Automated assembly of protein complexes from cryo-EM maps with structure-informed Monte Carlo Tree Search

Abstract

Structural cell biology aims to visualize functional molecules as they carry out their biological roles in their native cellular context. However, macromolecular complexes in situ have thus far been resolved predominantly at intermediate resolutions, complicating protein identification and structural modeling due to the vast combinatorial space of possible components within a proteome. Here, we developed Cryosearch, a GPU-accelerated framework for automated assembly of macromolecular complexes from proteome-scale monomer libraries. Cryosearch implements Monte Carlo tree search with correlation-based rewards to identify combinations of protein domains that collectively best explain density maps. This approach enables autonomous de novo assembly of molecular complexes from intermediate-resolution maps.