VCMM: A visual tool for continuum molecular modeling

Targeting Oxidative Stress Markers, Xanthine Oxidase, TNFRSF11A and Cathepsin L in Curcumin-Treated Collagen-Induced Arthritis: A Physiological and COSMO-RS Study

The effectiveness of curcumin in preventing and treating collagen-induced inflammatory arthritis (CIA) in rats and oxidative stress in rats was investigated. We investigated curcumin's curative and preventive effects on paw edema, arthritic size, body weight, and radiologic and histological joint abnormalities. It has been shown that curcumin may dramatically lower the risk of developing arthritis. In addition, the number of white blood cells (WBCs) in the body has dropped, which is a strong indication that curcumin has anti-inflammatory characteristics. A follow-up theoretical investigation of curcumin molecular docking on xanthine oxidase (XO) was carried out after the properties of curcumin were determined using the conductor-like screening model for real solvents (COSMO-RS) theory. Because of the interaction between curcumin and the residues on XO named Ile264, Val259, Asn351, and Leu404, XO may be suppressed by this molecule. Curcumin's anti-inflammatory and antioxidant properties may be responsible for the anti-arthritic effects that have been seen on oxidative stress markers and XO. On the other hand, more research is being conducted to understand its function better in the early stages of rheumatoid arthritis (RA). To determine whether or not curcumin interacts with AR targets, a molecular docking study was conducted using MVD software against TNFRSF11A and cathepsin L.

Molecular Sparse Representation by a 3D Ellipsoid Radial Basis Function Neural Network via L1 Regularization

The three-dimensional structures and shapes of biomolecules provide essential information about their interactions and functions. Unfortunately, the computational cost of biomolecular shape representation is an active challenge which increases rapidly as the number of atoms increase. Recent developments in sparse representation and deep learning have shown significant improvements in terms of time and space. A sparse representation of molecular shape is also useful in various other applications, such as molecular structure alignment, docking, and coarse-grained molecular modeling. We have developed an ellipsoid radial basis function neural network (ERBFNN) and an algorithm for sparsely representing molecular shape. To evaluate a sparse representation model of molecular shape, the Gaussian density map of the molecule is approximated using ERBFNN with a relatively small number of neurons. The deep learning models were trained by optimizing a nonlinear loss function with L1 regularization. Experimental results reveal that our algorithm can represent the original molecular shape with a relatively higher accuracy and fewer scale of ERBFNN. Our network in principle is applicable to the multiresolution sparse representation of molecular shape and coarse-grained molecular modeling. Executable files are available at https://github.com/SGUI-LSEC/SparseGaussianMolecule. The program was implemented in PyTorch and was run on Linux.

Frontiers in biomolecular mesh generation and molecular visualization systems

With the development of biomolecular modeling and simulation, especially implicit solvent modeling, higher requirements are set for the stability, efficiency and mesh quality of molecular mesh generation software. In this review, we summarize the recent works in biomolecular mesh generation and molecular visualization. First, we introduce various definitions of molecular surface and corresponding meshing software. Second, as the mesh quality significantly influences biomolecular simulation, we investigate some remeshing methods in the fields of computer graphics and molecular modeling. Then, we show the application of biomolecular mesh in the boundary element method (BEM) and the finite element method (FEM). Finally, to conveniently visualize the numerical results based on the mesh, we present two types of molecular visualization systems.

Molecular Surface Remeshing with Local Region Refinement

Molecular surface mesh generation is a prerequisite for using the boundary element method (BEM) and finite element method (FEM) in implicit-solvent modeling. Molecular surface meshes typically have small angles, redundant vertices, and low-quality elements. In the implicit-solvent modeling of biomolecular systems it is usually required to improve the mesh quality and eliminate low-quality elements. Existing methods often fail to efficiently remove low-quality elements, especially in complex molecular meshes. In this paper, we propose a mesh refinement method that smooths the meshes, eliminates invalid regions in a cut-and-fill strategy, and improves the minimal angle. We compared our method with four different state-of-the-art methods and found that our method showed a significant improvement over state-of-the-art methods in minimal angle, aspect ratio, and other meshing quality measurements. In addition, our method showed satisfactory results in terms of the ratio of regular vertices and the preservation of area and volume.