Optimal Bond Constraint Topology for Molecular Dynamics Simulations of Cholesterol

G protein pathway suppressor 2 suppresses aerobic glycolysis through RACK1-mediated HIF-1α degradation in breast cancer

Aerobic glycolysis has been recognized as a hallmark of human cancer. G protein pathway suppressor 2 (GPS2) is a negative regulator of the G protein-MAPK pathway and a core subunit of the NCoR/SMRT transcriptional co-repressor complex. However, how its biological properties intersect with cellular metabolism in breast cancer (BC) development remains poorly elucidated. Here, we report that GPS2 is low expressed in BC tissues and negatively correlated with poor prognosis. Both in vitro and in vivo studies demonstrate that GPS2 suppresses malignant progression of BC. Moreover, GPS2 suppresses aerobic glycolysis in BC cells. Mechanistically, GPS2 destabilizes HIF-1α to reduce the transcription of its downstream glycolytic regulators (PGK1, PGAM1, ENO1, PKM2, LDHA, PDK1, PDK2, and PDK4), and then suppresses cellular aerobic glycolysis. Notably, receptor for activated C kinase 1 (RACK1) is identified as a key ubiquitin ligase for GPS2 to promote HIF-1α degradation. GPS2 stabilizes the binding of HIF-1α to RACK1 by directly binding to RACK1, resulting in polyubiquitination and instability of HIF-1α. Furthermore, amino acid residues 70-92 aa of the GPS2 N-terminus bind RACK1. A 23-amino-acid-long GPS2-derived peptide was developed based on this N-terminal region, which promotes the interaction of RACK1 with HIF-1α, downregulates HIF-1α expression and significantly suppresses BC tumorigenesis in vitro and in vivo. In conclusion, our findings indicate that GPS2 decreases the stability of HIF-1α, which in turn suppresses aerobic glycolysis and tumorigenesis in BC, suggesting that targeting HIF-1α degradation and treating with peptides may be a promising approach to treat BC.

Enhancing the Biopharmacological Characteristics of Asperosaponin VI: Unveiling Dynamic Self-Assembly Phase Transitions in the Gastrointestinal Environment

Purpose

Asperosaponin VI (ASP VI) as an active ingredient of Dipsacus asperoides, which has a wide range of biological and pharmacological activity. However, its development and application are restricted due to the poor gastrointestinal permeability and oral bioavailability. This investigation aims to reveal the influence of the self-assembled structure by the interaction between ASP VI and endogenous components NaTC and/or DOPC in the gastrointestinal environment on its biopharmaceutical properties, and novelty elucidated the molecular mechanism for the formation of self-assembled nanomicelles.

Methods

This change in phase state in gastrointestinal fluids is characterized by dynamic light scattering (DLS) and transmission electron microscope (TEM). UPLC-Q-TOF-MS was used to analyze the composition of phase components and the exposure of nanomicelles in vivo. Molecular dynamics simulation (MDS) was applied to preliminarily elucidate the self-assembly mechanism of ASP VI in the gastrointestinal environment. Furthermore, theS8 promoting absorption mechanism of nanomicelles were investigated through in vivo pharmacokinetic experiments, parallel artificial membrane permeability assay (PAMPA), quadruple single-pass intestinal perfusion in rats, and Caco-2 cell monolayer model.

Results

We demonstrated that the ASP VI could spontaneously form dynamic self-assembled structures with sodium taurocholate (NaTC) and dipalmitoyl phosphatidylcholine (DOPC) during gastrointestinal solubilization, which promoted the gastrointestinal absorption and permeability of ASP VI and increased its exposure in vivo, thus improving the biopharmacological characteristics of ASP VI. Moreover, ASP VI-NaTC-DOPC-self-assembled nanostructures (ASP VI-NaTC-DOPC-SAN) manifested higher cellular uptake in Caco-2 cells as evidenced by flow cytometry and confocal microscopy, and this study also preliminarily revealed the mechanism of self-assembly formation of ASP VI with endogenous components NaTC and DOPC driven by electrostatic and hydrogen bonding interactions.

Conclusion

This study provides evidence that the dynamic self-assembled phase transition may play a key role in improving the biopharmacological characteristics of insoluble or low permeability active ingredients during the gastrointestinal dissolution of Chinese medicines.

CGCompiler: Automated Coarse-Grained Molecule Parametrization via Noise-Resistant Mixed-Variable Optimization

Coarse-grained force fields (CG FFs) such as the Martini model entail a predefined, fixed set of Lennard-Jones parameters (building blocks) to model virtually all possible nonbonded interactions between chemically relevant molecules. Owing to its universality and transferability, the building-block coarse-grained approach has gained tremendous popularity over the past decade. The parametrization of molecules can be highly complex and often involves the selection and fine-tuning of a large number of parameters (e.g., bead types and bond lengths) to optimally match multiple relevant targets simultaneously. The parametrization of a molecule within the building-block CG approach is a mixed-variable optimization problem: the nonbonded interactions are discrete variables, whereas the bonded interactions are continuous variables. Here, we pioneer the utility of mixed-variable particle swarm optimization in automatically parametrizing molecules within the Martini 3 coarse-grained force field by matching both structural (e.g., RDFs) as well as thermodynamic data (phase-transition temperatures). For the sake of demonstration, we parametrize the linker of the lipid sphingomyelin. The important advantage of our approach is that both bonded and nonbonded interactions are simultaneously optimized while conserving the search efficiency of vector guided particle swarm optimization (PSO) methods over other metaheuristic search methods such as genetic algorithms. In addition, we explore noise-mitigation strategies in matching the phase-transition temperatures of lipid membranes, where nucleation and concomitant hysteresis introduce a dominant noise term within the objective function. We propose that noise-resistant mixed-variable PSO methods can both improve and automate parametrization of molecules within building-block CG FFs, such as Martini.

Martini 3 Coarse-Grained Force Field for Cholesterol

Cholesterol plays a crucial role in biomembranes by regulating various properties, such as fluidity, rigidity, permeability, and organization of lipid bilayers. The latest version of the Martini model, Martini 3, offers significant improvements in interaction balance, molecular packing, and inclusion of new bead types and sizes. However, the release of the new model resulted in the need to reparameterize many core molecules, including cholesterol. Here, we describe the development and validation of a Martini 3 cholesterol model, addressing issues related to its bonded setup, shape, volume, and hydrophobicity. The proposed model mitigates some limitations of its Martini 2 predecessor while maintaining or improving the overall behavior.

Efficient generation of random rotation matrices in four dimensions

Four-dimensional (4D) rotations have applications in the fields of robotics, computer vision, and rigid-body mechanics. In the latter, they can be used to transform between equimomental systems of point masses. Here we provide an efficient algorithm to generate random 4D rotation matrices covering an arbitrary, predefined range of rotation angles. These matrices can be combined with Monte Carlo methods for the efficient sampling of the SO(4) group of 4D rotations. The matrices are unbiased and constructed such that repeated rotations result in uniform sampling over SO(4). The algorithm can be used to optimize the mass partitioning in coarse-grained simulation models of molecules involving coupled constraints for stable time integration.