Thermodynamic Transferability in Coarse-Grained Force Fields Using Graph Neural Networks.

Coarse-graining is a molecular modeling technique in which an atomistic system is represented in a simplified fashion that retains the most significant system features that contribute to a target output while removing the degrees of freedom that are less relevant. This reduction in model complexity allows coarse-grained molecular simulations to reach increased spatial and temporal scales compared with corresponding all-atom models. A core challenge in coarse-graining is to construct a force field that represents the interactions in the new representation in a way that preserves the atomistic-level properties.

Growing Desmoplastic Three-Dimensional Pancreatic Cancer Spheroids from Co-Culture.

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers with a 5-year survival rate of <12%. The biggest barrier to therapy is the dense desmoplastic extracellular matrix (ECM) that surrounds the tumor and reduces vascularization, generally termed desmoplasia. A variety of drug combinations and formulations have been tested to treat the cancer, and although many of them show success pre-clinically, they fail clinically.