Constrained template matching using rejection sampling

Identifying macromolecular complexes in situ using cryo-electron tomography remains challenging, with low signal-to-noise ratios and heterogeneous backgrounds among the key limiting factors. By integrating prior knowledge on macromolecular localization, such as the preferred orientations of membrane-associated proteins, detection can be improved by constraining searches to biologically feasible orientations. However, previous approaches integrating such constraints fail to achieve both computational scalability to large and curved systems and accurate detection. To resolve this, here we present rejection sampling, a novel approach for integrating translational and rotational constraints into template matching. Using simulated influenza virus-like particles, we demonstrate that rejection sampling outperforms existing methods in terms of precision and recall. Our approach can uniquely integrate constraints at voxel resolution while being compatible with imaging filters such as the contrast transfer function, essential for accurate macromolecular localization. Rejection sampling thus provides a practical solution for macromolecular detection in large and curved systems.