Bartender: Martini 3 Bonded Terms via Quantum Mechanics-Based Molecular Dynamics.

Coarse-grained (CG) molecular dynamics (MD) simulations have grown in applicability over the years. The recently released version of the Martini CG force field (Martini 3) has been successfully applied to simulate many processes, including protein-ligand binding. However, the current ligand parametrization scheme is manual and requires an a priori reference all-atom (AA) simulation for benchmarking. For systems with suboptimal AA parameters, which are often unknown, this translates into a CG model that does not reproduce the true dynamical behavior of the underlying molecule. Here, we present Bartender, a quantum mechanics (QM)/MD-based parametrization tool written in Go. Bartender harnesses the power of QM simulations and produces reasonable bonded terms for Martini 3 CG models of small molecules in an efficient and user-friendly manner. For small, ring-like molecules, Bartender generates models whose properties are indistinguishable from the human-made models. For more complex, drug-like ligands, it is able to fit functional forms beyond simple harmonic dihedrals and thus better captures their dynamical behavior. Bartender has the power to both increase the efficiency and the accuracy of Martini 3-based high-throughput applications by producing numerically stable and physically realistic CG models.

Glyphosate mimics 17ß-estradiol effects promoting estrogen receptor alpha activity in breast cancer cells.

Glyphosate, the active ingredient in several broad-spectrum herbicide formulations, has been validated and widely used throughout the world. Recent reports have questioned its safety, showing that glyphosate may act as an endocrine disruptor by promoting estrogenic activity. However, the molecular mechanism involved in this phenomenon remains unclear. Therefore, here we aimed to elucidate the mechanism by which glyphosate induces estrogenic activity using estrogen-sensitive breast cancer cell line models. Our results show that glyphosate mimics the cell effects of 17ß-estradiol (E2), promoting estrogen receptor α (ERα) phosphorylation, its degradation, and transcriptional activity at high concentrations. The molecular mechanism seems involved in the ERα ligand-binding domain (LBD). Molecular simulations suggest a plausible interaction between glyphosate and the LBD through a coordinated complex involving divalent cations such as Zn (II). In addition, glyphosate exposure alters the level of Cyclin-dependent kinase 7 that contribute to ERα phosphorylation. Finally, glyphosate increases cell proliferation rate and levels of cell cycle regulators, accompanied by an increase in anchorage-independent growth capacity. These findings suggest that glyphosate at high concentrations, induces estrogen-like effects through an ERα ligand binding site-dependent mechanism, leading to cellular responses resulting from a complex interplay of genomic and non-genomic events.