Zhenwei Luo

OPUS-ET improves cryo-ET resolution by resolving compositional and conformational heterogeneities using a deep learning framework, achieving sub-nanometer reconstructions and revealing structural dynamics in biomolecules.

OPUS-DSD2 disentangles structural heterogeneity in cryo-EM and cryo-ET data by separating rigid-body dynamics from other variations, improving analysis of macromolecular structures.

OPUS-BFactor predicts normalized protein B-factors using sequence or structural information, outperforming existing methods on benchmark datasets.

OPUS-TOMO improves resolution and resolves structural heterogeneity in cryo-ET data for biomolecules like ATP synthase and ribosomes.

OPUS-Rota5 improves protein side-chain modeling accuracy, enhancing molecular docking success rates for GPCR targets.

OPUS-Fold3 is a gradient-based protein folding and docking framework that generates accurate 3D structures under specified constraints, outperforming pyRosetta in side-chain modeling.