11 papers
ProteoCraft: Protein Design as Proposal-Verification Search
Fang Wu, Hongbin Lin, Bingchen Duan +24
Protein-protein interactions underpin nearly all biological processes. Yet, designing proteins with desired interactions remains challenging due to the structural complexity govern…
RiboBridge: protein-conditioned de novo RNA binder structure design
Zhou Zhang, Hanqun Cao, Minghao Sun +5
Designing RNA molecules that bind to target protein structures requires generating both an RNA conformation and its bound complex geometry, without assuming a predefined binding si…
Feedback-Calibrated Protein Optimization with Batch-Aligned Tail Arbitration
Zefeng Lin, Xianyong Fang, Tianfan Fu +1
Protein optimization aims to discover high-fitness sequences under a limited experimental budget. Existing machine-learning methods use task-specific predictors, biological priors,…
RNA Design via Conditioned Flow Matching and Finite-Policy Reinforcement Learning
Zefeng Lin, Xianyong Fang, Tianfan Fu +1
RNA design aims to identify sequences that fold into specified secondary structures. Existing methods formulate the task as target-specific search or conditional generation. Howeve…
Preserving Continuous Symmetry in Discrete Spaces: Geometric-Aware Quantization for SO(3)-Equivariant GNNs
Haoyu Zhou, Ping Xue, Hao Zhang +1
Equivariant Graph Neural Networks (GNNs) are essential for physically consistent molecular simulations but suffer from high computational costs and memory bottlenecks, especially w…
Quantized SO(3)-Equivariant Graph Neural Networks for Efficient Molecular Property Prediction
Haoyu Zhou, Ping Xue, Hao Zhang +1
Deploying 3D graph neural networks (GNNs) that are equivariant to 3D rotations (the group SO(3)) on edge devices is challenging due to their high computational cost. This paper add…
RiboSphere: Learning Unified and Efficient Representations of RNA Structures
Zhou Zhang, Hanqun Cao, Cheng Tan +3
Accurate RNA structure modeling remains difficult because RNA backbones are highly flexible, non-canonical interactions are prevalent, and experimentally determined 3D structures a…
Navigating heterogeneous protein landscapes through geometry-aware smoothing
Srinivas Anumasa, Barath Chandran, Tingting Chen +15
The evolutionary fitness landscape of biological molecules is extremely sparse and heterogeneous, with functional sequences forming isolated dense ``islands'' within a vast combina…
EnzyPGM: Pocket-conditioned Generative Model for Substrate-specific Enzyme Design
Zefeng Lin, Zhihang Zhang, Weirong Zhu +4
Designing enzymes with substrate-binding pockets is a critical challenge in protein engineering, as catalytic activity depends on the precise interaction between pockets and substr…
RadDiff: Retrieval-Augmented Denoising Diffusion for Protein Inverse Folding
Jin Han, Tianfan Fu, Wu-Jun Li
Protein inverse folding, the design of an amino acid sequence based on a target protein structure, is a fundamental problem of computational protein engineering. Existing methods e…
RiboPO: Preference Optimization for Structure- and Stability-Aware RNA Design
Minghao Sun, Hanqun Cao, Zhou Zhang +10
Designing RNA sequences that reliably adopt specified three-dimensional structures while maintaining thermodynamic stability remains challenging for synthetic biology and therapeut…