamic response and vibration of the laminated composite panel are investigated. [ABSTRACT FROM AUTHOR]

This article explores the impact of surface area, volume, curvature, and Lennard-Jones (LJ) potential on solvation free energy predictions. Rigidity surfaces are utilized to generate robust analytical expressions for maximum, minimum, mean, and Gaussian curvatures of solvent-solute interfaces, and define a generalized Poisson-Boltzmann (GPB) equation with a smooth dielectric profile. Extensive correlation analysis is performed to examine the linear dependence of surface area, surface enclosed volume, maximum curvature, minimum curvature, mean curvature, and Gaussian curvature for solvation modeling. It is found that surface area and surfaces enclosed volumes are highly correlated to each other's, and poorly correlated to various curvatures for six test sets of molecules. Different curvatures are weakly correlated to each other for six test sets of molecules, but are strongly correlated to each other within each test set of molecules. Based on correlation analysis, we construct twenty six nontrivial nonpolar solvation models. Our numerical results reveal that the LJ potential plays a vital role in nonpolar solvation modeling, especially for molecules involving strong van der Waals interactions. It is found that curvatures are at least as important as surface area or surface enclosed volume in nonpolar solvation modeling. In conjugation with the GPB model, various curvature-based nonpolar solvation models are shown to offer some of the best solvation free energy predictions for a wide range of test sets. For example, root mean square errors from a model constituting surface area, volume, mean curvature, and LJ potential are less than 0.42 kcal/mol for all test sets. © 2016 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Antibiotics like rifampicin are often persistent in the environment. When entering the water, it causes antimicrobial resistance that affects the ecosystem and accumulates in the aquatic organisms and affects human health through the food chain. In this study, titanium dioxide was doped with neodymium (0.01 to 0.8%) using the sol-gel hydrothermal method. TiO 2 /Nd was then coated on rice husk ash to produce a modified TiO 2 /Nd/rice husk ash material containing 0.36% (w/w) Nd. The structural characteristics and photocatalytic properties of the materials were analyzed by X-ray diffraction, energy dispersive X-ray, transmission electron microscopy, scanning electron microscopy, forbidden zone energy, and specific surface area. The TiO 2 /Nd material exhibited a higher photocatalytic decomposition capacity than TiO 2 and depended on the Nd content. The rifampicin removal efficiency of TiO 2 /Nd materials with 0.36 to 0.80% Nd contents was approximately 40% higher than that of TiO 2 /Nd containing 0.01 to 0.28% Nd. A new photocatalytic TiO 2 /Nd/rice husk ash material was developed to decompose rifampicin. The rifampicin-degrading efficiency of TiO 2 /Nd and TiO 2 /Nd/rice husk ash material reached approximately 86 and 75%, respectively, within 90 min under sunlight. Although a lower efficiency was obtained, the TiO 2 /Nd/rice husk ash material was selected to degrade rifampicin residue in water via the photocatalytic process (under sunlight) because of its advantages such as requirement of a small amount and easy recovery. In the rifampicin removal process, k values were found to match the zero- and first-order kinetics. In particular, for TiO 2 /Nd and TiO 2 /Nd/rice husk ash under solar irradiation, R 2 values reached approximately 0.98. These results have been previously published as a preprint., Competing Interests: The authors declare that there are no conflicts of interest regarding the publication of this paper., (Copyright © 2022 Thuy Dang Thi Ngoc et al.)