CondenSimAdapter: A Versatile Builder for Multiscale Simulations of Protein Condensates with Broad Force-Field Compatibility and Robust Dense-Phase Relaxation.

Multiscale molecular dynamics simulations that sequentially couple coarse-grained (CG) sampling with all-atom (AA) simulation are widely used to study biomolecular condensates, yet building such multiscale systems remains a practical challenge. Dense CG condensate configurations must be backmapped and converted into stable, explicitly solvated AA systems─a step where severe steric clashes often prevent production simulation, creating a "relaxation bottleneck". Here, we introduce CondenSimAdapter, a Python package that bridges this resolution gap by integrating SE(3)-transformer-based cg2all backmapping with a physics-inspired optimization protocol (using Gaussian repulsion and soft-core potentials), which succeeds where standard energy minimization fails. CondenSimAdapter unifies four CG and nine AA force fields under a single interface. We validated the workflow by (1) demonstrating the robust elimination of major structure conflicts across diverse CG-AA combinations, (2) verifying its functional versatility in preserving the structural integrity of multidomain proteins, and (3) confirming ensemble fidelity via a 2 μs atomistic simulation of a FUS LC condensate that accurately reproduced established macroscopic and microscopic properties. By resolving the dense-phase relaxation bottleneck and providing a highly accessible, streamlined workflow, CondenSimAdapter lowers the technical barrier to multiscale condensate simulations and enables systematic, high-throughput studies of protein phase separation. CondenSimAdapter is freely available at https://github.com/hanlab-computChem/CondenSimAdapter.